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Welcome to Volume 4 of IEEE Journal of Microwaves! In this issue, we bring you 11 quality papers: two invited and nine regular submissions. We also celebrate six of our Outstanding Reviewers of 2023 and announce our IEEE Journal of Microwaves 2022 Best Paper prize. Our author and reader pools continue to expand and our usage counts per article published now exceed 1530. All of our 232 published articles from 2021 to 2023 now appear on Clarivate's Web of Science and we are looking forward to possibly receiving an impact factor this July. Remember to take a look at our solicitation for papers that can fit into our Microwaves in Climate Change special issue, which we intend to release before the end of 2024.

Welcome to Volume 3 of IEEE Journal of Microwaves! In this issue we combine a complete set of regular contributions with Part 1 of a Microwave Theory and Technology Society 70th Anniversary commemoration, consisting of some twenty-one specially invited papers embodying this major milestone in the history of the organization. Several additional articles, including some major historic overviews, are to be released in our spring issue of JMW which contains Part 2 of this 70th Anniversary celebration. In order to make it possible to bring up all the anniversary issue papers contained in both parts one and two using a single database search, every special issue paper contains the index term: “MTT 70th Anniversary Special Issue.” The full set (covering two issues) of 70th anniversary papers can be accessed using a simple parenthesis-delineated search of the five-word phrase. Plans are also in place to combine all the on-line papers into a full-color print issue for distribution upon request. In addition to this very nice collection of quality papers, we celebrate six of our Outstanding Reviewers of 2021 and 2022 and announce our first IEEE Journal of Microwaves Best Paper prize.

The article presents the discussion on considerable aspects of face-to-face human interactions remain difficult to relay. Topics include computer's ability capturing a human's emotion called affective sensing, alternatively called emotion sensing and more recently emotional artificial intelligence (emotional AI); and use of emotions in crowd and traffic management; to relaying emotions to and from the metaverse.

The article presents the discussion on sustainable urban development as populations rise and cities draw ever-larger populations. Topics include industrial Internet and Internet of Vehicles, smart energy systems, building management systems, cyber security; and presenting the technological advancement and challenges of smart cities and smart villages from the system design and implementation point of view.

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

The article discusses the telecommunication industry has evolved to provide services for new types of Internet of Things (IoT) devices in addition to basic mobile phone or internet services. Topics include the extended reality devices, sensors, and ground and aerial robots, to name a few. With the deployment of these new services, it is difficult for the wireless network to support ubiquitous connections with diverse quality-of-service (QoS) requirements.

The article reports that from the late 1970's onward, the global telecommunication industry has gone through several waves of regulatory and technological changes. Today, the very definition of telecommunication has changed. First, the traffic is no longer confined to voice and limited data services, but has become a fundamental pillar of the digital transformation that is affecting all aspects of our contemporary life.

The article offers information on the journal's call for feature topic (FT) proposals to complement its Series and Open Call publication tracks.

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

We present the results of a comprehensive multi-pass analysis of visualization paper keywords supplied by authors for their papers published in the IEEE Visualization conference series (now called IEEE VIS) between 1990–2015. From this analysis we derived a set of visualization topics that we discuss in the context of the current taxonomy that is used to categorize papers and assign reviewers in the IEEE VIS reviewing process. We point out missing and overemphasized topics in the current taxonomy and start a discussion on the importance of establishing common visualization terminology. Our analysis of research topics in visualization can, thus, serve as a starting point to (a) help create a common vocabulary to improve communication among different visualization sub-groups, (b) facilitate the process of understanding differences and commonalities of the various research sub-fields in visualization, (c) provide an understanding of emerging new research trends, (d) facilitate the crucial step of finding the right reviewers for research submissions, and (e) it can eventually lead to a comprehensive taxonomy of visualization research. One additional tangible outcome of our work is an online query tool (http://keyvis.org/) that allows visualization researchers to easily browse the 3952 keywords used for IEEE VIS papers since 1990 to find related work or make informed keyword choices. [ABSTRACT FROM PUBLISHER]

