Accurate and low-latency positioning is a key enabler for optical links with Low Earth Orbit (LEO) satellites, where millisecond-level beam alignment is required to maintain reliable high-data-rate communication. This paper presents a learning-driven dual-line laser scanning framework for fast and precise satellite positioning. Unlike conventional Gaussian-beam acquisition systems that rely on multiple sequential beams or mechanical steering, the proposed approach employs two orthogonal line-shaped laser beams to perform structured optical scanning over the ambiguity region without any moving parts. A physics-based model incorporating atmospheric attenuation, turbulence, and MRR-based reflection is developed, and a data-driven neural estimator is trained to map received optical energy patterns to the satellite's two-dimensional position. Simulation results demonstrate that the learning-driven method achieves near-MAP accuracy with typical errors of 7-10 m and deterministic scanning time of 1-2 ms, while conventional two-stage Gaussian-beam schemes exhibit comparable errors but random sensing durations of up to 5 ms. The proposed framework therefore offers a favorable trade-off between positioning accuracy, computational complexity, and sensing latency, making it a practical candidate for next-generation optical LEO tracking systems.

High-speed vehicular environments require optical systems capable of joint sensing, positioning, and communication (JSPC) without mechanical tracking. Existing optical and integrated sensing-communication approaches often rely on point-source emitters or camera-based receivers, limiting spatial coverage and update rate under highway dynamics. This work introduces a new class of tracking-free optical JSPC systems that combine structured line-laser illumination with modulating retroreflector (MRR) arrays on vehicles. Two orthogonal line lasers perform synchronized longitudinal and transverse scanning to provide continuous, wide-area coverage across the roadway. A coverage-driven analytical framework models the coupling between beam divergence, scan geometry, and dwell-time allocation, enabling joint evaluation of sensing reliability and communication quality. An optimization scheme is developed to adapt scanning and divergence parameters for uniform coverage and power efficiency. Simulation results demonstrate significant improvements in spatial coverage uniformity, link stability, and reliability within a fixed scan period. These results establish a practical pathway toward scalable, turbulence-resilient optical architectures for next-generation vehicular JSPC networks.

Accurate characterization of free-space optical (FSO) channels requires joint estimation of transmitter pointing errors, receiver angle-of-arrival (AoA) fluctuations, and turbulence-induced fading. However, existing literature addresses these impairments in isolation, since their multiplicative coupling in the received signal severely limits conventional estimators and prevents simultaneous recovery. In this paper, we introduce a novel multi-aperture FSO receiver architecture that leverages spatial diversity across a lens array to decouple these intertwined effects. Building on this hardware design, we propose a hierarchical deep learning framework that sequentially estimates AoA, transmitter pointing error, and turbulence coefficients. This decomposition significantly reduces learning complexity and enables robust inference even under strong atmospheric fading. Simulation results demonstrate that the proposed method achieves near-MAP accuracy with orders-of-magnitude lower computational cost, and substantially outperforms end-to-end learning baselines in terms of estimation accuracy and generalization. To the best of our knowledge, this is the first work to demonstrate practical joint estimation of these three key parameters, paving the way for reliable, turbulence-resilient multi-aperture FSO systems.

In this paper, we investigate the performance of wireless-powered communication (WPC) systems operating under the harvest-then-transmit protocol with a three-piecewise nonlinear energy harvesting (EH) model, which explicitly captures the sensitivity and saturation behavior of practical EH circuits. In parallel, we adopt a versatile fading characterization by assuming Nakagami-mchannels in the EH phase and generalized Gamma channels in the information transfer phase, the latter being of practical interest as it unifies several standard fading distributions and accurately approximates fading environments in next-generation networks. Based on this setting, we develop a novel analytical framework that yields, for the first time, exact analytical expressions for the average throughput in the delay-limited, delay-tolerant, and Quality of Service (QoS) delay-constrained transmission modes. We then apply the developed framework to study the throughput of WPC-enabled reconfigurable intelligent surface-assisted systems as a direct application example. We conduct extensive Monte-Carlo simulations under various system configurations to confirm the accuracy of the analytical results. Our results show that nonlinear EH effects yield a more realistic benchmark for the average throughput compared to the conventional linear EH model, particularly under stringent sensitivity and saturation constraints.

