Question: A new rapid framework for topic labeling utilizing similarity-preserved hashing.

This paper introduces a novel framework for enhancing topic labeling by preserving similarity through hashing techniques. In the realm of text mining and knowledge management, statistical topic modeling has gained significant traction due to its robust capabilities. However, interpreting the semantic content of topics, often represented as probability distributions over words, remains a significant challenge. Topic labeling, a key method for interpretation, has recently garnered substantial interest. Prior efforts, however, have tended to overlook the hierarchical relationships among topics, focusing instead on individual topics in isolation. This oversight limits the creation of comprehensive hierarchical topic descriptors for topic hierarchies. To address this gap, we propose two innovative algorithms designed to automatically generate succinct labels for topics within a hierarchy. These algorithms leverage sibling and parent-child relationships among topics to enhance labeling accuracy. Our experimental findings confirm that incorporating inter-topic relationships significantly improves topic labeling performance. The proposed algorithms are capable of generating insightful topic labels that effectively aid in the interpretation of hierarchical topics, demonstrating their utility in knowledge management applications.

This paper presents a topic model that identifies interpretable low dimensional components in time-stamped data for capturing the evolution of trends. Unlike other models for time-stamped data, our proposal, the trend analysis model (TAM), focuses on the difference between temporal words and other words in each document to detect topic evolution over time. TAM introduces a latent trend class variable into each document and a latent switch variable into each token for handling these differences. The trend class has a probability distribution over temporal words, topics, and a continuous distribution over time, where each topic is responsible for generating words. The latter class uses a document specific probabilistic distribution to judge which variable each word comes from for generating words in each token. Accordingly, TAM can explain which topic co-occurrence pattern will appear at any given time, and represents documents of similar content and timestamp as sharing the same trend class. Therefore, TAM projects them on a latent space of trend dimensionality and allows us to predict the temporal evolution of words and topics in document collections. Experiments on various data sets show that the proposed model can capture interpretable low dimensionality sets of topics and timestamps, take advantage of previous models, and is useful as a generative model in the analysis of the evolution of trends.

The four-level pachinko allocation model (PAM) (Li & McCallum, 2006) represents correlations among topics using a DAG structure. It does not, however, represent a nested hierarchy of topics, with some topical word distributions representing the vocabulary that is shared among several more specific topics. This paper presents hierarchical PAM---an enhancement that explicitly represents a topic hierarchy. This model can be seen as combining the advantages of hLDA's topical hierarchy representation with PAM's ability to mix multiple leaves of the topic hierarchy. Experimental results show improvements in likelihood of held-out documents, as well as mutual information between automatically-discovered topics and humangenerated categories such as journals.

In this paper, we describe latent subtopics discovered from Yelp restaurant reviews by running an online Latent Dirichlet Allocation (LDA) algorithm. The goal is to point out demand of customers from a large amount of reviews, with high dimensionality. These topics can provide meaningful insights to restaurants about what customers care about in order to increase their Yelp ratings, which directly affects their revenue. We used the open dataset from the Yelp Dataset Challenge with over 158,000 restaurant reviews. To find latent subtopics from reviews, we adopted Online LDA, a generative probabilistic model for collections of discrete data such as text corpora. We present the breakdown of hidden topics over all reviews, predict stars per hidden topics discovered, and extend our findings to that of temporal information regarding restaurants peak hours. Overall, we have found several interesting insights and a method which could definitely prove useful to restaurant owners.

The problem of classification has been widely studied in the data mining, machine learning, database, and information retrieval communities with applications in a number of diverse domains, such as target marketing, medical diagnosis, news group filtering, and document organization. In this paper we will provide a survey of a wide variety of text classification

Word embedding maps words into a lowdimensional continuous embedding space by exploiting the local word collocation patterns in a small context window. On the other hand, topic modeling maps documents onto a low-dimensional topic space, by utilizing the global word collocation patterns in the same document. These two types of patterns are complementary. In this paper, we propose a generative topic embedding model to combine the two types of patterns. In our model, topics are represented by embedding vectors, and are shared across documents. The probability of each word is influenced by both its local context and its topic. A variational inference method yields the topic embeddings as well as the topic mixing proportions for each document. Jointly they represent the document in a low-dimensional continuous space. In two document classification tasks, our method performs better than eight existing methods, with fewer features. In addition, we illustrate with an example that our method can generate coherent topics even based on only one document.

Binary code learning, a.k.a., hashing, has been recently popular due to its high efficiency in large-scale similarity search and recognition. It typically maps high-dimensional data points to binary codes, where data similarity can be efficiently computed via rapid Hamming distance. Most existing unsupervised hashing schemes pursue binary codes by reducing the quantization error from an original real-valued data space to a resulting Hamming space. On the other hand, most existing supervised hashing schemes constrain binary code learning to correlate with pairwise similarity labels. However, few methods consider ordinal relations in the binary code learning process, which serve as a very significant cue to learn the optimal binary codes for similarity search. In this paper, we propose a novel hashing scheme, dubbed Ordinal Embedding Hashing (OEH), which embeds given ordinal relations among data points to learn the ranking-preserving binary codes. The core idea is to construct a directed unweighted graph to capture the ordinal relations, and then train the hash functions using this ordinal graph to preserve the permutation relations in the Hamming space. To learn such hash functions effectively, we further relax the discrete constraints and design a stochastic gradient decent algorithm to obtain the optimal solution. Experimental results on two large-scale benchmark datasets demonstrate that the proposed OEH method can achieve superior performance over the state-of-the-arts approaches. At last, the evaluation on query by humming dataset demonstrates the OEH also has good performance for music retrieval by using user’s humming or singing.

Thanks to the success of deep learning, cross-modal retrieval has made significant progress recently. However, there still remains a crucial bottleneck: how to bridge the modality gap to further enhance the retrieval accuracy. In this paper, we propose a self-supervised adversarial hashing (SSAH) approach, which lies among the early attempts to incorporate adversarial learning into cross-modal hashing in a self-supervised fashion. The primary contribution of this work is that two adversarial networks are leveraged to maximize the semantic correlation and consistency of the representations between different modalities. In addition, we harness a self-supervised semantic network to discover high-level semantic information in the form of multi-label annotations. Such information guides the feature learning process and preserves the modality relationships in both the common semantic space and the Hamming space. Extensive experiments carried out on three benchmark datasets validate that the proposed SSAH surpasses the state-of-the-art methods.

We present a non-traditional retrieval problem we call subtopic retrieval. The subtopic retrieval problem is concerned with finding documents that cover many different subtopics of a query topic. In such a problem, the utility of a document in a ranking is dependent on other documents in the ranking, violating the assumption of independent relevance which is assumed in most traditional retrieval methods. Subtopic retrieval poses challenges for evaluating performance, as well as for developing effective algorithms. We propose a framework for evaluating subtopic retrieval which generalizes the traditional precision and recall metrics by accounting for intrinsic topic difficulty as well as redundancy in documents. We propose and systematically evaluate several methods for performing subtopic retrieval using statistical language models and a maximal marginal relevance (MMR) ranking strategy. A mixture model combined with query likelihood relevance ranking is shown to modestly outperform a baseline relevance ranking on a data set used in the TREC interactive track.

We consider the problem of learning distributed representations for documents in data streams. The documents are represented as low-dimensional vectors and are jointly learned with distributed vector representations of word tokens using a hierarchical framework with two embedded neural language models. In particular, we exploit the context of documents in streams and use one of the language models to model the document sequences, and the other to model word sequences within them. The models learn continuous vector representations for both word tokens and documents such that semantically similar documents and words are close in a common vector space. We discuss extensions to our model, which can be applied to personalized recommendation and social relationship mining by adding further user layers to the hierarchy, thus learning user-specific vectors to represent individual preferences. We validated the learned representations on a public movie rating data set from MovieLens, as well as on a large-scale Yahoo News data comprising three months of user activity logs collected on Yahoo servers. The results indicate that the proposed model can learn useful representations of both documents and word tokens, outperforming the current state-of-the-art by a large margin.

Being a prevalent form of social communications on the Internet, billions of short texts are generated everyday. Discovering knowledge from them has gained a lot of interest from both industry and academia. The short texts have a limited contextual information, and they are sparse, noisy and ambiguous, and hence, automatically learning topics from them remains an important challenge. To tackle this problem, in this paper, we propose a semantics-assisted non-negative matrix factorization (SeaNMF) model to discover topics for the short texts. It effectively incorporates the word-context semantic correlations into the model, where the semantic relationships between the words and their contexts are learned from the skip-gram view of the corpus. The SeaNMF model is solved using a block coordinate descent algorithm. We also develop a sparse variant of the SeaNMF model which can achieve a better model interpretability. Extensive quantitative evaluations on various realworld short text datasets demonstrate the superior performance of the proposed models over several other state-of-the-art methods in terms of topic coherence and classification accuracy. The qualitative semantic analysis demonstrates the interpretability of our models by discovering meaningful and consistent topics. With a simple formulation and the superior performance, SeaNMF can be an effective standard topic model for short texts.


