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Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users' location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages, and implications. Notably, we demonstrate an impressive 53% improvement in the signal-to-interference-plus-noise ratio by implementing the adaptive beamforming maximum ratio transmission (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of artificial intelligence (AI) schemes, including machine learning and deep learning, in implementing contextual beamforming techniques that leverage user location information. Based on the comprehensive review, the results suggest that the combination of MRT and zero-forcing techniques, alongside deep neural networks employing Bayesian optimization, represents the most promising approach for contextual beamforming. Furthermore, the study discusses the future potential of programmable switches, such as Tofino—an innovative switch developed by Barefoot Networks (now a part of Intel)—in enabling location-aware beamforming. This paper highlights the significance of contextual beamforming for improving wireless telecommunications performance. By capitalizing on location information and employing advanced AI techniques, the field can overcome challenges and unlock new possibilities for delivering reliable and efficient mobile networks. [ABSTRACT FROM AUTHOR]

A wideband low-profile radiating G-shaped strip on a flexible substrate is proposed to operate as biomedical antenna for off-body communication. The antenna is designed to produce circular polarization over the frequency range 5–6 GHz to communicate with WiMAX/WLAN antennas. Furthermore, it is designed to produce linear polarization over the frequency range 6–19 GHz for communication with the on-body biosensor antennas. It is shown that an inverted G-shaped strip produces circular polarization (CP) of the opposite sense to that produced by G-shaped strip over the frequency range 5–6 GHz. The antenna design is explained and its performance is investigated through simulation, as well as experimental measurements. This antenna can be viewed as composed of a semicircular strip terminated with a horizontal extension at its lower end and terminated with a small circular patch through a corner-shaped strip extension at its upper end to form the shape of "G" or inverted "G". The purpose of the corner-shaped extension and the circular patch termination is to match the antenna impedance to 50 Ω over the entire frequency band (5–19 GHz) and to improve the circular polarization over the frequency band (5–6 GHz). To be fabricated on only one face of the flexible dielectric substrate, the antenna is fed through a co-planar waveguide (CPW). The antenna and the CPW dimensions are optimized to obtain the most optimal performance regarding the impedance matching bandwidth, 3dB Axial Ratio (AR) bandwidth, radiation efficiency, and maximum gain. The results show that the achieved 3dB-AR bandwidth is 18% (5–6 GHz). Thus, the proposed antenna covers the 5 GHz frequency band of the WiMAX/WLAN applications within its 3dB-AR frequency band. Furthermore, the impedance matching bandwidth is 117% (5–19 GHz) which enables low-power communication with the on-body sensors over this wide range of the frequency. The maximum gain and radiation efficiency are 5.37 dBi and 98%, respectively. The overall antenna dimensions are 25 × 27 × 0.13 mm 3 and the bandwidth-dimension ratio (BDR) is 1733. [ABSTRACT FROM AUTHOR]

Wireless communication has become an integral part of modern vehicles. However, securing the information exchanged between interconnected terminals poses a significant challenge. Effective security solutions should be computationally inexpensive, ultra-reliable, and capable of operating in any wireless propagation environment. Physical layer secret key generation has emerged as a promising technique, which leverages the inherent randomness of wireless-channel responses in amplitude and phase to generate high-entropy symmetric shared keys. The sensitivity of the channel-phase responses to the distance between network terminals makes this technique a viable solution for secure vehicular communication, given the dynamic behavior of these terminals. However, the practical implementation of this technique in vehicular communication is hindered by fluctuations in the communication link between line-of-sight (LoS) and non-line-of-sight (NLoS) conditions. This study introduces a key-generation approach that uses a reconfigurable intelligent surface (RIS) to secure message exchange in vehicular communication. The RIS improves the performance of key extraction in scenarios with low signal-to-noise ratios (SNRs) and NLoS conditions. Additionally, it enhances the network's security against denial-of-service (DoS) attacks. In this context, we propose an efficient RIS configuration optimization technique that reinforces the signals received from legitimate users and weakens the signals from potential adversaries. The effectiveness of the proposed scheme is evaluated through practical implementation using a 1-bit RIS with 64 × 64 elements and software-defined radios operating within the 5G frequency band. The results demonstrate improved key-extraction performance and increased resistance to DoS attacks. The hardware implementation of the proposed approach further validated its effectiveness in enhancing key-extraction performance in terms of the key generation and mismatch rates, while reducing the effect of the DoS attacks on the network. [ABSTRACT FROM AUTHOR]