This paper investigates a movable-antenna-assisted dual-hop space-air-ground non-terrestrial network (NTN) operating under an underlay spectrum sharing paradigm. A satellite communicates with multiple unmanned aerial vehicles (UAVs) over free-space optical (FSO) links, while each UAV simultaneously serves a cluster of ground users over radio-frequency (RF) channels subject to interference constraints imposed by a primary receiver. To efficiently exploit the complementary advantages of FSO and RF transmission and the additional spatial degrees of freedom offered by movable antennas, a joint optimization framework is developed to maximize the system sum rate. The proposed framework jointly optimizes satellite and UAV power allocation, multi-antenna precoding at the UAVs, and the positions of multiple movable antennas mounted on each UAV. An alternating-optimization algorithm is employed, where minimum mean square error (MMSE) based precoding accounts for both communication and interference channels, power allocation is convexified using auxiliary rate variables and successive convex approximation, and antenna locations are optimized via Taylor-based convex surrogates. Simulation results demonstrate that the proposed approach significantly outperforms benchmark schemes with fixed antenna locations, heuristic optimization and reinforcement learning methods, while providing robust performance across different system parameters.

This paper presents an efficient analytical framework for evaluating the performance of inter-satellite communication systems utilizing orbital angular momentum (OAM) beams under pointing errors. An accurate analytical model is first developed to characterize intermodal crosstalk caused by beam misalignment in OAM-based inter-satellite links. Building upon this model, we derive efficient expressions to analyze and optimize system performance in terms of bit error rate (BER). Unlike traditional Monte Carlo-based methods that are computationally intensive, the proposed approach offers accurate performance predictions. This enables a substantial decrease in computation time while maintaining high accuracy, thanks to the use of analytical expressions for both crosstalk and BER. This fast and accurate evaluation capability is particularly critical for dynamic low Earth orbit (LEO) satellite constellations, where network topology and channel conditions change rapidly, requiring real-time link adaptation. Furthermore, we systematically design and evaluate asymmetric OAM mode sets, which significantly outperform symmetric configurations in the presence of pointing errors. Our results also reveal key insights into the interaction between beam divergence, tracking accuracy, and link distance, demonstrating that the proposed framework enables real-time optimization of system parameters with high fidelity. The analytical findings are rigorously validated against extensive Monte Carlo simulations, confirming their practical applicability for high-mobility optical wireless systems such as LEO satellite networks.

Non-terrestrial networks (NTNs) using unmanned aerial vehicles (UAVs) as temporary base stations enable flexible coverage in disaster-stricken areas and congested regions. This paper presents a beamforming design for rate splitting multiple access (RSMA) enabled UAV underlay networks that addresses untrusted users (potential eavesdroppers), enforces max–min fairness in achievable user rates, accommodates imperfect CSI, and limits interference to a licensed primary receiver. We transform the non-convex optimization problem via auxiliary-variable-based reformulation and successive convex approximation (SCA), obtaining a tractable convex semi-definite program (SDP). Simulations demonstrate that the proposed framework achieves perfect rate fairness (Jain’s fairness index = 1.0) across all users while delivering robust sum-rate performance under varying numbers of users, UAV transmit antennas, and secrecy requirements.

Due to the expected exploitation of high frequency bands to meet increasing demands on high data rates, multi-hop links are being under investigation as a solution for limited transmission distances over these bands. As such, many of recent transmission schemes are analyzed over multi-hop scenarios. To this end, in this paper, we design a dual-hop system of Index Modulation based Orthogonal Frequency Division Multiple Access (IM-OFDMA) with the help of decode-and-forward relays. Two different scenarios are considered, with single and multiple DF relays. Moreover, the average error rate is analyzed for the proposed system considering the two different scenarios. Our results indicate that the overall performance in the case of a single DF relay is governed by the performance of the second hop. Also, results reveal that a significant gain can be attained if a single relay is assigned to each user rather than one relay for all users.