We consider a variable-length source coding problem subject to local decodability constraints. In particular, we investigate the blocklength scaling behavior attainable by encodings of $r$ -sparse binary sequences, under the constraint that any source bit can be correctly decoded upon probing at most $d$ codeword bits. We consider both adaptive and non-adaptive access models, and derive upper and lower bounds that often coincide up to constant factors. Such a characterization for the fixed-blocklength analog of our problem, known as the bit probe complexity of static membership, remains unknown despite considerable attention from researchers over the last few decades. We also show that locally decodable schemes for sparse sequences are able to decode 0s (frequent source symbols) of the source with far fewer probes on average than they can decode 1s (infrequent source symbols), thus rigorizing the notion that infrequent symbols require high probe complexity, even on average. Connections to the fixed-blocklength model and to communication complexity are also briefly discussed. [ABSTRACT FROM AUTHOR]

In one of the several manifestations, the future cellular networks are required to accommodate a massive number of devices, several orders of magnitude compared to today’s networks. At the same time, the future cellular networks will have to fulfill stringent latency constraints. To that end, one problem that is posed as a potential showstopper is extreme congestion for requesting uplink scheduling over the physical random access channel (PRACH). Indeed, such congestion drags along scheduling delay problems. In this paper, the use of self-organized device-to-device (D2D) clustering is advocated for mitigating PRACH congestion. To this end, this paper proposes two D2D clustering schemes, namely, random-based clustering and channel-gain-based clustering. Accordingly, this paper sheds light on random access within the proposed D2D clustering schemes and presents a case study based on a stochastic geometry framework. For the sake of objective evaluation, the D2D clustering is benchmarked by the conventional scheduling request procedure. Accordingly, this paper offers insights into useful scenarios that minimize the scheduling delay for each clustering scheme. Finally, this paper discusses the implementation algorithm and some potential implementation issues and remedies. [ABSTRACT FROM AUTHOR]

The December page is devoted to IEEE Communications Society Awards and the Awards Committee that receives the nominations and processes them to identify the recipients. ComSoc Awards are meant to honor colleagues who in some ways, either via scientific/technical contributions or exemplary services, have reached significant, widely recognized achievements in our telecommunications community. Owing to their high significance and value, they need to be awarded through a fair and transparent process, and this is the essential, yet difficult and heavy task of the Awards Committee. It is my pleasure to introduce Lajos Hanzo, the Chair of the IEEE Communications Society Awards Committee, who will describe the awards and the procedure followed by the Awards Committee. [ABSTRACT FROM PUBLISHER]

A substantial amount of research exists in the area of energy efficiency in communications and networking. In recognition of this fact, the IEEE Communications Society has decided to publish a series on Green Communications and Networking as three issues of the IEEE Journal On Selected Areas in Communications. The first issue of the Series was published in December 2015 with 39 papers. This second issue of the Series has 52 papers, covering a wide selection of topics. These topics can be characterized in five categories. The first category in this issue is cellular networks and consists of 15 papers. [ABSTRACT FROM AUTHOR]

This is Part II of the double-part Special Issue (SI) on Integrated Sensing and Communication (ISAC). This SI aims at bringing together contributions from both academia and industry to highlight the recent progress of ISAC, where sensing and communication (S $\$ $ C) functionalities are jointly designed to utilize wireless/hardware resources efficiently and to assist each other for mutual benefits. The 32 accepted articles of this SI are arranged into six groups, namely, 1) Fundamental Performance Bounds and Optimization, 2) Time-Frequency Signal Processing, 3) Spatial Signal Processing, 4) Networking and Resource Allocation, 5) ISAC With Emerging Communications Technologies, and 6) ISAC Applications. We kindly refer readers to Part I of this SI for a comprehensive overview written by the Guest Editorial Team, which provides both a bird’s eye view and technical details regarding state-of-the-art ISAC innovations. The contributions made by the papers in Part II are summarized as follows, which correspond to paper groups 4), 5), and 6). [ABSTRACT FROM AUTHOR]