Using reconfigurable intelligent surfaces (RISs) to improve the coverage and the data rate of future wireless networks is a viable option. These surfaces are constituted of a significant number of passive and nearly passive components that interact with incident signals in a smart way, such as by reflecting them, to increase the wireless system's performance as a result of which the notion of a smart radio environment comes to fruition. In this survey, a study review of RIS‐assisted wireless communication is supplied starting with the principles of RIS which include the hardware architecture, the control mechanisms, and the discussions of previously held views about the channel model and pathloss; then the performance analysis considering different performance parameters, analytical approaches and metrics are presented to describe the RIS‐assisted wireless network performance improvements. Despite its enormous promise, RIS confronts new hurdles in integrating into wireless networks efficiently due to its passive nature. Consequently, the channel estimation for, both full and nearly passive RIS and the RIS deployments are compared under various wireless communication models and for single and multi‐users. Lastly, the challenges and potential future study areas for the RIS aided wireless communication systems are proposed. [ABSTRACT FROM AUTHOR]

A study of the behavior of NB-IoT wireless communication in an industrial indoor environment was conducted in this paper. With Wireless Insite software, a scenario in the industrial sector was simulated and modeled. Our research examined how this scenario or environment affected the communication parameters of NB-IoT's physical layer. In this context, throughput levels among terminals as well as between terminals and transceiver towers, the power received at signal destination points, signal-to-noise ratios (SNRs) in the environment, and distances between terminals and transceivers are considered. These simulated results are also compared with the calculated or theoretical values of these parameters. The results show the effect of the industrial setting on wireless communication. The differences between the theoretical and simulated values are also established. [ABSTRACT FROM AUTHOR]

Next‐generation wireless communication networks, in particular, the densified 5G will bring many developments to the existing telecommunications industry. The key benefits will be the higher throughput and very low latency. In this context, the usage of unmanned aerial vehicle (UAV) is becoming a feasible option for deploying 5G services on demand. At the same time, the immense bandwidth potential of mmWave has strengthened its performance in radio communication. In this article, we provide a consolidated synthesis on the role of UAVs and mmWave in 5G, emphasis on recent developments and challenges. The review focuses on UAV relay architectures, identifies the relevant problems and limitations in the deployment of UAVs using mmWave in both access and backhaul links simultaneously. There is a critical analysis of the optimum placement of the UAVs as a relay with a focus on the mmWave band. The distinctive rich characteristics of the mmWave propagation and scattering are presented. We also synthesis mmWave path loss models. Then, the scope of artificial intelligence and machine learning techniques as an efficient solution for combating the dynamic and complex nature of UAV‐based cellular communication networks are discussed. In the end, security and privacy issues in UAV‐based cellular network are spotlighted. It is believed that the literature discussed, and the findings reached in this article are of significant importance to researchers, application engineers and decision‐makers in the designing and deployment of UAV‐supported 5G network. [ABSTRACT FROM AUTHOR]

Original distributed consensus algorithms are typically engineered with wired communication networks in mind. However, when these algorithms are applied in wireless networks, the unique characteristics of wireless communication among nodes, including high error rates, variable latency, and dynamic network topology, present novel challenges that necessitate the development of adaptive protocols. This article aims to address these challenges by designing an adaptive protocol specifically for the implementation of the Raft consensus algorithm within wireless environments. We first outline the key stages of this adaptive protocol, focusing on enhancing robustness and efficiency in the state synchronization and routing processes, which are demonstrated through extensive simulations. The proposed adaptive protocol intends to ensure consistent states across nodes in wireless networks, which promote reliable and effective distributed systems for a variety of applications in autonomous wireless networks, including Vehicle-to-everything (V2X), Internet of Things (IoT), and edge computing. [ABSTRACT FROM AUTHOR]

Providing higher data rate is a momentous goal for wireless communications systems, while interference is an important obstacle to reach this purpose. To cope with this problem, interference alignment (IA) has been proposed. In this paper, we propose two rank minimization methods to enhance the performance of IA in the presence of uncoordinated interference, i.e., interference that cannot be properly aligned with the rest of the network and thus is a crucial issue. In this scenario, perfect and imperfect channel state information (CSI) cases are considered. Our proposed approaches employ the $l_{2}$ and the Schatten- $p$ norms to approximate the rank function, due to its non-convexity. Also, we propose a new convex relaxation to expand the feasible set of our optimization problem, providing lower rank solutions compared to other IA methods from the literature. In addition, we propose a modified weighted-sum method to deal with interference in the relay-aided MIMO interference channel, which employs a set of weighting parameters in order to find more solutions. [ABSTRACT FROM AUTHOR]