This paper investigates the performance of satellite-based quantum key distribution (QKD) under realistic channel conditions, emphasizing the adverse effects of photon loss introduced by pointing errors and the presence of background photons. By leveraging a stochastic framework, we model the probability distribution of the number of photons detected at the receiver, considering Gaussian beam propagation, finite receiver aperture, and Poisson-distributed background noise. We then evaluate essential QKD performance metrics—such as the quantum key rate, quantum bit error rate (QBER), and outage probability—across a wide range of beam waist sizes and tracking accuracies. Numerical simulations demonstrate how subtle increases in the pointing error variance can drastically reduce the secure key generation rate, particularly for tightly focused beams. These findings highlight the importance of precise pointing systems and careful selection of optical parameters to ensure an acceptable QBER and a sufficiently high secret key rate in inter-satellite QKD links.

High peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) signals presents a persistent challenge in satellite communications (SatCom), impacting signal quality and causing adjacent channel interference. This paper introduces a novel framework that combines the elastic net-based machine learning (ML) model with the partial transmit sequence (PTS) technique to effectively reduce PAPR. Additionally, the potential of artificial intelligence (AI) approaches are investigated, specifically swarm intelligence and ML methods, for high-performance, low-complexity solutions. In this regard, ML models are applied to mitigate PAPR in SatCom networks under the presence of a traveling wave tube amplifier (TWTA) model and a land mobile satellite (LMS) channel, employing 16-quadrature amplitude modulation (16-QAM). Compared with the baseline schemes, simulation results demonstrate that the proposed ML framework, integrating principal component analysis (PCA) with the elastic net learning model, achieves comparable PAPR performance and minimal computational complexity.

The next generation of wireless communication networks must offer robust connectivity to serve users in remote or disaster-stricken regions where terrestrial infrastructure is unavailable or compromised. High-altitude platforms (HAPs), functioning as non-terrestrial network (NTN) nodes, can rapidly restore coverage and extend service reach by transmitting directly to ground users. To further enhance communication performance, simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) can be deployed alongside HAPs, intelligently shaping the wireless channel to improve channel reliability. In this work, we investigate a HAP-assisted NTN in which a STAR-RIS aids downlink transmission to multiple ground users under a rate-splitting multiple access (RSMA) protocol with imperfect successive interference cancellation (SIC). The joint design of power allocation at the HAP and STAR-RIS beamforming presents a challenging non-convex problem because of the coupled rate expressions and rank-one constraints on the STAR-RIS matrices. To address this, we introduce auxiliary variables and apply successive convex approximation (SCA) to convexify rate functions, while employing a difference-of-convex (DC) programming approach to handle the rank-one requirement. An alternating optimization framework is then developed to iteratively solve a convex power allocation subproblem and a penalized semi-definite program for STAR-RIS beamforming. Simulation results show the efficacy of the proposed framework, showing excellent performance even under imperfect SIC and with discretized phase shifts at the STAR-RIS.

This paper addresses the challenge of optimizing user grouping in Index Modulation-based Orthogonal Frequency-Division Multiple Access (IM-OFDMA) systems within dynamic and stochastic noise environments. Utilizing the eXtreme Gradient Boosting (XGBoost) machine learning algorithm, we devised a framework capable of accurately predicting the optimality of user groupings across varying Signal-to-Noise Ratio (SNR) levels. Six models corresponding to different noise conditions were created, showcasing adaptability to adjacent noise levels via distribution shift handling, thereby ensuring robust performance across a wide noise spectrum. To accurately identify the most appropriate optimality prediction model for dynamic environments, we introduced a specialized model for precisely estimating the system’s internal noise power. The accuracy of this model is crucial for the selection process and was significantly enhanced by implementing sequential Bayesian updating, facilitating a more precise estimation of internal noise power. Following this, we introduced a provisional optimization algorithm designed to refine user groupings within dynamic IM-OFDMA systems. Simulation results highlight the algorithm’s effectiveness in markedly improving system performance, evidenced by a significant decrease in bitrate errors. These findings illuminate the significant potential of applying machine learning strategies to wireless communication systems, providing insightful contributions to the enhancement of IM-OFDMA systems in practical settings.