The explosive growth of Internet-of-Things (IoT) applications such as smart cities and Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating the rapid development of new techniques for enhancing spectrum utilization needed by new generation wireless communication technologies. Among others, dynamic spectrum access (DSA) is one of the most widely accepted approaches. In this paper, as an enhancement of existing works, we take into consideration of inter-node collaborations in a dynamic spectrum environment. Typically, in such distributed circumstances, intelligent dynamic spectrum access almost invariably relies on self-learning to achieve dynamic spectrum access improvement. Whereas, this paper proposes a DSA scheme based on deep reinforcement learning to enhance spectrum and access efficiency. Unlike traditional Q-learning-based DSA, we introduce the following to enhance the spectrum efficiency in dynamic IoT spectrum environments. First, deep double Q-learning is adopted to perform local self-spectrum-learning for IoT terminals in order to achieve better dynamic access accuracy. Second, to accelerate learning convergence, federated learning (FL) in edge nodes is used to improve the self-learning. Third, multiple secondary users, who do not interfere with each other and have similar operation condition, are clustered for federated learning to enhance the efficiency of deep reinforcement learning. Comparing with the traditional distributed DSA with deep learning, the proposed scheme has faster access convergence speed due to the characteristic of global optimization for federated learning. Based on this, a framework of federated deep reinforcement learning (FDRL) for DSA is proposed. Furthermore, this scheme preserves privacy of IoT users in that FDRL only requires model parameters to be uploaded to edge servers. Simulations are performed to show the effectiveness of theproposed FDRL-based DSA framework. [ABSTRACT FROM AUTHOR]

Computer networks fundamentally changed the way we communicate and interact with each other. In fact, they now form the backbone of our modern societies. While early networks were merely a mechanism for exchanging data between end-hosts, current computer and telecommunication networks are way more than that. Compared to the early days of the networking not only the hardware of networks has changed fundamentally, but with it also the software deployed to control and manage these networks. To reduce the significant management cost of large networks, automated management, including autonomic computing and communications evolved. [ABSTRACT FROM PUBLISHER]

This paper focuses on the design and evaluation of pragmatic schemes for delay-sensitive communication. Specifically, this contribution studies the operation of data links that employ incremental redundancy as a means to shield information bits from the degradation associated with unreliable channels. While this inquiry puts forth a general methodology, exposition centers around erasure channels because they are well suited for analysis. Nevertheless, the goal is to identify both structural properties and design guidelines that are broadly applicable. Conceptually, this paper leverages a methodology, termed sequential differential optimization, aimed at identifying near-optimal block sizes for hybrid ARQ. This technique is applied to erasure channels and it is extended to scenarios where throughput is maximized subject to a constraint on the feedback rate. The analysis shows that the impact of the coding strategy adopted and the propensity of the channel to erase symbols naturally decouple when maximizing throughput. Ultimately, block size selection is informed by approximate distributions on the probability of decoding success at every stage of the incremental transmission process. This novel perspective, which rigorously bridges hybrid automatic repeat request and coding, offers a computationally efficient framework to select code rates and blocklengths for incremental redundancy. These findings are supported through numerical results. [ABSTRACT FROM AUTHOR]

With the proliferation of portable devices, the exponential growth of the global mobile traffic brings great challenges to the traditional communication networks and the traditional wireless communication technologies. In this context, converged networks and cache-based data offloading have drawn more and more attention based on the strong correlation of services. This paper proposes a novel popular services pushing and caching scheme by using converged overlay networks. The most popular services are pushed by terrestrial broadcasting networks. And they are cached in ${n}$ router-nodes with limited cache sizes. Each router-node only interconnects with its neighbor nodes. Users are served through the router’s WiFi link. If the services requested are cached in the routers, the user can be immediately responded; otherwise, the requests can be responded through the link from cellular stations to the router. In the proposed scheme, the cache size of the router, the maximum number of requests each router can serve, and the whole-time delay are limited. Three node-selecting and dynamic programming algorithms are adopted to maximize the equivalent throughput. Analytical and numerical results demonstrate that the proposed scheme is very effective. [ABSTRACT FROM AUTHOR]