Question: A future perspective on flexible radio access beyond 5G: waveform, numerology, and frame design principles.

This comprehensive survey explores the landscape of multicarrier communications, focusing on prototype filters, lattice structures, and implementation aspects. The widespread adoption of orthogonal frequency division multiplexing (OFDM) in communication standards has sparked significant research interest in multicarrier systems, prompting a re-examination of various techniques as potential alternatives to OFDM. The survey aims to not only offer an integrated review of waveform design options for multicarrier schemes but also to outline a roadmap for their advancement from current capabilities to future technologies. A generalized framework for multicarrier schemes is introduced, encompassing three critical components: the symbols to transmit, the filters to use for transmission, and the lattice for determining where and when to transmit. This framework serves as a basis for examining a range of multicarrier systems, including orthogonal, bi-orthogonal, and non-orthogonal schemes. The survey delves into filter design considerations for various multicarrier systems, analyzing them from four distinct perspectives: energy concentration, rapid decay, spectrum nulling, and compatibility with channel and hardware characteristics. Evaluation tools for comparing filters across multicarrier schemes are also explored. Lastly, the survey assesses multicarrier schemes from a practical standpoint, addressing issues such as lattice adaptation, equalization, synchronization, multiple antennas, and the impact of hardware limitations.

Commercial automotive radars used today are based on frequency modulated continuous wave signals due to the simple and robust detection method and good accuracy. However, the increase in both the number of radars deployed per vehicle and the number of such vehicles leads to mutual interference, cutting short future plans for autonomous driving and active safety functionality. We propose and analyze a radar communication (RadCom) approach to reduce this mutual interference while simultaneously offering communication functionality. We achieve this by frequency division multiplexing radar and communication, where communication is built on a decentralized carrier sense multiple access protocol and is used to adjust the timing of radar transmissions. Our simulation results indicate that radar interference can be significantly reduced, at no cost in radar accuracy.

Large-scale multiple-input multiple-output (MIMO) systems enable high spectral efficiency by employing large antenna arrays at both the transmitter and the receiver of a wireless communication link. In traditional MIMO systems, full digital beamforming is done at the baseband; one distinct radio-frequency (RF) chain is required for each antenna, which for large-scale MIMO systems can be prohibitive from either cost or power consumption point of view. This paper considers a two-stage hybrid beamforming structure to reduce the number of RF chains for large-scale MIMO systems. The overall beamforming matrix consists of analog RF beamforming implemented using phase shifters and baseband digital beamforming of much smaller dimension. This paper considers precoder and receiver design for maximizing the spectral efficiency when the hybrid structure is used at both the transmitter and the receiver. On the theoretical front, bounds on the minimum number of transmit and receive RF chains that are required to realize the theoretical capacity of the large-scale MIMO system are presented. It is shown that the hybrid structure can achieve the same performance as the fully-digital beamforming scheme if the number of RF chains at each end is greater than or equal to twice the number of data streams. On the practical design front, this paper proposes a heuristic hybrid beamforming design strategy for the critical case where the number of RF chains is equal to the number of data streams, and shows that the performance of the proposed hybrid beamforming design can achieve spectral efficiency close to that of the fully-digital solution.

Communication systems in practice are subject to many technical/technological constraints and restrictions. Multiple input, multiple output (MIMO) processing in current wireless communications, as an example, mostly employs codebook-based pre-coding to save computational complexity at the transmitters and receivers. In such cases, closed form expressions for capacity or bit-error probability are often unattainable; effects of realistic signal processing algorithms on the performance of practical communication systems rather have to be studied in simulation environments. The Vienna LTE-A Uplink Simulator is a 3GPP LTE-A standard compliant MATLAB-based link level simulator that is publicly available under an academic use license, facilitating reproducible evaluations of signal processing algorithms and transceiver designs in wireless communications. This paper reviews research results that have been obtained by means of the Vienna LTE-A Uplink Simulator, highlights the effects of single-carrier frequency-division multiplexing (as the distinguishing feature to LTE-A downlink), extends known link adaptation concepts to uplink transmission, shows the implications of the uplink pilot pattern for gathering channel state information at the receiver and completes with possible future research directions.

This paper presents a 64 GHz transmit/receive communication link between two 32-element SiGe-based phased arrays. The antenna element is a series-fed patch array, which provides directivity in the elevation plane. The transmit array results in an EIRP of 42 dBm, while the receive array provides an electronic gain of 33 dB and a system NF < 8 dB including the T/R switch and antenna losses. The arrays can be scanned to +/−50° in the azimuth using a 5-bit phase shifter on the SiGe chip, while keeping very low sidelobes and a near-ideal pattern. The communication link uses one array on the transmit side and another array on the receive side, together with external mixers and IF amplifiers. A Keysight M8195A arbitrary waveform generator is used to generate the modulated waveforms on the transmit side and a Keysight DSO804A oscilloscope is used to demodulate the received IF signal. The link performance was measured for different scan angles and modulation formats. Data rates of 1 Gbps using 16-QAM and 2 Gbps using QPSK are demonstrated at 300 m. The system also results in > 4 Gbps data rate at 100 meters, and ∼ 500 Mbps data rate at 800 meters.

This article presents a high-level overview of the IEEE 802.22 standard for cognitive wireless regional area networks (WRANs) that is under development in the IEEE 802 LAN/MAN Standards Committee.

In this paper we present methods for the design of planar frequency-modulated continuous-wave (FMCW) multiple-input multiple-output (MIMO) arrays with an emphasis on the problem of moving targets in time-division multiple-access (TDMA) systems. We discuss the influence of target motion and boundaries of operation and present a method to compensate for its effects, which requires special attention in the array design and in signal processing. Array design techniques, examples including an implementation, and measurement results are also covered in this article.

For the development of new 5G systems to operate in bands up to 100 GHz, there is a need for accurate radio propagation models at these bands that currently are not addressed by existing channel models developed for bands below 6 GHz. This document presents a preliminary overview of 5G channel models for bands up to 100 GHz. These have been derived based on extensive measurement and ray tracing results across a multitude of frequencies from 6 GHz to 100 GHz, and this document describes an initial 3D channel model which includes: 1) typical deployment scenarios for urban microcells (UMi) and urban macrocells (UMa), and 2) a baseline model for incorporating path loss, shadow fading, line of sight probability, penetration and blockage models for the typical scenarios. Various processing methodologies such as clustering and antenna decoupling algorithms are also presented.

Cognitive radio (CR) can facilitate the issue of range shortage by permitting secondary users to coincide with incumbent clients in authorized range groups, while it causes no interference to occupant interchanges. Spectrum sensing is the essential in enabling innovation of CR to detect the presence of primary users (PUs) or authorized user signals and adventure the spectrum holes. Henceforth, this paper addresses the testing of spectrum sensing method for Differential Phase Shift Keying (DPSK) transceiver by utilizing an open source programming, GNU Radio. Moreover, the effect of various reproduction channels, for example, Dynamic channel demonstrate with Rayleigh fading, dynamic channel display with Rician fading, frequency selective faded channel show with Rayleigh and frequency selective faded channel show with Rician fading are exhibited.

Vehicle-to-vehicle (V2V) communications aim to enhance driver safety and traffic efficiency by using the recently designated frequency bands in the 5.9 GHz range in Europe. Due to the time-frequency selective fading behavior of the vehicular communication channel, multi-antenna techniques can provide enhanced link conditions by means of diversity processing. This paper highlights the integration of a four-element (N =4) linear array antenna into the roof-top compartment of a vehicle to conduct Multiple-Input Multiple-Output (MIMO) high-resolution mobile-to-mobile channel measurements.

In this letter, we propose the cooperative relaying system using non-orthogonal multiple access (NOMA) to improve the spectral efficiency. The achievable average rate of the proposed system is analyzed for independent Rayleigh fading channels, and also its asymptotic expression is provided. In addition, a suboptimal power allocation scheme for NOMA used at the source is proposed.


Question: A future outlook on waveform, numerology, and frame design principles for flexible radio access beyond 5G.

In this paper, we explore the transformative shift in wireless communications, moving beyond the boundaries of LTE/LTE-A (5G), based on the insights gained from the European research initiative, 5GNOW. Our focus is on identifying the catalysts that necessitate the transition to 5G networks. For instance, the proliferation of the Internet of Things (IoT) and its seamless integration with traditional human-driven communications demand a radical rethinking of the system architecture. We highlight that the rigid adherence to synchronism and orthogonality, as implemented in LTE, imposes limitations on efficiency and scalability. Challenging this established framework, we introduce novel physical (PHY) layer technology innovations. These include a unified frame structure, advanced multicarrier waveform design with integrated filtering capabilities, sparse signal processing techniques, a robust operational framework, and mechanisms for ultra-low latency communications. These components collectively pave the way for an efficient and scalable air interface, adeptly addressing the diverse and stringent requirements emanating from the 5G drivers. This forward-thinking approach is essential for accommodating the expansive and varied demands of future mobile applications.