Recently, mobile crowd sensing (MCS) is captivating growing attention because of their suitability for enormous range of new types of context-aware applications and services. This is attributed to the fact that modern smartphones are equipped with unprecedented sensing, computing, and communication capabilities that allow them to perform more complex tasks besides their inherent calling features. Despite a number of merits, MCS confronts new challenges due to network dynamics, the huge volume of data, sensing task coordination, and the user privacy problems. In this paper, a comprehensive review of MCS is presented. First, we highlight the distinguishing features and potential advantages of MCS compared to conventional sensor networks. Then, a taxonomy of MCS is devised based on sensing scale, level of user involvement and responsiveness, sampling rate, and underlying network infrastructure. Afterward, we categorize and classify prominent applications of MCS in environmental, infrastructure, social, and behavioral domains. The core architecture of MCS is also described. Finally, we describe the potential advantages, determine and reiterate the open research challenges of MCS and illustrate possible solutions. • A comprehensive review of mobile crowd sensing is presented. • A taxonomy of mobile crowd sensing is devised based on various factors. • Emerging mobile crowd sensing applications are categorized and classified. • An architecture of mobile crowd sensing is described based on the provided services and the interacting entities. • The core challenges of mobile crowd sensing are identified and highlighted. [ABSTRACT FROM AUTHOR]

Wireless networks are undergoing a transition from connecting people to connecting things, which will allow human interaction with the physical world in a real-time fashion, for example, Tactile Internet, industrial automation, self-driving vehicles, and remote surgery. Therefore, future wireless networks need to support real-time control since it is the essential function enabling such emerging applications. In this article, some fundamental design capabilities needed to realize real-time control in future wireless networks are discussed, with primary emphasis given to communication- control because both communication and control systems have strong dynamics and interdependencies, and they tightly interact with each other. A case study is provided to demonstrate the necessity of such co-design. [ABSTRACT FROM AUTHOR]

The homogeneous spatial Poisson point process (SPPP) is widely used for spatial modeling of mobile terminals (MTs). This process is characterized by a homogeneous distribution, complete spatial independence, and constant intensity measure. However, it is intuitive to understand that the locations of MTs are neither homogeneous, due to inhomogeneous terrain, nor independent, due to homophilic relations. Moreover, the intensity is not constant due to mobility. Therefore, assuming an SPPP for spatial modeling is too simplistic, especially for modeling realistic emerging device-centric frameworks such as device-to-device (D2D) communication. In this paper, assuming inhomogeneity, positive spatial correlation, and random intensity measure, we propose a doubly stochastic Poisson process, a generalization of the homogeneous SPPP, to model D2D communication. To this end, we assume a permanental Cox process (PCP) and propose a novel Euler-Characteristic-based approach to approximate the nearest-neighbor distribution function. We also propose a threshold and spatial distances from an excursion set of a chi-square random field as interference control parameters for different cluster sizes. The spatial distance of the clusters is incorporated into a Laplace functional of a PCP to analyze the average coverage probability of a cellular user. A closed-form approximation of the spatial summary statistics is in good agreement with empirical results, and its comparison with an SPPP authenticates the correlation modeling of D2D nodes. [ABSTRACT FROM AUTHOR]

The increasing popularity of wireless services and devices necessitates high bandwidth requirements; however, spectrum resources are not only limited but also heavily underutilized. Multiple license channels that support the same levels of QoS are desirable to resolve the problems posed by the scarcity and inefficient use of spectrum resources in multi-channel cognitive radio networks (MCRNs). One reason is that multimedia services and applications have distinct, stringent QoS requirements. However, due to a lack of coordination between primary and secondary users, identifying the QoS levels supported over available licensed channels has proven to be problematic and has yet to be attempted. This article presents a novel Bayesian non-parametric channel clustering scheme, which identifies the QoS levels supported over available license channels. The proposed scheme employs the infinite Gaussian mixture model and collapsed Gibbs sampler to identify the QoS levels from the feature space of the bit rate, packet delivery ratio, and packet delay variation of licensed channels. Moreover, the real measurements of wireless data traces and comparisons with baseline clustering schemes are used to evaluate the performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