This paper focuses on the optimal design of a modulated retroreflector (MRR) laser link to establish a high-speed downlink for cube satellites (CubeSats), taking into account the weight and power limitations commonly encountered by these tiny satellites. To this end, first, a comprehensive channel modeling is conducted considering key real channel parameters including mechanical gimbal error, fast steering mirror angle error, laser beamwidth, MRR area, atmospheric turbulence, and channel coherence time. Accordingly, a closed-form expression for the distribution of the received signal is derived and utilized to propose a maximum likelihood based method to sense and estimate the initial position of the satellite. Subsequently, the distribution of the distance estimation error during the sensing phase is formulated as a function of the laser beamwidth and the gimbal error, which enables us to fine-tune the optimal laser beamwidth to minimize sensing time. Moreover, using the sensing and initial satellite distance estimation, two positioning algorithms are proposed. To compare the performance of the proposed positioning method, we obtain the lower bound of the positioning error as a benchmark. Finally, by providing comprehensive simulations, we evaluate the effect of different parameters on the performance of the considered MRR-based system in both the sensing and positioning phases.

Given the growing significance of CubeSats for real-time Earth monitoring and space networking, there is an increasing demand for high-speed links for CubeSats facing constraints related to the weight, dimensions, and power consumption of telecommunication equipment. This article addresses such a need by designing a modulating retroreflector (MRR)-based optical downlink system tailored for fast-moving CubeSats, highlighting joint tracking and communication operations using a single transmitter for high data rates. Key contributions encompass precise system characterization, the design of a dual-transmitter system to maximize channel capacity, derivation of channel capacity as a function of 2M + 4 random variables, and the development of an MRR-based CubeSat downlink system. Subsequently, leveraging the obtained analysis and results, we design a system with a single transmitter, enabling simultaneous tracking and communication operations through optimal adjustments of beam timing and placement in the satellite’s vicinity. Pertinent analyses demonstrate optimal laser beam adjustments to achieve maximum capacity while maintaining tracking accuracy. Monte Carlo simulations are used to validate a closed-form expression for efficient optimization of system parameters. Comprehensive simulations assess the effect of different parameters, offering crucial insights for optimal system design.

Low Earth orbit (LEO) satellite constellations are emerging as a key enabler of next-generation communications, offering global coverage and significantly lower latency compared to traditional terrestrial networks and geostationary satellites. However, further latency reduction is essential for time-critical applications such as real-time sensing, autonomous systems, and interactive services. One critical bottleneck is the optical-to-electrical (O/E) and electrical-to-optical (E/O) conversions at intermediate nodes in multi-hop links, which introduce unwanted processing delays. To address this, we investigate an all-optical relay system based on Optical Hard Limiters (OHL), which operate purely in the optical domain to suppress noise and restore signal quality without requiring O/E conversions. First, we present a rigorous analysis of inter-satellite multi-relay communication under the OHL relaying architecture, comparing it against conventional Amplify-and-Forward (AF) and Decode-and-Forward (DF) schemes. Through this comparison, we highlight both the advantages and limitations of OHL relays, including their particular sensitivity to parameter choices such as the threshold setting and divergence angle at the transmitter. Recognizing that a LEO constellation is inherently time-varying—satellites move relative to one another, causing continuous changes in link distances and tracking errors—we propose a joint optimization strategy. This scheme adaptively tunes the OHL decision threshold and beam divergence in real time to maintain optimal performance, ultimately lowering error rates and latency. Extensive simulations in a large-scale LEO network demonstrate the viability of our method and offer insights into practical implementation for next-generation inter-satellite communication systems.

Terahertz (THz) band is widely nominated to be exploited in next wireless networks to meet the high demand on data rates. However, unlike lower frequency bands, several challenges come up while designing a transmission system over the THz band. Among these challenges is the hardware impairments at the transmitter front-end. It is well known that hardware impairments limit the error performance of any transmission system, where a lower bound on the error rate is usually noticed. Such an impact becomes more severe as the operating frequency increases, which significantly degrades the transmission over THz band. To this end, this paper proposes an adaptive modulation scheme that is able to overcome this problem. Moreover, the optimal detector for the proposed adaptive modulation scheme is presented. Mathematical modeling and analysis of the performance of the conventional QAM and the proposed modulation scheme are included along with simulation results that verify the analytical findings. Results indicate that the error performance of the proposed scheme is much better than conventional QAM where no error floor is noticed.