This study reports a novel tight-coupled dipole array antenna to operate with up to six octave bandwidth and 60 degrees scanning. The array was designed through full-wave EM simulations by employing the current sheet array radiator concept that was advanced by a novel integrated feed network. Several prototypes of planar and conformal arrays across 0.3–20 GHz have been fabricated and tested with good agreement observed between all predicted and measured terminal and radiation features. The exemplified arrays have been designed for 1.2–6 GHz with relative radiator height 0.12 of maximum operational wavelength.

This paper presents the details and results of double-directional propagation measurements carried out in two indoor office environments: a semi-open, cubicle-type office space and a more traditional work environment with closed offices. The measurements cover seven frequency bands from 2.4 to 61 GHz, permitting the propagation characteristics to be compared over a wide range of candidate radio frequencies for next-generation mobile wireless systems, including ultra high frequency and millimeter-wave bands. A novel processing algorithm is introduced for the expansion of multiband measurement data into sets of discrete multipath components. Based on the resulting multipath parameter estimates, models are presented for frequency-dependent path loss, shadow fading, copolarization ratio, delay spread, and angular spreads, along with their interfrequency correlations. Our results indicate a remarkably strong consistency in multipath structure over the entire frequency range considered.

This paper propounds a new flexible material, which has been designed by employing flexible Poly Vinyl Chloride (PVC) having dielectric constant εr= 2.7 as substrate. The projected antenna design states that a circular shaped copper patch with flag shaped slot on it has been deployed over the hexagonal PVC substrate of thickness 1 mm. Then ground plane is partially minimized and slotted to revamp the antenna performance. The proposed antenna operates within frequency range of 7.2032GHz to 7.9035GHz while resonating at 7.55GHz. The proposed antenna design has minimal return loss of −55.226dB with the impedance bandwidth of 700 MHz, gain of 4.379dB and directivity of 4.111dBi. The antenna has VSWR less than maximum acceptable value of 2. The projected antenna design can be suitably employed for UWB, radio-determination applications (7.235GHz to 7.25GHz), naval, defence systems (7.25GHz – 7.3GHz) and weather satellite applications (7.75GHz to 7.90GHz). The antenna has been designed in CST Microwave Studio 2014. The proposed antenna has been fabricated and tested using E5071C Network Analyser and anechoic chamber. It has been observed that the stimulated results closely match with the experimental results.

The exponentially increasing number of internet of things (IoT) devices and the data generated by these devices introduces the spectrum crisis at the already crowded ISM 2.4 GHz band. To address this issue and enable more flexible and concurrent communications among IoT devices, we propose B2W2, a novel communication framework that enables N-way concurrent communication among WiFi and Bluetooth Low Energy (BLE) devices. Specifically, we demonstrate that it is possible to enable the BLE to WiFi cross-technology communication while supporting the concurrent BLE to BLE and WiFi to WiFi communications. We conducted extensive experiments under different real-world settings and results show that its throughput is more than 85X times higher than the most recently reported cross-technology communication system [22], which only supports one-way communication (i.e., broadcasting) at any specific time.

The starring role of the Heterogeneous Networks (HetNet) strategy as the key Radio Access Network (RAN) architecture for future 5G networks poses serious challenges to the current user association (cell selection) mechanisms used in cellular networks. The max-SINR algorithm, although historically effective for performing this function, is inefficient at best and obsolete at worst in 5G HetNets. The foreseen embarrassment of riches and diversified propagation characteristics of network attachment points spanning multiple Radio Access Technologies (RAT) requires novel and creative context-aware system designs that optimize the association and routing decisions in the context of single-RAT and multi-RAT connections, respectively. This paper proposes a framework under these guidelines that relies on Machine Learning techniques at the terminal device level for Cognitive RAT Selection and presents simulation results to suppport it.

With the development of mobile Internet and Internet of things (IoT), the 5th generation (5G) wireless communications will foresee explosive increase in mobile traffic. To address challenges in 5G such as higher spectral efficiency, massive connectivity, and lower latency, some non-orthogonal multiple access (NOMA) schemes have been recently actively investigated, including power-domain NOMA, multiple access with low-density spreading (LDS), sparse code multiple access (SCMA), multiuser shared access (MUSA), pattern division multiple access (PDMA), etc. Different from conventional orthogonal multiple access (OMA) schemes, NOMA can realize overloading by introducing some controllable interferences at the cost of slightly increased receiver complexity, which can achieve significant gains in spectral efficiency and accommodate much more users. In this paper, we will discuss basic principles and key features of three typical NOMA schemes, i.e., SCMA, MUSA, and PDMA. What's more, their performance in terms of uplink bit error rate (BER) will be compared. Simulation results show that in typical Rayleigh fading channels, SCMA has the best performance, while the BER performance of MUSA and PDMA are very close to each other. In addition, we also analyze the performance of PDMA using the same factor graph as SCMA, which indicates that the performance gain of SCMA over PDMA comes from both the difference of factor graph and the codebook optimization.

For the first time, to the best of our knowledge, this paper reports a complete millimeter wave (mmWave) wireless system, which coherently utilizes polarization diversity, multi-input multioutput (MIMO), and beamforming technologies applicable for upcoming fifth generation wireless mobile terminals. Using an interdisciplinary approach across the entire layers constituting of antennas, RF architecture, and digital modem, the polarization of the presented mmWave beamforming antenna system dynamically adapts to the channel environments and MIMO transmission modes. Empirical investigations, which are taken under real-life environments, ascertain that implementing switchable dual-polarized array antennas can alleviate the complexity of the beam searching procedure and MIMO channelization. In addition, experimental results acquired from intensive system level tests indicate more than 22 dB averaged cross-polarization discrimination under polarized MIMO channel conditions at the 60 GHz band. The beam selection algorithm that can be easily implemented based on power metric is confirmed to feature a 99.5% accuracy in comparison with the optimal selection algorithm derived from the theoretical maximal capacity.

This paper investigates a planar monopole antenna for fifth generation (5G) wireless communication networks. The proposed antenna has an ultra-wide band impedance response in millimeter wave (mmW) spectrum, 25–39 GHz covering Ka band. The antenna has unique structural layout resembling hexagonal honeycomb and has low profile (8×7 mm2) on 0.254 mm thick Rogers substrate, enabling the design for incorporation into future mobile phones. This antenna provides peak gain of 4.15 dBi along with 90% efficiency in the working band. The design is also extended to an 8×1 element array presenting maximum gain of 12.7 dBi at central frequency of the antenna.

Sparse code multiple access (SCMA) is being considered as a promising multiple access solution for 5G systems. A distinguishing feature of SCMA is that it combines the procedures of bit to constellation symbol mapping and subsequent spreading using multidimensional codebooks differentiated by users. Such codebooks dominate the system implementation as a main source of not only performance gain but also design complexity. This letter presents a joint constellation with mapping matrix design for SCMA codebooks, which formulates the constellations optimization as a nonconvex quadratically constrained quadratic programming problem based on a set of well-constructed mapping matrices. We elaborately solve the problem to achieve outperformance over existing SCMA design in terms of bit error rate (BER). For improving practicality, an approximate approach is further proposed to reduce the complexity significantly with a limited BER loss.

This paper presents a cell search procedure in 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) downlink systems. The proposed cell search procedure contains three steps. In the beginning, conventional mode detection, symbol timing detection and fractional carrier frequency offset (CFO) estimation methods are adopted so that frequency-domain signal processing can be performed subsequently. Secondly, a new joint detection method for integer carrier frequency offset and sector cell index information is proposed, which is shown to be capable of resisting symbol timing error. Finally, we also proposed a detection method for frame timing and cell identity (ID) group information without explicit channel estimates. Simulation results demonstrate that the proposed scheme with lower detection error probability is effective and robust compared with some conventional approaches.


Question: A forward-looking perspective on flexible radio access beyond 5G: waveform, numerology, and frame design principles.

This paper introduces a novel multiple access scheme known as Sparse Code Multiple Access (SCMA), designed to enhance the efficiency and performance of communication systems beyond conventional approaches. SCMA builds upon the principles of Multicarrier Code Division Multiple Access (MC-CDMA), a technique that distributes QAM symbols across multiple Orthogonal Frequency-Division Multiple Access (OFDMA) tones using a complex spreading sequence. While MC-CDMA effectively repeats QAM symbols across multiple tones, Low Density Signature (LDS) CDMA offers a more refined approach, utilizing a sparse spreading sequence to enable near-optimal Maximum Likelihood (ML) reception with manageable computational complexity.