Due to the use of an appropriately designed pulse shaping prototype filter, filter bank multicarrier (FBMC) system can achieve low out of band (OoB) emissions and is also robust to the channel and synchronization errors. However, it comes at a cost of long filter tails, which may reduce the spectral efficiency significantly when the block size is small. Filter output truncation (FOT) can reduce the overhead by discarding the filter tails but may also significantly destroy the orthogonality of FBMC system, by introducing intercarrier interference (ICI) and intersymbol interference (ISI) terms in the received signal. As a result, the signal-to-interference ratio (SIR) is degraded. In addition, the presence of intrinsic interference terms in FBMC also proves to be an obstacle in combining multiple-input multiple-output (MIMO) with FBMC. In this paper, we present a theoretical analysis on the effect of FOT in an MIMO-FBMC system. First, we derive the matrix model of MIMO-FBMC system, which is subsequently used to analyze the impact of finite filter length and FOT on the system performance. The analysis reveals that FOT can avoid the overhead in the time domain but also introduces extra interference in the received symbols. To combat the interference terms, we then propose a compensation algorithm that considers odd and even overlapping factors as two separate cases, where the signals are interfered by the truncation in different ways. The general form of the compensation algorithm can compensate all the symbols in a MIMO-FBMC block and can improve the SIR values of each symbol for better detection at the receiver. It is also shown that the proposed algorithm requires no overhead and can still achieve a comparable bit error rate (BER) performance to the case with no filter truncation. [ABSTRACT FROM AUTHOR]

In energy harvesting wireless communication systems, transmitter harvests energy from the surrounding environment and stores it in a finite sized battery. During storage, part of the harvested energy is lost due to inefficiency of the storage devices. Moreover, a notable amount of energy is utilized as circuit power consumption. In this paper, we consider a single-user energy harvesting model and propose optimum power allocation policies by explicitly considering energy storage losses and circuit power consumption. To reduce energy losses, we consider a finite time fraction during which transmitter and receiver are turned 'on' and a power level is assigned for data transmission. The optimization problem is formulated as a throughput maximization problem. Lagrange multiplier method and KKT conditions are applied and an offline algorithm is proposed to find optimum thresholds for power allocation. Similarly, an online policy is derived with water-level thresholds. These thresholds vary with storage efficiency and value of an epoch. Simulation results show an improved performance as compared to the earlier work considering energy storage losses. [ABSTRACT FROM AUTHOR]

The homogeneous Poisson point process is widely used to model spatial distribution of base stations and mobile terminals. The same process can be used to model underlay device-to-device (D2D) network; however, neglecting homophilic relation for D2D pairing presents underestimated system insights. In this paper, we model both spatial and social distributions of interfering D2D nodes as proximity-based independently marked homogeneous Poisson point process. The proximity considers physical distance between D2D nodes whereas social relationship is modeled as Zipf-based marks. We apply these two paradigms to analyze the effect of interference on coverage probability of distance-proportional power-controlled cellular user. Effectively, we apply two types of functional mappings (physical distance, social marks) to Laplace functional of PPP. The resulting coverage probability has no closed-form expression; however, for a subset of social marks, the mark summation converges to digamma and polygamma functions. This subset constitutes the upper and lower bounds on coverage probability. We present numerical evaluation of these bounds on coverage probability by varying number of different parameters. The results show that by imparting simple power control on cellular user, ultradense underlay D2D network can be realized without compromising the coverage probability of cellular user. [ABSTRACT FROM PUBLISHER]

Wireless body area networks are captivating growing interest because of their suitability for wide range of applications. However, network lifetime is one of the most prominent barriers in deploying these networks for most applications. Moreover, most of these applications have stringent QoS requirements such as delay and throughput. In this paper, the modified superframe structure of IEEE 802.15.4 based MAC protocol is proposed which addresses the aforementioned problems and improves the energy consumption efficiency. Moreover, priority guaranteed CSMA/CA mechanism is used where different priorities are assigned to body nodes by adjusting the data type and size. In order to save energy, a wake-up radio based mechanism to control sleep and active modes of body sensors are used. Furthermore, a discrete time finite state Markov model to find the node states is used. Analytical expressions are derived to model and analyze the behavior of average energy consumption, throughput, packet drop probability, and average delay during normal and emergency data. Extensive simulations are conducted for analysis and validation of the proposed mechanism. Results show that the average energy consumption and delay are relatively higher during emergency data transmission with acknowledgment mode due to data collision and retransmission. [ABSTRACT FROM AUTHOR]