Blockchain technology is becoming the cornerstone for the development and deployment of other technologies like Federated Learning (FL) and the Internet of Things (IoT), as it plays a critical role in data sharing and incentives. Blockchains supports decentralization, data-privacy protection, security, and reliability. Assuring secure data sharing in mobile computing and FL is challenging because of untrustworthy participants and unknown data quality. Blockchain provides trust in decentralized environments without requiring trusted third parties. By using smart contracts, blockchain has been able to supporting rich decentralized applications. However, the scalability of blockchain is a challenge that prevents its wide adoption by high-performance applications. To address the blockchain scalability issue, various blockchain sharding technologies and off-chain solutions have been proposed. To improve the network throughput, blockchain sharding divides the entire network into several smaller parallel groups and exploits fast consensus algorithms in blockchain shards. Off-chain solutions, such as payment channel networks (PCNs), transfer the slow on-chain transactions to the off-chain environment, in which transactions can be accelerated. Without consensus and on-chain expensive operations, off-chain scalable solutions significantly reduce transaction costs and increase transaction throughput. This special issue aims to provide a forum for the presentation of state-of-the-art research approaches that advance the construction of intelligent blockchain systems. A total of 27 articles were accepted after a two-round rigorous review process. Based on their topics, we have grouped the accepted articles into four categories: blockchain-based federated learning systems, blockchain and the IoT, blockchain scalability, and high-performance blockchains. In what follows, we introduce these articles and their contributions. [ABSTRACT FROM AUTHOR]

In the future era of intelligent networks, communication technology and network architecture need to be further developed to provide users with high-quality services. The Space-Air-Ground Integrated Networks (SAGIN) is seen as a potential architecture to provide ubiquitous communication and drive the era of the intelligent global network. The space and air segments in SAGIN can assist in offloading traffic from the ground segment. However, in a highly dynamic and heterogeneous network like SAGIN, offloading decisions are easily affected by the incorporated/malicious nodes. How to ensure security and improve network performance becomes a critical problem. In this paper, we address the above problem by jointly using blockchain and federated reinforcement learning (FRL). Firstly, we propose a blockchain-based secure federated learning framework that combines topology information chain and model chain to assist traffic offloading. Then, we propose a node security evaluation and an enhanced practical byzantine fault tolerance (EPBFT) algorithm to secure the traffic offloading process. Furthermore, we describe the traffic offloading problem as a Markov decision problem (MDP) and employ the Blockchain-based Federated Asynchronous Advantage Actor-Critic (BFA3C) algorithm to solve this problem. Finally, the simulation results show that the BFA3C-based algorithm used in SAGIN with/without malicious nodes achieves superior performance in terms of latency and security. [ABSTRACT FROM AUTHOR]

The testing of vehicular communication technologies, the study of urban mobility patterns, the evaluation of new traffic policies cannot dispense from vehicle mobility simulation. As is often the case, the larger the dataset, the better. Indeed, in recent years, many projects in the fields of mobility or vehicular communication have sought new traffic simulators with extended areas of investigation, possibly covering a whole city and its suburbs. In this spirit, we have modeled an urban traffic simulation in a 600-Km2 area in and around the Municipality of Turin, leveraging the SUMO tool. This paper aims at reporting in detail the methodology we followed in the creation of this dataset. Our results demonstrate that a complete modeling of such a wide area is possible at the expense of minor simplifications, reaching a very good level of approximation. [ABSTRACT FROM AUTHOR]

Space-division multiplexing (SDM) technology is a promising candidate to achieve massive parallelism in optical fiber cables and overcome the capacity limitation of the conventional single-mode fiber (SMF). Among the several kinds of SDM fiber, a weakly coupled multicore fiber (MCF) is advantageous in that it can be easily upgraded for use in existing equipment and requires no complex signal processing for optical multi-input multi-output (MIMO). In this article, we discuss the progress and standardization activity of MCF technologies from the viewpoint of accelerating the practical application of SDM technology. We first describe the possible application areas of SDM fibers and then show the recent progress of the essential technologies to construct the MCF link: the MCF itself, its splicing and connectorization, and the input/output techniques. We also discuss the availability and deployability of MCF as a large-capacity transmission medium and detail the progress on establishing a new international standard for SDM technology, which includes both historical progress and more recent endeavors on the standardization of optical fiber cables and SDM technology in International Telecommunication Union Telecommunication Standardization Sector (ITU-T) and International Electrotechnical Commission (IEC). We close with a summary of MCF technology and its standardization activity with an eye to next-generation transmission systems and the long-term development of ultralarge capacity SDM transmission technology. [ABSTRACT FROM AUTHOR]