SCMA, however, pushes the boundaries further by combining the processes of bit-to-QAM symbol mapping and spreading, allowing incoming bits to be directly mapped to a multidimensional codeword from a dedicated SCMA codebook set. Each user or communication layer is assigned a unique codebook, facilitating a more sophisticated form of data transmission. The performance enhancement in SCMA is primarily attributed to the shaping gain of multidimensional constellations, a significant improvement over the simple repetition of QAM symbols in LDS.

The design of SCMA codebooks is formulated as an optimization problem, and while finding the optimal solution may be challenging, a systematic sub-optimal approach is proposed in this paper. This approach aims to strike a balance between performance gains and computational feasibility, making SCMA a promising technique for future communication systems, particularly in the context of flexible radio access beyond 5G. By addressing waveform, numerology, and frame design principles, SCMA is poised to play a pivotal role in shaping the next generation of wireless communication technologies.

DVB-NGH (Digital Video Broadcasting - Next Generation Handheld) is the next generation technology for mobile TV broadcasting, which has been developed by the DVB project with the most advanced transmission technologies. DVB-NGH is the first broadcasting standard to incorporate multiple-input multiple-output (MIMO) as the key technology to overcome the Shannon limit of single antenna communications. MIMO techniques can be used to improve the robustness of the transmitted signal by exploiting the spatial diversity of the MIMO channel, but also to achieve increased data rates through spatial multiplexing. This article describes the benefits of MIMO that motivated its incorporation in DVB-NGH, reviews the MIMO schemes adopted, and discusses some aspects related to the deployment of MIMO networks in DVB-NGH. The article also provides a feature comparison with the multi-antenna techniques for 3GGP's LTE/LTE-Advanced for cellular networks. Finally, physical layer simulation results calibrated within the DVB-NGH standardization process are provided to illustrate the gain of MIMO for the next generation of mobile TV broadcasting.

Recent advancements in wireless communication are creating a spectrum shortage problem on a daily basis. Recently, Cognitive Radio (CR), a novel technology, has attempted to minimize this problem by dynamically using the free spectrum in wireless communications and mobile computing. Cognitive radio networks (CRNs) can be formed using cognitive radios by extending the radio link features to network layer functions. The objective of CRN architecture is to improve the whole network operation to fulfil the user’s demands anytime and anywhere, through accessing CRNs in a more efficient way, rather than by just linking spectral efficiency. CRNs are more flexible and exposed to wireless networks compared with other traditional radio networks. Hence, there are many security threats to CRNs, more so than other traditional radio environments. The unique characteristics of CRNs make security more challenging. Several crucial issues have not yet been investigated in the area of security for CRNs. A typical public key infrastructure (PKI) scheme which achieves secure routing and other purposes in typical ad hoc networks is not enough to guarantee the security of CRNs under limited communication and computation resources. However, there has been increasing research attention on security threats caused specifically by CR techniques and special characteristics of CR in CRNs. Therefore, in this research, a survey of CRNs and their architectures and security issues has been carried out in a broad

In this paper LDS-OFDM is introduced as an uplink multicarrier multiple access scheme. LDS-OFDM uses Low Density Signature (LDS) structure for spreading the symbols in frequency domain. This technique benefits from frequency diversity besides its ability of supporting parallel data streams up to 400% more than the number of subcarriers (overloaded condition). The performance of LDS-OFDM is evaluated and compared with conventional OFDMA systems over multipath fading channel. Monte Carlo based simulations for various loading conditions indicate significant performance improvement over OFDMA system.

With the ratification of the IEEE 802.11ad amendment to the 802.11 standard in December 2012, a major step has been taken to bring consumer wireless communication to the millimeter wave (mm-Wave) band. However, multi-Gbps throughput and small interference footprint come at the price of adverse signal propagation characteristics and require a fundamental rethinking of Wi-Fi communication principles. This paper describes the design assumptions taken into consideration for the IEEE 802.11ad standard and the novel techniques defined to overcome the challenges of mm-Wave communication. In particular we study the transition from omni-directional to highly directional communication and its impact on the design of

In this paper, we propose an efficient beam tracking method for mobility scenario in mmWave-band communications. When the position of the mobile changes in mobility scenario , the base-station needs to perform beam training frequently to t rack the time-varying channel, thereby spending significant res ources for training beams. In order to reduce the training overhead, we propose a new beam training approach called “beam tracking” which exploits the continuous nature of time varying angle of departure (AoD) for beam selection. We show that transmissi on of only two training beams is enough to track the time-varying AoD at good accuracy. We derive the optimal selection of beam pai r which minimizes Cramer-Rao Lower Bound (CRLB) for AoD estimation averaged over statistical distribution of the AoD. Our numerical results demonstrate that the proposed beam track ing scheme produces better AoD estimation than the conventiona l beam training protocol with less training overhead. I. I NTRODUCTION The next generation wireless communication systems aim to achieve Giga bit/s throughput to support high speed multimedia data service [1], [2]. Since there exist ample amount of unutilized frequency spectrum in millimeter Wave (mmWave) band (30 GHz-300 GHz), wireless communication over mmWave band is considered as a promising solution to achieve significant leap in spectral efficiency [3]. However , one major limitation of mmWave communications is significant free space path loss, which causes large attenuation of sign al power at the receiver. Furthermore, the overall path loss ge t worse when the signal goes through obstacles, rain, foliage , and any blockage to mobile devices. Recently, active resear ch on mmWave communication has been conducted in order to overcome these limitations [1]–[5]. In mmWave band, many antenna elements can be integrated in a small form factor and hence, we can employ high directional beamforming using a large number of antennas to compensate high path loss. In order to perform high directional beamforming, it is necessary to estimate channels for all transmitter and rece iver antenna pair. While this step requires high computational c omplexity due to large number of antennas, channel estimation can be performed efficiently by using the angular domain representation of channels [6]. In angular domain, only a fe w angular bins contain the most of the received energy. Hence, if we identify the dominant angular bins (which correspond to the angle of arrival (AoA) and the angle of departure (AoD)), we can obtain the channel estimate without incurrin g computational complexity. Basically, both AoD and AoA can be estimated using so called “beam training” procedure. The base-station sends t he training beams at the designated direction and the receiver estimates the AoD/AoA based on the received signals. Widely used beam training method (called “beam cycling method”) is to allow the base-station to transmit N training beams one by one at the equally spaced directions. However, to ensure good estimate of AoD/AoA, N should be large, leading to significant training overhead. This problem becomes even more serious for the mobility scenario in mmWave communications. Since the location of mobiles keeps changing, th e base-station should transmit training beams more frequent ly to update AoD/AoA estimates, causing significant drop in data throughput [7]. Recently, several adaptive beam train ing schemes have been proposed to improve the conventional beam training method [10]–[14]. In this paper, we introduce a novel beam training method for mobility scenario in mmWave communications. Our idea is based on the observation that for mobility scenario, the AoD of the particular user does not change drastically so that continuous nature of the AoD change can be accounted to improve the efficacy of the beam training. Since this approach exploits temporal dynamics of AoD, we call such beam training scheme “beam tracking”. While the convenional method makes no assumption on the state of AoD, we use statistical distribution of the AoD given the previousl y state of AoD. Using the probabilistic model on AoD change, we derive effective beam tracking strategy which employs transmission of two training beams from the base-station. Optimal placement of two training beams in angular domain is sought by minimizing (the lower bound of) variance of the estimation error for AoD. As a result, we choose the best beam p ir from the beam codebook for the given prior knowledge on AoD. Our simulation results show that the proposed beam tracking method offers the channel estimation performance comparable to the conventional beam training methods with significantly reduced training overhead. The rest of this paper is organized as follows; In section II, we introduce the system and channel models for mmWave communications and in section III, we describe the proposed b am tracking method and the simulation results are provide d in section IV. Finally, the paper is concluded in section V. II. SYSTEM MODEL In this section, we describe the system model for mmWave communications. First, we describe the angular domain repr esentation of the mmWave channel and then we introduce the procedure for beam training and channel estimation. A. Channel Model Consider single user mmWave MIMO systems with the base-station withNb antennas and the mobile with Nm antennas. The MIMO channel model with L paths at timet is described by [8]

The demonstration of multi-Gb/s links in the 60GHz band has created new opportunities for wireless communications [1,2]. Due to the directional nature of millimeter-wave (mm-Wave) propagation, beam steering enables longer-range non-line-of-sight (NLOS) links at these frequencies. A phased-array architecture is attractive for an integrated 60GHz transmitter (Tx) since it can attain both beam steering and higher EIRP through spatial combining. An all-RF 16-element 40-to-45GHz Tx for satellite applications [3], a 6-element 60GHz Tx with IF-path phase-shift [4], and a bi-directional 4-element 60GHz Tx/Rx with RF phase shifters [5] have been recently demonstrated in silicon. This work presents a fully-integrated phased-array Tx which supports multi-Gb/s NLOS IEEE 802.15.3c links. In addition to beamsteering, the IC has the following major features: an on-chip power sensor at each element, 3 temperature sensors, LO leakage and I/Q phase and amplitude adjustment, front-end OP1dB programmability, and an integrated modulator for pi/2-BPSK/MSK signaling (common mode in 802.15.3c). The IC integrates 2240 NPNs, 323,000 FETs and hundreds of transmission lines and is fabricated in the IBM 8HP 0.12µm SiGe BiCMOS process (fT = 200GHz).