In this paper, using stochastic geometry, we investigate the average energy efficiency (AEE) of the user terminal (UT) in the uplink of a two-tier heterogeneous network, where the two tiers are operated on separate carrier frequencies. In such a deployment, a typical UT must periodically perform the interfrequency small-cell discovery (ISCD) process to discover small cells in its neighborhood and benefit from the high data rate and traffic offloading opportunity that small cells present. We assume that the base stations of each tier and UTs are randomly located, and we derive the average ergodic rate and UT power consumption, which are later used for our AEE evaluation. The AEE incorporates the percentage of time that a typical UT missed small-cell offloading opportunity as a result of the periodicity of the ISCD process. The additional power consumed by the UT due to the ISCD measurement is also included. Moreover, we derive the optimal ISCD periodicity based on the UT's average energy consumption (AEC) and AEE. Our results reveal that ISCD periodicity must be selected with the objective of either minimizing the UT's AEC or maximizing the UT's AEE. [ABSTRACT FROM PUBLISHER]

Key distribution is essential for providing secure communication between commercial and sensitive applications of wireless sensor and actor networks (WSANs). It becomes more challenging when any of the intermediate sensor nodes is compromised by the adversaries as the messages carrying secure keys will be exposed and links will be unreliable. This paper presents a Disjoint Key Establishment Protocol (DKEP) that does not require transmitting keys across the nodes. In DKEP, each node is preloaded with one row and one column from a matrix. After the deployment, indices for row and column are exchanged between the two nodes and values at intersection of row and column index will be used to calculate the key on each node. DKEP is verified by performing formal analysis using Rubin Logic and validated using simulations in NS-2. Simulation results demonstrate the effectiveness and efficiency of DKEP compared to contemporary schemes in terms of reducing storage and communication cost and improving resilience against node compromise attacks. Moreover, the proposed scheme is implemented in a group-based mobile application scenario for secure message exchange. [ABSTRACT FROM AUTHOR]

Energy efficient and reliable communication is extremely crucial in most of the applications of Wireless Body Area Networks (WBANs). Communication between sensor nodes is the major energy guzzler that limits the network lifetime and hence, disrupt WBAN's operation. Moreover, unreliability in wireless communication caused by the channel impairments, such as shadowing and fading, further exacerbate the situation. This paper presents a new three-stage cooperative relaying scheme which proves to be energy efficient and reliable for WBANs. Analytical expressions for the Energy Efficiency (EE) and Packet Error Rate (PER) are also derived in this study. [ABSTRACT FROM AUTHOR]

In wireless communication, received signal strength indicator (RSSI) is a measurement of power in the received signal. This parameter is mainly used in radio frequency (RF) based distance estimation, position estimation, and handover mechanisms. In real-time applications such as object tracking, a handover mechanism, distance estimations require continuous reception of RSSI measurements in order to accurately estimate the position of the object. However, there are some constraints such as signal attenuation, signal loss, multi-path effects. These parameters cause variations in RSSI, and hence it becomes weak, which produces communication holes. Communication holes refer to the phenomenon when the signal drops to zero, and there is a communication blockage, which is practically negligible and can be considered as disconnection. This communication hole occurs due to various factors such as multi-path effects, noise, moving out of the coverage zone, device manufacturing faults, and inquiry procedure as well. The main focus of this paper is to address the issue of communication holes in Bluetooth networks. In Bluetooth networks communication holes also occur due to the delay in the inquiry procedure. Therefore, an existing gradient filter is modified based on the most recent measurements received. The proposed extended gradient filter is tested using simulated and real time RSSI measurements and compared with Kalman Filter and Kalman Smoother. The results show better performance in case of communication holes occurrence. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) were envisaged to become the fabric of our environment and society. However, they are yet unable to surmount many operational challenges such as limited network lifetime, which strangle their widespread deployment. To prolong WSN lifetime, most of the existing clustering schemes are geared towards homogeneous WSN. This paper presents enhanced developed distributed energy-efficient clustering (EDDEEC) scheme for heterogeneous WSN. EDDEEC mainly consists of three constituents i.e., heterogeneous network model, energy consumption model, and clustering-based routing mechanism. Our heterogeneous network model is based on three energy levels of nodes. Unlike most works, our energy consumption model takes into account the impact of radio environment. Finally, the proposed clustering mechanism of EDDEEC changes the cluster head selection probability in an efficient and dynamic manner. Simulation results validate and confirm the performance supremacy of EDDEEC compared to existing schemes in terms of various metrics such as network life. [ABSTRACT FROM AUTHOR]