Involving Unmanned Aerial Vehicles (UAVs) in wire-less networks has been widely investigated in the literature considering different scenarios such as emergency scenarios in which UAV(s) can play a significant role by compensating the damaged/lost network's components. For example, Sensor Networks (SNs) in emergency scenarios may lose some sensor nodes or the Central Entity (CE) itself, which requires fast, prompt and efficient alternative to replace them. Therefore, UAVs are widely nominated to such a role due to their flexibility and maneuverability. However, compared to ground-based entities, UAVs suffer from the continuous position fluctuations, which directly affects the antenna's orientation. Such an effect becomes a serious challenge in high frequency links such as millimeter wave (mmWave) links which are very sensitive to antennas misalignment. In this paper, the performance of UAV-based SNs is addressed by analyzing the impact of UAV's vibration on the performance metrics including detection and false-alarm probabilities. To this end, two network models are adopted, namely, Ground-based Hybrid SN (G-HSN) and Aerial-based Hybrid SN (A-HSN), depending on whether the CE is ground or aerial node. A mathematical framework is followed to express performance metrics in closed form expressions considering practical conditions including channel fading, orientation fluctuations of directional mmWave antennas and path loss. Simulation results validate the accuracy of the derived mathematical expressions and depict the impact of different operational parameters.

This paper presents a novel approach for joint Terahertz (THz) communication and three-dimensional (3D) map reconstruction using an Unmanned Aerial Vehicle (UAV). Due to the need for precise mapping to provide Line-of-Sight (LoS) THz communication services, our approach leverages the UAV's trajectory to initiate the reconstruction and updating of the 3D environment in real-time. The UAV starts without any prior knowledge of the target area, establishing THz communications with users scattered among 3D obstacles. A comprehensive system model is developed, incorporating realistic antenna patterns, UAV oscillations, and received signal power modeling for accurate analysis. We establish an adaptive methodology for 3D environment modeling, dynamically constructing and refining a grid-based obstacle map. A dynamic algorithm for real-time 3D map reconstruction is implemented, utilizing received signal strengths to update the environmental model. Detailed simulations validate the effectiveness of our proposed methods, demonstrating significant improvements in computational efficiency and real-time decision-making in UAV-assisted communication networks. Our results highlight the potential of this joint approach in enhancing operational efficiency and communication reliability under varying environmental conditions.

Index Modulation Orthogonal Frequency Division Multiple Access (IM-OFDMA) is a spectral-efficient uplink multiple access scheme that has been recently proposed. IM-OFDMA relies on the index modulation concept and allows for multiple users to simultaneously share the same spectrum resources. It has been demonstrated that IM-OFDMA outperforms its conventional and recent counterparts in terms of the error performance and the number of served users. However, as IM-OFDMA employs a joint maximum likelihood detection to decode the received signals, it suffers from the computational complexity required at the receiver. The computational complexity becomes serious challenge especially at a large number of users, a large number of frequency subcarriers or a high modulation order. Therefore, this paper aims to reduce the computational complexity of the detection process in IM-OFDMA systems by employing the Successive Interference Cancellation (SIC) detection method. Specifically, the implementation of SIC in IM-OFDMA is in detail described, followed by the analysis of the error performance and the reduction of the computational complexity. Our results reveal that the SIC detector can reduce the computational complexity with a significant percentage as compared to the maximum likelihood detection. Also, the results show that the impact on the error performance is minimal if the served users in each frequency chunk are carefully selected.

Exploiting the high-frequency bands, such as millimeter wave band (mmWave), has become a pressing need due to the increasing demand on the high data rates. However, two main challenges are still hindering the usage of mmWave band, which are represented by the short transmission distance and strict Line-of-Sight (LoS) requirements. To this end, relaying schemes have been widely nominated to address these two challenges, where the transmission distance can be extended and the LoS can be attained by the aid of a well-positioned relay. One of the promising spectral-efficient relaying schemes is the well known Two-Way Relaying (TWR). In this paper, the performance of the TWR scheme is investigated for aerial links operating over the mmWave band. Specifically, the bit error rate (BER) is analyzed for a dual-hop system in which source, relay and destination are represented by hovering unmanned aerial vehicles. A closed form expression of the average BER is derived considering the impact of the antennas' fluctuations, modulation order, transmission distance, beamwidth, path loss and channel fading. Simulation results are explored to investigate the impact of all operational parameters.