This paper presents an overview of radio interface technologies for cooperative transmission in 3GPP LTE-Advanced, i.e., coordinated multi-point (CoMP) transmission, enhanced inter-cell interference coordination (eICIC) for heterogeneous deployments, and relay transmission techniques. This paper covers not only the technical components in the 3GPP specifications that have already been released, but also those that were discussed in the Study Item phase of LTE-Advanced, and those that are currently being discussed in 3GPP for potential specification in future LTE releases. key words: LTE-Advanced, CoMP, eICIC, relay

The rapid growth of traffic and number of simultaneously available devices leads to the new challenges in constructing fifth generation wireless networks (5G). To handle with them various schemes of non-orthogonal multiple access (NOMA) were proposed. One of these schemes is Sparse Code Multiple Access (SCMA), which is shown to achieve better link level performance. In order to support SCMA signal decoding channel estimation is needed and sparse Bayesian learning framework may be used to reduce the requirement of pilot overhead. In this paper we propose a modification of sparse Bayesian learning based channel estimation algorithm that is shown to achieve better accuracy of user detection and faster convergence in numerical simulations.

The extensive growth of wireless communications industry is creating a big market opportunity. Wireless operators are currently searching for new solutions which would be implemented into the existing wireless communication networks to provide the broader bandwidth, the better quality and new value-added services. In the last decade, most commercial efforts were focused on the 1-10 GHz spectrum for voice and data applications for mobile phones and portable computers (Niknejad & Hashemi, 2008). Nowadays, the interest is growing in applications that use high rate wireless communications. Multigigabit-per-second communication requires a very large bandwidth. The Ultra-Wide Band (UWB) technology was basically used for this issue. However, this technology has some shortcomings including problems with interference and a limited data rate. Furthermore, the 3–5 GHz spectrum is relatively crowded with many interferers appearing in the WiFi bands (Niknejad & Hashemi, 2008). The use of millimeter wave frequency band is considered the most promising technology for broadband wireless. In 2001, the Federal Communications Commission (FCC) released a set of rules governing the use of spectrum between 57 and 66 GHz (Baldwin, 2007). Hence, a large bandwidth coupled with high allowable transmit power equals high possible data rates. Traditionally the implementation of 60 GHz radio technology required expensive technologies based on III-V compound semiconductors such as InP and GaAs (Smulders et al., 2007). The rapid progress of CMOS technology has enabled its application in millimeter wave applications. Currently, the transistors became small enough, consequently fast enough. As a result, the CMOS technology has become one of the most attractive choices in implementing 60 GHz radio due to its low cost and high level of integration (Doan et al., 2005). Despite the advantages of CMOS technology, the design of 60 GHz CMOS transceiver exhibits several challenges and difficulties that the designers must overcome. This chapter aims to explore the potential of the 60 GHz band in the use for emergent generation multi-gigabit wireless applications. The chapter presents a quick overview of the state-of-the-art of 60 GHz radio technology and its potentials to provide for high data rate and short range wireless communications. The chapter is organized as follows. Section 2 presents an overview about 60 GHz band. The advantages are presented to highlight the performance characteristics of this band. The opportunities of the physical layer of the IEEE

Two-dimensional non-uniform constellations (2D-NUC) have been adopted for the most recent terrestrial broadcasting system called ATSC 3.0. They are known for being more efficient than one-dimensional non uniform constellations (1D-NUC) and uniform constellations (UC). They can be used in any communication system with the bit-interleaved coded modulation (BICM) structure. However, one of the main challenges of such constellations is their design for optimal behaviour in a wide range of cases and the design of a demapper that exploits their advantages. This paper presents two different condensation methodologies to design efficient 2D-NUCs simple in design and with limited demapping complexity. The proposal provides a complexity reduction of the design and demapping processes in the range from 13% to 94%. The demapping stage provides performance losses less than 0.1 dB if compared with standard 2D-NUC demapping.


Question: A forward-looking perspective on waveform, numerology, and frame design principles for flexible radio access beyond 5G.

This document explores a systematic methodology for the design of Sparse Code Multiple Access (SCMA) codebooks, focusing on the principles underlying lattice constellation design. SCMA, a non-orthogonal spreading technique, combines the processes of bit-to-QAM symbol mapping and spreading into a single step, where incoming bits are directly transformed into multi-dimensional codewords selected from predefined codebook sets. Each codebook is associated with a specific layer, facilitating the shaping gain of multi-dimensional constellations. This gain significantly contributes to the enhanced performance of SCMA over the straightforward repetition of QAM symbols observed in Low Density Signature (LDS) systems. Similar to LDS, SCMA benefits from low-complexity reception techniques, thanks to the inherent sparsity of its codewords. The proposed design approach for SCMA codebooks is grounded in the design principles of lattice constellations, ensuring optimized performance. The paper includes simulation outcomes that vividly illustrate the superior performance of SCMA relative to LDS and Orthogonal Frequency Division Multiple Access (OFDMA) systems.

**Question**: An Overview of Neural Network Architectures for Time Series Forecasting

**Documents**: A Comparative Study of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) Networks for Time Series Prediction
In this paper, a comparative analysis of two popular recurrent neural network architectures, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), is conducted for time series prediction. LSTM and GRU are recurrent neural networks that have been specifically designed to overcome the vanishing gradient problem and to learn long-term dependencies in sequential data. They do this by using memory cells and gates (input, output, forget) in the case of LSTM, and an update gate and a reset gate in the case of GRU. Despite their architectural differences, both LSTM and GRU have shown promising results in various time series prediction tasks. In this study, we compare the performance of LSTM and GRU on a variety of time series datasets, including financial, environmental, and physiological data. The results indicate that both models can effectively capture the temporal dynamics of the time series, but the choice between LSTM and GRU may depend on the specific characteristics of the dataset and the computational resources available. In general, LSTM tends to perform slightly better when the time series has long-term dependencies, while GRU is computationally more efficient and may be a better choice for real-time applications.

**Similar Documents**: This paper presents a detailed comparative evaluation of Long Short-Term Memory

Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the large bandwidth available at mmWave frequencies. To realize sufficient link margin, mmWave systems will employ directional beamforming with large antenna arrays at both the transmitter and receiver. Due to the high cost and power consumption of gigasample mixed-signal devices, mmWave precoding will likely be divided among the analog and digital domains. The large number of antennas and the presence of analog beamforming requires the development of mmWave-specific channel estimation and precoding algorithms. This paper develops an adaptive algorithm to estimate the mmWave channel parameters that exploits the poor scattering nature of the channel. To enable the efficient operation of this algorithm, a novel hierarchical multi-resolution codebook is designed to construct training beamforming vectors with different beamwidths. For single-path channels, an upper bound on the estimation error probability using the proposed algorithm is derived, and some insights into the efficient allocation of the training power among the adaptive stages of the algorithm are obtained. The adaptive channel estimation algorithm is then extended to the multi-path case relying on the sparse nature of the channel. Using the estimated channel, this paper proposes a new hybrid analog/digital precoding algorithm that overcomes the hardware constraints on the analog-only beamforming, and approaches the performance of digital solutions. Simulation results show that the proposed low-complexity channel estimation algorithm achieves comparable precoding gains compared to exhaustive channel training algorithms. The results illustrate that the proposed channel estimation and precoding algorithms can approach the coverage probability achieved by perfect channel knowledge even in the presence of interference.

In this work the realization of a 77-GHz frequency-division multiple-access-based frequency-modulated continuous-wave multiple-input multiple-output radar with four transceiver channels in conjunction with a non-uniform linear antenna array is presented. The radar system, consisting of an RF-frontend utilizes transceiver chips with integrated inphase/quadrature-modulators to generate the frequency shifted transmit signals and a field programmable gate array-based baseband board, is used for test measurements to verify the system performance and to demonstrate the beamforming capability as well as the accuracy of the digital-beamforming method.