There are a number of challenges caused by the large amount of data and limited resources such as memory, processing capability, energy consumption, and bandwidth, when implementing vision systems on wireless smart cameras using embedded platforms. It is usual for research in this field to focus on the development of a specific solution for a particular problem. There is a requirement for a tool which facilitates the complexity estimation and comparison of wireless smart camera systems in order to develop efficient generic solutions. To develop such a tool, we have presented, in this paper, a complexity model by using a system taxonomy. In this model, we have investigated the arithmetic complexity and memory requirements of vision functions with the help of system taxonomy. To demonstrate the use of the proposed model, a number of actual systems are analyzed in a case study. The complexity model, together with system taxonomy, is used for the complexity estimation of vision functions and for a comparison of vision systems. After comparison, the systems are evaluated for implementation on a single generic architecture. The proposed approach will assist researchers in benchmarking and will assist in proposing efficient generic solutions for the same class of problems with reduced design and development costs. [ABSTRACT FROM AUTHOR]

A Wireless Visual Sensor Network (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. After acquiring an image of the area of interest, the VSN performs local processing on it and transmits the result using an embedded wireless transceiver. Wireless data transmission consumes a great deal of energy, where energy consumption is mainly dependent on the amount of information being transmitted. The image captured by the VSN contains a huge amount of data. For certain applications, segmentation can be performed on the captured images. The amount of information in the segmented images can be reduced by applying efficient bi-level image compression methods. In this way, the communication energy consumption of each of the VSNs can be reduced. However, the data reduction capability of bi-level image compression standards is fixed and is limited by the used compression algorithm. For applications attributing few changes in adjacent frames, change coding can be applied for further data reduction. Detecting and compressing only the Regions of Interest (ROIs) in the change frame is another possibility for further data reduction. In a communication system, where both the sender and the receiver know the employed compression standard, there is a possibility for further data reduction by not including the header information in the compressed bit stream of the sender. This paper summarizes different information reduction techniques such as image coding, change coding and ROI coding. The main contribution is the investigation of the combined effect of all these coding methods and their application to a few representative real life applications. This paper is intended to be a resource for researchers interested in techniques for information reduction in energy constrained embedded applications. [ABSTRACT FROM AUTHOR]

Wireless vision sensor networks (WVSNs) have a number of wireless vision sensor nodes (VSNs), often spread over a large geographical area. Each node has an image capturing unit, a battery or alternative energy source, a memory unit, a light source, a wireless link, and a processing unit. The challenges associated with WVSNs include low energy consumption, low bandwidth, limited memory, and processing capabilities. In order to meet these challenges, our paper is focused on the exploration of energy-efficient reconfigurable architectures for VSN. In this paper, the design and research challenges associated with the implementation of VSN on different computational platforms, such as microcontroller, field-programmable gate arrays, and server, are explored. In relation to this, the effect on the energy consumption and the design complexity at the node, when the functionality is moved from one platform to another, are analyzed. Based on the implementation of the VSN on embedded platforms, the lifetime of the VSN is predicted using the measured energy values of the platforms for different implementation strategies. The implementation results show that an architecture, where the compressed images after pixel-based operation are transmitted, realize a WVSN system with low energy consumption. Moreover, the complex postprocessing tasks are moved to a server which has less constraints. [ABSTRACT FROM AUTHOR]