Recently, reconfigurable intelligent surface (RIS) has drawn much attention due to its capability of improving coverage and communication performance. The development of RIS-assisted communication technology relies on deep understanding of RIS channel characteristics. However, most of the existing investigations focus on the impact of RIS, ignoring the existence of local scatterers in the real propagation environment. The ideal propagation condition limits the accuracy and application of the developed channel model. In this paper, we aim to analyze the channel characteristics of RIS-assisted near-filed communication by considering different conditions of local scatterers. Specifically, we propose a three-dimensional (3D) RIS-assisted multiple-input multiple-output (MIMO) channel model based on a three-dimensional cylinder model, which considers line-of-sight, single-bounced at RIS (SBR) and double-bounced (DB) modes where radio waves reflect from RIS and scatterers near receiver. Based on the proposed channel model, we investigate some key statistical properties for SBR and DB propagation, including the time-frequency-space correlation function and Doppler power spectrum. From the simulation results, it is found that RIS element number, RIS horizontal and vertical locations, distribution of surrounding scatterers, and movement of Rx have significant impacts on channel characteristics. Finally, channel capacities of SBR and DB modes are calculated, where the large size and appropriate locations of RIS significantly improve the channel capacity of RIS-assisted communication. These numerical results and observations can be used for design of RIS-assisted near-field communication systems. [ABSTRACT FROM AUTHOR]

Emerging communication technologies allow to reconfigure the physical network topology at runtime, enabling demand-aware networks (DANs): networks whose topology is optimized toward the workload they serve. However, today, only little is known about the fundamental algorithmic problems underlying the design of such demand-aware networks. This paper presents the first bounded-degree, demand-aware network, $\textit {cl-DAN} $ , which minimizes both congestion and route lengths. The degree bound $\Delta $ is given as part of the input. The designed network is provably (asymptotically) optimal in each dimension individually: we show that there do not exist any bounded-degree networks providing shorter routes (independently of the load), nor do there exist networks providing lower loads (independently of the route lengths). The main building block of the designed $\textit {cl-DAN} $ networks are $\textit {ego-trees}$ : communication sources arrange their communication partners in an optimal tree, individually. While the union of these ego-trees forms the basic structure of $\textit {cl-DANs}$ , further techniques are presented to ensure bounded degrees (for scalability). [ABSTRACT FROM AUTHOR]

Downlink transmission into frequency-selective links experiencing different coherence bandwidths and coherence times has obvious practical relevance, but is often addressed via assuming for all users the coherence conditions corresponding to the fastest, most dispersive user. This paper demonstrates an alternative approach that directly exploits the differences between coherence bandwidth and coherence time of users under frequency-selective conditions, showing that it can lead to significant new efficiencies and gains. More specifically, we study a two-user downlink frequency-selective channel under three broad conditions of disparity between the link qualities: when the disparity is in coherence time, in coherence bandwidth, and in both coherence time and coherence bandwidth. Each of the coherence scenarios calls for a distinct treatment; for each, we provide an analysis demonstrating the gains in achievable rates due to exploiting coherence disparity. Numerical simulations demonstrate the advantages of the proposed schemes. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

The objective of this special issue is to bring together the most updated research contributions addressing antennas for satellite communications (both spaceborne and user terminals), and propose new applications, solutions, and challenges for the future. [ABSTRACT FROM PUBLISHER]