Millimeter-wave technology brings a new paradigm of wireless communication in various areas including mobile devices, automotive, IoT (Internet of Things), medical, military and many others. In this paper, we present our recently developed antenna in a package and system for 5G (Fifth-Generation) millimeter-wave applications. The antenna is configured to be an array to compensate path loss and maintain data link budget. The antenna is designed with a multi-layer laminate substrate and is integrated with a 5G mmW RFIC. 5G NR (New Radio) wireless connection is demonstrated with a RFIC transceiver at 28 GHz band. Interoperability test is conducted to ensure compatibility with the 3GPP standard. Finally, indoor and outdoor field test including beamforming and beamtracking are presented to show realistic system-level throughput performance.

Terahertz frequency band, 0.1–10THz, is envisioned as one of the possible resources to be utilized for wireless communications in networks beyond 5G. Communications over this band will be feature a number of attractive properties, including potentially terabit-per-second link capacities, miniature transceivers and, potentially, high energy efficiency. Meanwhile, a number of specific research challenges have to be addressed to convert the theoretical estimations into commercially attractive solutions. Due to the diversity of the challenges, the research on THz communications at its early stages was mostly performed by independent communities from different areas. Therefore, the existing knowledge in the field is substantially fragmented. In this paper, an attempt to address this issue and provide a clear and easy to follow introduction to the THz communications is performed. A review on the state-of-the-art in THz communications research is given by identifying the target applications and major open research challenges as well as the recent achievements by industry, academia, and the standardization bodies. The potential of the THz communications is presented by illustrating the basic tradeoffs in typical use cases. Based on the given summary, certain prospective research directions in the field are identified.

This paper provides an overview of the optional multiple-input multiple-output (MIMO) antenna scheme adopted in ATSC 3.0 to improve robustness or increase capacity via additional spatial diversity and multiplexing by sending two data streams in a single radio frequency channel. Although it is not directly specified, it is expected in practice to use cross-polarized 2×2 MIMO (i.e., horizontal and vertical polarization) to retain multiplexing capabilities in line-of-sight conditions. MIMO allows overcoming the channel capacity limit of single antenna wireless communications in a given channel bandwidth without any increase in the total transmission power. But in the U.S. MIMO can actually provide a larger comparative gain because it would be allowed to increase the total transmit power, by transmitting the nominal transmit power in each polarization. Hence, in addition to the MIMO gains (array, diversity, and spatial multiplexing), MIMO could exploit an additional 3 dB power gain. The MIMO scheme adopted in ATSC 3.0 re-uses the single-input single-output antenna baseline constellations, and hence it introduces the use of MIMO with non-uniform constellations.

Massive multiple input and multiple output (MIMO) has attracted significant interests in both academia and industry. It has been considered as one of most promising technologies for 5G wireless systems. The large-scale antenna array for base stations naturally becomes the key to deploy the Massive MIMO technologies. In this communication, we present a dual-polarized antenna array with 144 ports for Massive MIMO operating at 3.7 GHz. The proposed array consists of 18 low profile subarrays. Each subarray consists of four single units. Each single antenna unit consists of one vertically polarized port and one horizontally polarized port connected to power splitters, which serve as a feeding network. A stacked patch design is used to construct the single unit with the feeding network, which gives higher gain and lower mutual coupling within the size of a conversional dual-port patch antenna. Simulation results of the proposed single antenna unit, sub-array, and Massive MIMO array are verified by measurement.

Single carrier frequency division multiple access (SC FDMA), a modified form of orthogonal FDMA (OFDMA), is a promising technique for high data rate uplink communications in future cellular systems. SC-FDMA has similar throughput performance and essentially the same overall complexity as OFDMA. A principal advantage of SC-FDMA is the peak-to-average power ratio (PARR), which is lower than that of OFDMA. SC FDMA is currently a strong candidate for the uplink multiple access scheme in the long term evolution of cellular systems under consideration by the third generation partnership project (3GPP). In this paper, we give an overview of SC-FDMA. We also analyze the effects of subcarrier mapping on throughput and PARR. Among the possible subcarrier mapping approaches, we find that localized FDMA (LFDMA) with channel-dependent scheduling (CDS) results in higher throughput than interleaved FDMA (JFDMA). However, the PARR performance of IFDMA is better than that of LFDMA. As in other communications systems there are complex tradeoffs between design parameters and performance in an SC-FDMA system

Vehicular applications and communications technologies are often referred to as vehicle-to-everything (V2X), which is classified into four different types: vehicle-to-vehicle (V2V), vehicle- to-infrastructure (V2I), vehicle-to-network (V2N), and vehicle-to-pedestrian (V2P) [1]. V2X related research projects, field tests, and regulatory work have been promoted in different countries and regions. In May 2015, the Ministry of Industry and Information Technology (MIIT) of China explained national strategies, "Made in China 2025," about intelligent connected vehicles. In 2020 and 2025, the overall technology and key technologies for intelligent driver assistance and automatic driving will be available in China, respectively [2]. V2X solutions are the critical technologies to support the realization of such visions. Although IEEE 802.11p has been selected as the technology for V2X communications in some countries such as the United States and in Europe, the intrinsic characteristics of IEEE 802.11p have confined the technology to support low latency with high reliability [3, 4]. Standardization of Long Term Evolution (LTE)-based V2X is being actively conducted by the Third Generation Partnership Project (3GPP) to provide the solution for V2X communications that benefit from the global deployment and fast commercialization of LTE systems. Because of the wide deployment of LTE networks, V2I and V2N services can be provided with high data rate, comprehensive quality of service (QoS) support, ubiquitous coverage, and high penetration rate [5]. Meanwhile, LTE can be extended to support V2V direct communications based on device-to-device (D2D) sidelink design to satisfy the QoS requirements, such as low latency, high reliability, and high speed in the case of high vehicle density [6].

The 3GPP has introduced a new narrowband radio technology called narrowband Internet of Things (NB-IoT) in Release 13. NB-IoT was designed to support very low power consumption and low-cost devices in extreme coverage conditions. NB-IoT operates in very small bandwidth and will provide connectivity to a large number of low-data-rate devices. This article highlights some of the key features introduced in NB-IoT and presents performance results from real-life experiments. The experiments were carried out using an early-standard-compliant prototype based on a software defined radio partial implementation of NB-IoT that runs on a desktop computer connected to the network. It is found that a cloud radio access network is a good candidate for NB-IoT implementation.

This paper describes the implementation of a pseudo-random noise radar system on a scalable sensor platform that consists of several multi-purpose 61- and 122-GHz transceivers in a Silicon-Germanium BiCMOS technology. The multi-band transceivers are equipped with a frequency multiplier to generate the 61- and 122-GHz carrier signals from a single 30.5-GHz LO signal and can be cascaded to build a MIMO radar system with 2 different frequency bands. The implemented scalable sensor system is suitable for various radar and communication applications by using the same transceiver chips with integrated binary phase-shift keying modulators and I/Q receiver. A suitable pseudo-random binary sequence was used in a radar measurement to demonstrate the applicability of the developed chips.


Question: A forward-looking perspective on flexible radio access post-5G: Waveform, numerology, and frame design principles.

Introducing LDS-OFDM: An Enhanced Multiple Access Scheme for Future Wireless Networks

In this research, we present LDS-OFDM, a novel uplink multicarrier multiple access technique designed for future wireless networks. LDS-OFDM leverages a Low Density Signature (LDS) structure to spread symbols across the frequency domain, thereby enhancing its capability to support parallel data streams. Remarkably, this technique can handle up to 400% more data streams than the number of subcarriers, even under overloaded conditions. To assess its performance, we compare LDS-OFDM with conventional OFDMA systems in a multipath fading channel environment. Through extensive Monte Carlo simulations conducted under various loading scenarios, we demonstrate that LDS-OFDM significantly outperforms OFDMA, showcasing its potential for future flexible radio access beyond 5G.

As a promising downlink multiple access scheme for further LTE enhancement and future radio access (FRA), this paper investigates the system-level performance of non-orthogonal multiple access (NOMA) with a successive interference canceller (SIC) on the receiver side. The goal is to clarify the potential gains of NOMA over orthogonal multiple access (OMA) such as OFDMA, taking into account key link adaptation functionalities of the LTE radio interface such as adaptive modulation and coding (AMC), hybrid automatic repeat request (HARQ), time/frequency-domain scheduling, and outer loop link adaptation (OLLA), in addition to NOMA specific functionalities such as dynamic multi-user power allocation. Based on computer simulations, we show under multiple configurations that the system-level performance achieved by NOMA is superior to that for OMA.