In this paper, we extend the well-known model for the Gaussian Cellular Multiple Access Channel originally presented by Wyner. The first extension to the model incorporates the distance-dependent path loss (maintaining a close relevance to path loss values in real world cellular systems) experienced by the users distributed in a planar cellular array. The density of base stations and hence the cell sizes are variable. In the context of a Hyper-receiver joint decoder, an expression for the information theoretic capacity is obtained assuming a large number of users in each cell. The model is further extended to incorporate the log-normal shadow fading variations, ensuring that the shadowing models are fairly comparable to the free space model. Using these fair models the effect of the shadow fading standard deviation on the information theoretic capacity of the cellular system is quantified. It is observed that a higher standard deviation results in lower capacity if the mean path loss is appropriately adjusted in order to model the mean loss due to the physical obstacles causing the shadow fading. The results validate that larger cell sizes and a higher standard deviation of shadowing (with appropriately adjusted mean path loss) results in lower spectral efficiency. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) and its applications in industrial settings are set to bring in the fourth industrial revolution. The industrial environment consisting of high profile manufacturing plants and a variety of equipment is inherently characterized by high reflectiveness, causing significant multi-path components that affect the propagation of wireless communications—a challenge among others that needs to be resolved. This paper provides a detailed insight into Narrow-Band IoT (NB-IoT), Industrial IoT (IIoT), and Wireless Sensor Networks (WSN) within the context of indoor industrial environments. It presents the applications of NB-IoT for industrial settings, such as the challenges associated with these applications. Furthermore, future research directions were put forth in the areas of NB-IoT network management using self-organizing network (SON) technology, edge computing for scalability enhancement, security in NB-IoT generated data, and proposing a suitable propagation model for reliable wireless communications. [ABSTRACT FROM AUTHOR]

The rapid advancements in wireless communications are expected to increase the demand for radio spectrum resources by orders of magnitude during the next decade. This problem must be addressed using technology and regulatory innovations for significant improvements in spectrum utilization in cellular networks. Emerging cognitive radio technology has been identified as a high-impact disruptive innovation that could provide solutions to the cellular traffic congestion problems and exploit the underutilized spectral resources to pave an application-driven path toward the next generation of cellular technology. [ABSTRACT FROM PUBLISHER]

As the idea of a new wireless communication standard (5G) started to circulate around the world, there was much speculation regarding its performance, making it necessary to carry out further research by keeping in view the challenges presented by it. 5G is considered a multi-system support network due to its ability to provide benefits to vertical industries. Due to the wide range of devices and applications, it is essential to provide support for massively interconnected devices. Network slicing has emerged as the key technology to meet the requirements of the communications network. In this paper, we present a review of the latest achievements of 5G network slicing by comparing the architecture of The Next Generation Mobile Network Alliance's (NGMN's) and 5G-PPP, using the enabling technologies software-defined networking (SDN) and network function virtualization (NFV). We then review and discuss machine learning (ML) techniques and their integration with network slicing for beyond 5G networks and elaborate on how ML techniques can be useful for mobility prediction and resource management. Lastly, we propose the use case of network slicing based on ML techniques in a smart seaport environment, which will help to manage the resources more efficiently. [ABSTRACT FROM AUTHOR]

The increasing needs of free licensed frequency bands like Industrial, Scientific, and Medical (ISM), Wireless Local Area Network (WLAN), and 5G for underwater communications required more bandwidth (BW) with higher data transferring rate. Microwaves produce a higher transferring rate of data, and their associated devices are smaller in comparison with sonar and ultrasonic. Thus, transceivers should have broad BW to cover more of a frequency band, especially from ultra-wideband (UWB) systems, which show potential outcomes. However, previous designs of similar work for underwater communications were very complicated, uneasy to fabricate, and large. Therefore, to overcome these shortcomings, a novel compact elliptical UWB antenna is designed to resonate from 1.3 to 7.2 GHz. It is invented from a polytetrafluoroethylene (PTFE) layer with a dielectric constant of 2.55 mm and a thickness of 0.8 mm. The proposed antenna shows higher gain and radiation efficiency and stability throughout the working band when compared to recent similarly reported designs, even at a smaller size. The characteristics of the functioning antenna are investigated through fluid mediums of fresh-water, seawater, distilled water, and Debye model water. Later, its channel capacity, bit rate error, and data rate are evaluated. The results demonstrated that the antenna offers compact, easier fabrication with better UWB characteristics for underwater 5G communications. [ABSTRACT FROM AUTHOR]

The articles in this special section focuses on the deployment of mobile and wireless technologies and services in smart cities. [ABSTRACT FROM PUBLISHER]