Connected and automated vehicles will enable advanced traffic safety and efficiency applications thanks to the dynamic exchange of information between vehicles, and between vehicles and infrastructure nodes. Connected vehicles can utilize IEEE 802.11p for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. However, a widespread deployment of connected vehicles and the introduction of connected automated driving applications will notably increase the bandwidth and scalability requirements of vehicular networks. This paper proposes to address these challenges through the adoption of heterogeneous V2V communications in multi-link and multi-RAT vehicular networks. In particular, the paper proposes the first distributed (and decentralized) context-aware heterogeneous V2V communications algorithm that is technology and application agnostic, and that allows each vehicle to autonomously and dynamically select its communications technology taking into account its application requirements and the communication context conditions. This study demonstrates the potential of heterogeneous V2V communications, and the capability of the proposed algorithm to satisfy the vehicles’ application requirements while approaching the estimated upper bound network capacity. [ABSTRACT FROM AUTHOR]

With the explosive proliferation of connected devices and mobile users in the Internet-of-things, multiple access techniques are urged to be developed for the next generation wireless communications. Recently, rate-splitting multiple access (RSMA) has been a promising communication technology that holds advantages of strong robustness, low complexity, and high spectral efficiency, which can be integrated with the indoor visible light communication (VLC) broadcast system to compensate for the shortcomings of limited modulation bandwidth of LEDs. However, the research on the RSMA-based VLC systems is still in its infancy and there exist various problems to be explored. To benefit from the RSMA technique, this paper investigates the energy efficiency optimizations for both single-cell and multi-cell RSMA-based VLC broadcast systems. Specifically, these two systems are modeled, where the VLC broadcast channel follows Lambertian radiation model, and the splitting design and successive interference cancellation of RSMA are employed to mitigate the multi-user interference. Especially for multi-cell networks, the zero-forcing approach is adopted to eliminate the inter-cell interference. To maximize the energy efficiency, the precoding and power allocation problems are formulated for single-cell and multi-cell networks while accommodating multiple constraints including dynamic operation ranges of LEDs, QoS requirements, and interference elimination. For solving these non-convex fractional problems, two pieces of successive convex approximation (SCA)-based algorithms are proposed, in which the variable transformation and linear approximation are adopted. Simulation results indicate that the proposed schemes can achieve superior energy efficiency with fast convergence for various network loads and user deployments. [ABSTRACT FROM AUTHOR]

An inverse matrix auto-search algorithm for radiated two-stage (RTS) multiple-input and multiple-output (MIMO) over-the-air (OTA) tests is proposed in this paper. The RTS method is one of the significant techniques for the MIMO OTA test and was provided by organizations such as the Cellular Telecommunication and Internet Association and the Third-Generation Partnership Project. An extremely important basic step in the RTS test procedure is to select an appropriate combination of measurement antennas and device-under-test orientation for inverse matrix solving. The automatic resolving algorithm proposed in this paper can be divided into two parts: the technique for selecting the appropriate combinations for inverse matrix solving, and the method for solving the inverse matrix at a fixed combination. The technique proposed in this paper can make the RTS test procedure automatic and fast, which greatly improves the user experience. The most mentionable advantage of the technique is that only 2 min are required for the whole process including the appropriate combination calculation and the inverse matrix solving at the selected combination, while several hours might be needed using the traversal method. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of decoding in large-scale multiple-input–multiple-output (MIMO) systems. In this case, the optimal maximum-likelihood (ML) detector becomes impractical due to an exponential increase in the complexity with the signal and the constellation dimensions. This paper introduces an iterative decoding strategy with a tolerable complexity order. We consider a MIMO system with finite constellation and model it as a system with sparse signal sources. We propose an ML relaxed detector that minimizes the Euclidean distance with the received signal while preserving a constant \ell1 -norm of the decoded signal. We also show that the detection problem is equivalent to a convex optimization problem, which is solvable in polynomial time. Two applications are proposed, and simulation results illustrate the efficiency of the proposed detector. [ABSTRACT FROM PUBLISHER]

The degrees of freedom (DoFs) of the $K$ -user Gaussian interference channel determine the asymptotic growth of the maximal sum rate as a function of the signal-to-noise ratio. Subject to a very general sufficient condition on the cross-channel gains, we give a formula for the DoFs of the scalar interference channel as a function of the deterministic channel matrix, which involves maximization of a sum of information dimensions over $K$ scalar input distributions. Known special cases are recovered, and even generalized in certain cases with unified proofs. [ABSTRACT FROM PUBLISHER]