Two-dimensional non-uniform constellations (2D-NUC) have been adopted for the most recent terrestrial broadcasting system called ATSC 3.0. They are known for being more efficient than one-dimensional non uniform constellations (1D-NUC) and uniform constellations (UC). They can be used in any communication system with the bit-interleaved coded modulation (BICM) structure. However, one of the main challenges of such constellations is their design for optimal behaviour in a wide range of cases and the design of a demapper that exploits their advantages. This paper presents two different condensation methodologies to design efficient 2D-NUCs simple in design and with limited demapping complexity. The proposal provides a complexity reduction of the design and demapping processes in the range from 13% to 94%. The demapping stage provides performance losses less than 0.1 dB if compared with standard 2D-NUC demapping.

Long-term evolution (LTE) represents an emerging and promising technology for providing broadband ubiquitous Internet access. For this reason, several research groups are trying to optimize its performance. Unfortunately, at present, to the best of our knowledge, no open-source simulation platforms, which the scientific community can use to evaluate the performance of the entire LTE system, are freely available. The lack of a common reference simulator does not help the work of researchers and poses limitations on the comparison of results claimed by different research groups. To bridge this gap, herein, the open-source framework LTE-Sim is presented to provide a complete performance verification of LTE networks. LTE-Sim has been conceived to simulate uplink and downlink scheduling strategies in multicell/multiuser environments, taking into account user mobility, radio resource optimization, frequency reuse techniques, the adaptive modulation and coding module, and other aspects that are very relevant to the industrial and scientific communities. The effectiveness of the proposed simulator has been tested and verified considering 1) the software scalability test, which analyzes both memory and simulation time requirements; and 2) the performance evaluation of a realistic LTE network providing a comparison among well-known scheduling strategies.

Beamforming(BF) based on codebook is regarded as an attractive solution to resolve the poor link budget of millimeter-wave 60GHz wireless communication. Because the number of the elements of antenna array in 60GHz increases, the beam patterns generated are more than common BF, and it causes long set-up time during beam patterns searching. In order to reduce the set-up time, three stages protocol, namely the device (DEV) to DEV linking, sector-level searching and beam-level searching has been adopted by the IEEE 802.15.3c as an optional functionality to realize Gbps communication systems. However, it is still a challenge to create codebook of different patterns to support three stages protocol from common codebook of beam pattern. In this paper, we proposes a multi-stage codebook design and the realization architecture to support three stages BF. The multi-stage codebook can create different granularity of beam patterns and realize progressive searching. Simulation results for eight elements uniform linear array (ULA) show that this design can divide the beam searching to three stages searching without increasing the system complexity.

The tremendous growth in communication technology is shaping a hyper-connected network where billions or connected devices are producing a huge volume of data. Cellular and mobile network is a major contributor towards this technology shift and require new architectural paradigm to provide low latency, high performance in a resource constrained environment. 5G technology deployment with fully IP-based connectivity is anticipated by 2020. However, there is no standard established for 5G technology and many efforts are being made to establish a unified 5G stander. In this context, variant technology such as Software Defined Network (SDN) and Network Function virtualization (NFV) are the best candidate. SDN dissociate control plane from data plane and network management is done on the centralized control plane. In this paper, a survey on state of the art on the 5G integration with the SDN is presented. A comprehensive review is presented for the different integrated architectures of 5G wireless network and the generalized solutions over the period 2010–2016. This comparative analysis of the existing solutions of SDN-based cellular network (5G) implementations provides an easy and concise view of the emerging trends by 2020.

Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications and all cellular systems. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.

Non-orthogonal multiple access (NOMA) has been recently considered as a promising multiple access technique for fifth generation (5G) mobile networks as an enabling technology to meet the demands of low latency, high reliability, massive connectivity, and high throughput. The two dominants types of NOMA are: power-domain and code-domain. The key feature of power-domain NOMA is to allow different users to share the same time, frequency, and code, but with different power levels. In code-domain NOMA, different spread-spectrum codes are assigned to different users and are then multiplexed over the same time-frequency resources. This paper concentrates on power-domain NOMA. In power-domain NOMA, Successive Interference Cancellation (SIC) is employed at the receiver. In this paper, the optimum received uplink power levels using a SIC detector is determined analytically for any number of transmitters. The optimum uplink received power levels using the SIC decoder in NOMA strongly resembles the μ-law encoding used in pulse code modulation (PCM) speech companders.

Next-generation mobile technology (5G) aims to provide an improved experience through higher data-rates, lower latency, and improved link robustness. Millimeter-wave phased arrays offer a path to support multiple users at high data-rates using high-bandwidth directional links between the base station and mobile devices. To realize this vision, a phased-array-based pico-cell must support a large number of precisely controlled beams, yet be compact and power efficient. These system goals have significant mm-wave radio interface implications, including scalability of the RFIC+antenna-array solution, increase in the number of concurrent beams by supporting dual polarization, precise beam steering, and high output power without sacrificing TX power efficiency. Packaged Si-based phased arrays [1–3] with nonconcurrent dual-polarized TX and RX operation [2,3], concurrent dual-polarized RX operation [3] and multi-IC scaling [3,4] have been demonstrated. However, support for concurrent dual-polarized operation in both RX and TX remains unaddressed, and high output power comes at the cost of power consumption, cooling complexity and increased size. The RFIC reported here addresses these challenges. It supports concurrent and independent dual-polarized operation in TX and RX modes, and is compatible with a volume-efficient, scaled, antenna-in-package array. A new TX/RX switch at the shared antenna interface enables high output power without sacrificing TX efficiency, and a t-line-based phase shifter achieves <1° RMS error and <5° phase steps for precise beam control.

A 1 V low voltage delta-sigma fractional-N frequency divider for multi-band (780/868/915 MHz and 2.4 GHz) WSN frequency synthesizers is presented. The frequency divider consists of a dual-modulus prescaler, a pulse-swallow counter and a delta-sigma modulator. The high-speed and low-voltage phase-switching dualmodulus prescaler is used in the frequency divider. Low threshold voltage transistors are applied to overcome low voltage supply and forward phase-switching technique is adopted to prevent glitches. The modified deltasigma modulator with long output sequence length and less spurs is adopted to minimize the fractional spurs. The frequency divider is designed in 0.18 μm TSMC RF CMOS technology under 1 V supply instead of the standard 1.8 V supply. The total chip area is 1190 μm × 485 μm including I/O pads. The post simulation results show the frequency divider operates normally over a wide range of 1.3-5.0 GHz and the core circuit (without test buffers) consumes 2.3 mW. Copyright © 2013 IFSA.

Elevation beamforming and Full Dimension MIMO (FD-MIMO) has been an active area of research and standardization in 3GPP LTE-Advanced. In an FD-MIMO system, a base station with 2-dimensional (2D) active array supports multi-user joint elevation and azimuth beamforming (a.k.a. 3D beamfoming), which results in much higher cell capacity compared to conventional systems. Recent study has shown that with these new FD-MIMO technologies, we can achieve promising 3-5× gain in both cell capacity as well as cell-edge throughput. In this paper, we will provide a brief summary of recent 3GPP activities, including the recently completed 3D channel model, ongoing study on FD-MIMO scenarios, antenna/RF (radio frequency) transceiver architectures, as well as potential network performance benefits. In addition, we also discuss some methods for reducing CSI (channel state information) feedback overhead and ensuring efficient operation of large size FD-MIMO for both TDD and FDD systems.


Question: Exploring the Anxious Mind: Anxiety, Worry, and Frontal Engagement in Sustained Attention Compared to Off-Task Processing

This paper elucidates the impact of subject motion on the integrity of resting state functional connectivity MRI (rs-fcMRI) data, even after attempts to mitigate motion effects through spatial registration and regression. We reveal that subject motion can significantly alter the temporal dynamics of rs-fcMRI data, leading to systematic yet misleading correlation patterns across the brain. In particular, long-distance correlations are typically diminished, while short-distance correlations are augmented. These alterations in rs-fcMRI correlations are not merely artifacts but result from inherent limitations in common functional connectivity processing techniques. To address this issue, we propose two metrics to assess data quality and present a straightforward method to mitigate motion-related distortions in rs-fcMRI analyses, which can be readily integrated into various software platforms. We showcase the effectiveness of this technique on our dataset, which leads to a reevaluation of previous conclusions regarding brain development. Our findings underscore the importance of rigorous handling of subject motion and the necessity to reassess prior rs-fcMRI studies that may have inadequately accounted for the influence of transient subject movements.

Little is known about the function of the retrosplenial cortex and until recently, there was no evidence that it had any involvement in emotional processes. Surprisingly, recent functional neuroimaging studies show that the retrosplenial cortex is consistently activated by emotionally salient words. A review of the functional neuroimaging literature reveals a previously overlooked pattern of observations: the retrosplenial cortex is the cortical region most consistently activated by emotionally salient stimuli. Evidence that this region is also involved in episodic memory suggests that it might have a role in the interaction between emotion and episodic memory. Recognition that the retrosplenial cortex has a prominent role in the processing of emotionally salient stimuli invites further studies to define its specific functions and its interactions with other emotion-related brain regions.