This work presents penta-notched UWB antenna with sharp frequency edge selectivity using combination of SRR, CSRR, and DGS to reject the WiMAX (3.30–3.60 GHz), lower WLAN (5.150–5.350 GHz), upper WLAN (5.725–5.825 GHz), downlink of X-band satellite communication (7.0–7.40 GHz), and the uplink of X-band satellite communication (8.10–8.50 GHz) frequency bands. All these frequency bands lie within the UWB frequency spectrum. The proposed antenna is suitable for portable communication applications due to its compact dimensions. It sharply notches the existing frequency bands to mitigate the interference caused by nearby wireless communication systems within UWB frequency range. The sharp notching is achieved by the combination of complementary split ring resonators (CSRR) on the radiating semi-circular patch, split ring resonators (SRR) placed at the junction of the feedline, and a pair of defected ground structures (DGS). All notched bands can be well controlled and shifted and the equivalent lumped model of the notched bands are also developed for validation. The proposed antenna simulated, and measured results show better performance over the present state-of-the-art designs. The proposed penta-notched UWB antenna possesses better reflection coefficient, VSWR, stable gain, and small foot print. The proposed antenna has a nearly omnidirectional radiation pattern in the passbands. [ABSTRACT FROM AUTHOR]

In this paper, we propose novel Hybrid Automatic Repeat re-Quest (HARQ) strategies used in conjunction with hybrid relaying schemes, named as H^2-ARQ-Relaying. The strategies allow the relay to dynamically switch between amplify-and-forward/compress-and-forward and decode-and-forward schemes according to its decoding status. The performance analysis is conducted from both the spectrum and energy efficiency perspectives. The spectrum efficiency of the proposed strategies, in terms of the maximum throughput, is significantly improved compared with their non-hybrid counterparts under the same constraints. The consumed energy per bit is optimized by manipulating the node activation time, the transmission energy and the power allocation between the source and the relay. The circuitry energy consumption of all involved nodes is taken into consideration. Numerical results shed light on how and when the energy efficiency can be improved in cooperative HARQ. For instance, cooperative HARQ is shown to be energy efficient in long distance transmission only. Furthermore, we consider the fact that the compress-and-forward scheme requires instantaneous signal to noise ratios of all three constituent links. However, this requirement can be impractical in some cases. In this regard, we introduce an improved strategy where only partial and affordable channel state information feedback is needed. [ABSTRACT FROM PUBLISHER]

Abstract: Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes. [Copyright &y& Elsevier]

Wireless Body Area Networks (WBANs) are envisaged to play crucial role in psychological, medical and non-medical applications. This paper presents iM-SIMPLE; a reliable, and power efficient routing protocol with high throughput for WBAN. We deploy sensor nodes on human body to measure the physiological parameters such as blood pressure, temperature, glucose, lactic acid, EMG, acceleration, pressure, and position. Data from sensors is forwarded to intermediate node, from where it is transmitted to sink. An end user can access the required information available at sink via internet. To minimize energy consumption of the network, we utilize multi-hop mode of communication. A cost function is introduced to select the forwarder; node with high residual energy and least distance to sink has minimum cost function value and is selected. Residual energy parameter balances the energy consumption among the sensor nodes, and least distance improves packet delivery to sink because of reduced less path loss. We formulate the minimum energy consumption and high throughput problems as an Integer Linear Program. In order to support mobility, we also consider two body postures. Simulation results confirm the performance advantage of iM-SIMPLE compared to contemporary schemes in terms of maximizing stability period and throughput of the network. [ABSTRACT FROM AUTHOR]

• Security of ultra-reliable low latency communications. • Eavesdropping behaviors in 5G and beyond communications. • Friendly jamming schemes to protect 5G and beyond communications. The security vulnerabilities are becoming the major obstacle to prevent the wide adoption of ultra-reliable and low latency communications (URLLC) in 5G and beyond communications. Current security countermeasures based on cryptographic algorithms have a stringent requirement on the centralized key management as well as computational capabilities of end devices while it may not be feasible for URLLC in 5G and beyond communications. In contrast to cryptographic approaches, friendly jamming (FJ) as a promising physical layer security method can enhance wireless communications security while it has less resource requirement on end devices and it can be applied to the full distribution environment. In order to protect wireless communications, FJ signals are introduced to degrade the decoding ability of eavesdroppers who maliciously wiretap confidential information. This article presents a state-of-the-art survey on FJ schemes to enhance network security for IoT networks with consideration of various emerging wireless technologies and different types of networks. First, we present various secrecy performance metrics and introduce the FJ method. The interference caused by FJ signals on legitimate communication is the major challenge of using FJ schemes. In order to overcome this challenge, we next introduce the integration of FJ schemes with various communication technologies, including beamforming, multiple-input multiple-output, full duplex, and relay selection. In addition, we also integrate FJ schemes with different types of communication networks. Finally, a case study of FJ schemes is illustrated and future research directions of FJ schemes have been outlined. [ABSTRACT FROM AUTHOR]