Cellular heterogeneous networks (HetNets), which are realized through shared carrier deployments of macrocells and small cells, are widely seen as a potential solution to serve growing data capacity demands. While these networks pose significant challenges in interference management, much of the focus in earlier efforts has been limited only to small-cell range expansion in the downlink. In this paper, we provide a comprehensive analysis of interference management techniques applicable to the uplink of cellular HetNets, with the goal of characterizing and improving edge user (e.g., 5th percentile) performance. In particular, we propose and study virtual soft-handoff (VSHO), which offers a low-complexity and low-overhead solution that exploits the link asymmetry observed in the uplink geometry of HetNets. VSHO exploits the fact that, in the uplink, an edge macro user who suffers from very low throughput may be closer to a nearby small cell than its own macrocell. The intuition is that such macro users should have better decoding opportunity when their signals are processed at the nearby small cell with better channel conditions. We also study how interference cancelation (IC) and interference avoidance through resource blanking can be incorporated into our VSHO proposal for further throughput gains. In addition to the VSHO techniques outlined in this paper, we also analyze other candidate techniques available in the Third Generation Partnership Project Long-Term Evolution (3GPP-LTE), such as cell-range expansion (CRE) and joint processing, to present a unified view of interference management options available in HetNets. [ABSTRACT FROM PUBLISHER]

Technical developments in communication technology and measurement synchronization have facilitated the design of advanced protection schemes, such as Line Current Differential Relays (LCDRs). However, the superior performance of LCDRs is achieved at the expense of exposing them to cyber-threats, since cyber-induced intrusions against protective relays—which take advantage of the direct control of relays over circuit-breakers—can cause protection system mis-operations. To address this problem, this paper presents a Learning-based Framework (LBF) for detecting False Data Injection Attacks (FDIAs) and Time Synchronization Attacks (TSAs) against LCDRs, and for differentiating them from faults. In the proposed LBF, a Multi-Layer Perceptron (MLP) model is trained based on differential and super-imposed features, which are selected using the Recursive Feature Elimination method. After implementing the proposed LBF in LCDRs, when an LCDR picks up, it initially extracts the features and sends them to the trained MLP model. The LCDR trips the line if the proposed LBF confirms a fault. The performance of the proposed LBF is corroborated using the IEEE 39-bus test system. Evaluation results show that the proposed LBF (i) works independently of a system's operating point and configuration, (ii) is not considerably affected by instrumentation errors, and (iii) can accurately detect FDIAs and TSAs. [ABSTRACT FROM AUTHOR]

Orthogonal frequency-division multiplexing (OFDM) is a promising technology for communication systems. This paper investigates the impacts of unknown noise variance on the popular spectrum sensing scheme, i.e., energy detection, for OFDM cognitive radios over multipath fading channels. To study the effects of unknown parameters on the energy detector, a new maximum-likelihood estimation of noise and signal powers employing the cyclic prefix of OFDM is presented in this paper. The mean values and Cram $\acute{\text{e}}$ r–Rao lower bounds of the estimation are obtained. Furthermore, the performances of the energy detector for both hypotheses, i.e., false-alarm rate and detection probability, under the influence of unknown noise variance are validated by both simulation and analytical results. The assessment on the required number of samples for the proposed energy detector is conducted, which indicates that an amount of 40–50% samples can be saved compared to the conventional energy detector. [ABSTRACT FROM AUTHOR]

Array antennas are increasingly used for transmission and reception in applications such as telecommunication, medical imaging, radar, or radio astronomy. Low-loss matching networks are inserted in each channel between the antenna and amplifiers in order to optimize power transfer in transmission and/or signal-to-noise ratio (SNR) in reception. The adjustment of these matching components becomes challenging if residual coupling between antenna elements significantly influences the results. The most general, so-called, array noise matching then leads to the optimum SNR taking into account the noise-coupling effects also. This paper describes that concept completely in the scattering matrix domain using waves for signal and noise rather than voltages and currents. [ABSTRACT FROM AUTHOR]