The author acknowledge support from National Institute of Health Research Grants MH55687 and AG15685. Marc Howard is now at the Department of Psychology, Boston University, 64 Cunningham Street, Boston, MA 02215. Address correspondence and reprint requests to Michael J. Kahana, Volen Center for Complex Systems, Brandeis University, MS 013, Waltham, MA 02254. E-mail: kahana@brandeis.edu. Marc W. Howard and Michael J. Kahana

Recent studies suggest that months to years of intensive and systematic meditation training can improve attention. However, the lengthy training required has made it difficult to use random assignment of participants to conditions to confirm these findings. This article shows that a group randomly assigned to 5 days of meditation practice with the integrative body-mind training method shows significantly better attention and control of stress than a similarly chosen control group given relaxation training. The training method comes from traditional Chinese medicine and incorporates aspects of other meditation and mindfulness training. Compared with the control group, the experimental group of 40 undergraduate Chinese students given 5 days of 20-min integrative training showed greater improvement in conflict scores on the Attention Network Test, lower anxiety, depression, anger, and fatigue, and higher vigor on the Profile of Mood States scale, a significant decrease in stress-related cortisol, and an increase in immunoreactivity. These results provide a convenient method for studying the influence of meditation training by using experimental and control methods similar to those used to test drugs or other interventions.

We study the incidence (rate of occurrence), persistence (rate of reoccurrence immediately after occurrence), and impact (effect on behavior) of students’ cognitive-affective states during their use of three different computer-based learning environments. Students’ cognitive-affective states are studied using different populations (Philippines, USA), different methods (quantitative field observation, self-report), and different types of learning environments (dialogue tutor, problemsolving game, and problem-solving based Intelligent Tutoring System). By varying the studies along these multiple factors, we can have greater confidence that findings which generalize across studies are robust. The incidence, persistence, and impact of boredom, frustration, confusion, engaged concentration, delight, and surprise were compared. We found that boredom was very persistent across learning environments and was associated with poorer learning and problem behaviors, such as gaming the system. Despite prior hypothesis to the contrary, frustration was less persistent, less associated with poorer learning, and did not appear to be an antecedent to gaming the system. Confusion and engaged concentration were the most common states within all three learning environments. Experiences of delight and surprise were rare. These findings suggest that significant effort should be put into detecting and responding to boredom and confusion, with a particular emphasis on developing pedagogical interventions to disrupt the “vicious cycles” which occur when a student becomes bored and remains bored for long periods of time.

Our everyday surroundings besiege us with information. The battle is for a share of our limited attention and memory, with the brain selecting the winners and discarding the losers. Previous research shows that both bottom-up and top-down factors bias competition in favor of high priority stimuli. We propose that arousal during an event increases this bias both in perception and in long-term memory of the event. Arousal-biased competition theory provides specific predictions about when arousal will enhance memory for events and when it will impair it, which accounts for some puzzling contradictions in the emotional memory literature.

Executive control (EC) generally refers to the regulation of mental activity. It plays a crucial role in complex cognition, and EC skills predict high-level abilities including language processing, memory, and problem solving, as well as practically relevant outcomes such as scholastic achievement. EC develops relatively late in ontogeny, and many sub-groups of developmental populations demonstrate an exaggeratedly poor ability to control cognition even alongside the normal protracted growth of EC skills. Given the value of EC to human performance, researchers have sought means to improve it through targeted training; indeed, accumulating evidence suggests that regulatory processes are malleable through experience and practice. Nonetheless, there is a need to understand both whether specific populations might particularly benefit from training, and what cortical mechanisms engage during performance of the tasks used in the training protocols. This contribution has two parts: in Part I, we review EC development and intervention work in select populations. Although promising, the mixed results in this early field make it difficult to draw strong conclusions. To guide future studies, in Part II, we discuss training studies that have included a neuroimaging component - a relatively new enterprise that also has not yet yielded a consistent pattern of results post-training, preventing broad conclusions. We therefore suggest that recent developments in neuroimaging (e.g., multivariate and connectivity approaches) may be useful to advance our understanding of the neural mechanisms underlying the malleability of EC and brain plasticity. In conjunction with behavioral data, these methods may further inform our understanding of the brain-behavior relationship and the extent to which EC is dynamic and malleable, guiding the development of future, targeted interventions to promote executive functioning in both healthy and atypical populations.

There has been significant interest in the impact of anxiety disorders on quality of life. In this meta-analytic review, we empirically evaluate differences in quality of life between patients with anxiety disorders and nonclinical controls. Thirty-two patient samples from 23 separate studies (N=2892) were included in the analysis. The results yielded a large effect size indicating poorer quality of life among anxiety disorder patients vs. controls and this effect was observed across all anxiety disorders. Compared to control samples, no anxiety disorder diagnosis was associated with significantly poorer overall quality of life than was any other anxiety disorder diagnosis. Examination of specific domains of QOL suggests that impairments may be particularly prominent among patients with post-traumatic stress disorder. QOL domains of mental health and social functioning were associated with the highest levels of impairment among anxiety disorder patients. These findings are discussed in the context of future research on the assessment of quality of life in the anxiety disorders.

Electrophysiological and neuroimaging studies have shown that attention to visual motion can increase the responsiveness of the motion-selective cortical area V5 and the posterior parietal cortex (PP). Increased or decreased activation in a cortical area is often attributed to attentional modulation of the cortical projections to that area. This leads to the notion that attention is associated with changes in connectivity. We have addressed attentional modulation of effective connectivity using functional magnetic resonance imaging (fMRI). Three subjects were scanned under identical stimulus conditions (visual motion) while varying only the attentional component of the task. Haemodynamic responses defined an occipito-parieto-frontal network, including the, primary visual cortex (V1), V5 and PR A structural equation model of the interactions among these dorsal visual pathway areas revealed increased connectivity between V5 and PP related to attention. On the basis of our analysis and the neuroanatomical pattern of projections from the prefrontal cortex to PP we attributed the source of modulatory influences, on the posterior visual pathway, to the prefrontal cortex (PFC). To test this hypothesis we included the PFC in our model as a 'modulator' of the pathway between V5 and PP, using interaction terms in the structural equation model. This analysis revealed a significant modulatory effect of prefrontal regions on V5 afferents to posterior parietal cortex.

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People perceive meaningful wholes and later separate out constituent parts (D. Navon, 1977). Yet there are cross-national differences in whether a focal target or integrated whole is first perceived. Rather than construe these differences as fixed, the proposed culture-as-situated-cognition model explains these differences as due to whether a collective or individual mind-set is cued at the moment of observation. Eight studies demonstrated that when cultural mind-set and task demands are congruent, easier tasks are accomplished more quickly and more difficult or time-constrained tasks are accomplished more accurately (

STUDY 1
Koreans, Korean Americans; STUDY 2: Hong Kong Chinese; STUDY 3: European- and Asian-heritage Americans; STUDY 4: Americans;

STUDY
5 Hong Kong Chinese; STUDY 6: Americans; STUDY 7: Norwegians; STUDY 8: African-, European-, and Asian-heritage Americans). Meta-analyses (d = .34) demonstrated homogeneous effects across geographic place (East-West), racial-ethnic group, task, and sensory mode-differences are cued in the moment. Contrast and separation are salient individual mind-set procedures, resulting in focus on a single target or main point. Assimilation and connection are salient collective mind-set procedures, resulting in focus on multiplicity and integration.

*Correspondence: Athena Demertzi , Coma Science Group, Cyclotron Research Center, Allée du 6 août no 8, Sart Tilman B30, University of Liège, 4000 Liège, Belgium. e-mail: a.demertzi@ulg.ac.be In order to better understand the functional contribution of resting state activity to conscious cognition, we aimed to review increases and decreases in functional magnetic resonance imaging (fMRI) functional connectivity under physiological (sleep), pharmacological (anesthesia), and pathological altered states of consciousness, such as brain death, coma, vegetative state/unresponsive wakefulness syndrome, and minimally conscious state.The reviewed resting state networks were the DMN, left and right executive control, salience, sensorimotor, auditory, and visual networks. We highlight some methodological issues concerning resting state analyses in severely injured brains mainly in terms of hypothesis-driven seed-based correlation analysis and data-driven independent components analysis approaches. Finally, we attempt to contextualize our discussion within theoretical frameworks of conscious processes.We think that this “lesion” approach allows us to better determine the necessary conditions under which normal conscious cognition takes place. At the clinical level, we acknowledge the technical merits of the resting state paradigm. Indeed, fast and easy acquisitions are preferable to activation paradigms in clinical populations. Finally, we emphasize the need to validate the diagnostic and prognostic value of fMRI resting state measurements in non-communicating brain damaged patients.