Nonregenerative pulsewidth-modulated (PWM) rectifiers are increasingly being considered for applications, where the power flow is unidirectional, such as power supplies for telecommunications, X-ray, the machine-side converter for wind energy conversion systems, etc. They use fewer active switches, which increase their power density and reduce cost. This paper proposes a novel reduced switch topology for a multilevel (five-level or higher) nonregenerative PWM rectifier. It uses only four controlled switches and eight diodes per phase for a five-level rectifier. Half of the diodes are naturally commutated (zero current switching) at the line frequency, which reduces switching losses. This topology has several other advantages compared to similar topologies reported in the literature, such as minimum voltage stress across the devices, elimination of transient voltage-balancing snubbers, no extra hardware for balancing the flying capacitors, the dc-link mid-point voltage, etc. In this paper, switching cycle average modeling and the carrier-based modulation strategy for this rectifier are also presented to maintain a balanced dc link and to regulate flying capacitor voltages, while achieving unity displacement factor at the rectifier input terminals. The overall performance of the rectifier is verified by experimental results. [ABSTRACT FROM AUTHOR]

This paper studies the asymptotic performance of multi-hop amplify-and-forward relay multiple-antenna communication channels. Each multi-antenna relay terminal in the considered network amplifies the received signal, sent by a source, and retransmits it upstream toward a destination. Achievable ergodic rates of the relay channel with both jointly optimal detection and decoding and practical separate-decoding receiver architectures for arbitrary signaling schemes, along with average bit error rates for various types of detectors are derived in the regime where the number of antennas at each terminal grows large without a bound. To overcome the difficulty of averaging over channel realizations, we apply a large-system analysis based on the replica method from statistical physics. The validity of the large-system analysis is further verified through Monte Carlo simulations of realistic finite-sized systems. [ABSTRACT FROM AUTHOR]

In the Master’s of Telecommunication Engineering program at the University of Deusto, Spain, courses in communication circuit design, electronic instrumentation, advanced systems for signal processing and radiocommunication systems allow students to acquire concepts crucial to the fields of electronics and communication. During the educational project presented in this paper, students build a continuous-wave frequency-modulation (CWFM) Doppler radar system from components as simple as ordinary cocoa cans and common electronics components placed on a breadboard without any soldering. One of the goals of the project is to stimulate students' interest in building an entire, completely functional communication system that integrates the knowledge acquired in the various courses and whose functioning they can check in real scenarios. This paper describes this learning project and the ways in which it helps students understand and connect all the concepts that underlie a fully operative communications system, thus meeting the competencies and learning outcomes of the courses involved in the project. [ABSTRACT FROM PUBLISHER]

By introducing rapid and innovative network functions, software-based networking and virtualization are fundamentally revamping how the communication infrastructures are designed, programmed and operated. Network slicing, mobile edge computing, new radio access networks, and programmable cloud-native services represent some of the key technical components of future network infrastructures, including 5G networks that started being commercialized in 2019. The third issue of the "Telecom Software, Network Virtualization, and Software Defined Networks" series features five papers that deal with critical aspects of future networks, such as the adoption of edge computing technologies for mobile networks; the use of network slicing for 5G access and mission-critical services; advanced techniques for virtualized network programmability; and automation of virtualized network security services. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive survey of recent advances in deep learning (DL) techniques for channel coding problems. Inspired by the recent successes of DL in a variety of research domains, its applications to physical layer technologies have been extensively studied in recent years, and they are expected to be a potential breakthrough in supporting the emerging use cases of the next generation wireless communication systems such as 6G. In this paper, we focus exclusively on channel coding problems and review existing approaches that incorporate advanced DL techniques into code design and channel decoding. After briefly introducing the background of recent DL techniques, we categorize and summarize a variety of approaches, including model-free and model-based DL, for the design and decoding of modern error-correcting codes, such as low-density parity check (LDPC) codes and polar codes, to highlight their potential advantages and challenges. Finally, the paper concludes with a discussion of open issues and future research directions in channel coding.