Cardiac arrhythmia is one of the prime reasons for death globally. Early diagnosis of heart arrhythmia is crucial to provide timely medical treatment. Heart arrhythmias are diagnosed by analyzing the electrocardiogram (ECG) of patients. Manual analysis of ECG is time-consuming and challenging. Hence, effective automated detection of heart arrhythmias is important to produce reliable results. Different deep-learning techniques to detect heart arrhythmias such as Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Transformer, and Hybrid CNN-LSTM were proposed. However, these techniques, when used individually, are not sufficient to effectively learn multiple features from the ECG signal. The fusion of CNN and LSTM overcomes the limitations of CNN in the existing studies as CNN-LSTM hybrids can extract spatiotemporal features. However, LSTMs suffer from long-range dependency issues due to which certain features may be ignored. Hence, to compensate for the drawbacks of the existing models, this paper proposes a more comprehensive feature fusion technique by merging CNN, LSTM, and Transformer models. The fusion of these models facilitates learning spatial, temporal, and long-range dependency features, hence, helping to capture different attributes of the ECG signal. These features are subsequently passed to a majority voting classifier equipped with three traditional base learners. The traditional learners are enriched with deep features instead of handcrafted features. Experiments are performed on the MIT-BIH arrhythmias database and the model performance is compared with that of the state-of-art models. Results reveal that the proposed model performs better than the existing models yielding an accuracy of 99.56%.

The terahertz (THz) band radio access with larger available bandwidth is anticipated to provide higher capacities for next-generation wireless communication systems. However, higher path loss at THz frequencies significantly limits the wireless communication range. Massive multiple-input multiple-output (mMIMO) is an attractive technology to increase the Rayleigh distance by generating higher gain beams using low wavelength and highly directive antenna array aperture. In addition, both far-field and near-field components of the antenna system should be considered for modeling THz electromagnetic propagation, where the channel estimation for this environment becomes a challenging task. This paper proposes a novel channel estimation method using a real image denoising network (RIDNet) and orthogonal matching pursuit (OMP) for hybrid-field THz mMIMO channels, including far-field and near-field constituents. The simulation experiments are performed using the ray-tracing tool. The results demonstrate that the proposed RIDNet-based method consistently provides lower channel estimation errors than the conventional OMP algorithm for all signal-to-noise ratio (SNR) regions. The performance gap becomes higher at low SNR regimes. Furthermore, the results imply that the same error performance of the OMP can be achieved by the RIDNet-based method using a lower number of RF chains and pilot symbols.

The estimation of millimeter-wave (mmWave) massive multiple input multiple output (MIMO) channels becomes compelling when one-bit analog-to-digital converters (ADCs) are utilized. Furthermore, as the number of antenna increases, pilot overhead scales up to provide consistent channel estimation, eventually degrading spectral efficiency. This study presents a channel estimation approach that combines a conditional generative adversarial network (cGAN) with a novel blind denoising network with a sparse feature attention mechanism. Performance analysis and simulations show that using a cGAN fused with a feature attention-based denoising neural network significantly enhances the channel estimation performance while requiring less pilot transmission.

Automatic modulation classification (AMC) facilitates adaptive modulation schemes, leading to the minimization of pilot signals, thus affecting spectral efficiency and reducing the power consumption in wireless communications systems. Since high-frequency heterogeneous and adaptive networks are established as future projections, AMC will also play a critical role in the millimeter-wave (mmWave) band communications. This study proposes multi-channel convolutional long short-term deep neural network (MCLDNN) model for AMC in mmWave bands. The performance of the proposed method is evaluated under real conditions based on a measurement campaign. 802.11ad signals are utilized for the measurements in 57.24 GHz to 59.40 GHz band. The classification performance of the proposed model is compared with that of well-known deep-learning methods, i.e., convolutional neural network and convolutional long short-term deep neural network. The measurement results imply the robustness of the proposed method to real-life conditions and its superiority against contemporary networks, especially in low signal-to-noise ratio (SNR) region.

In this paper, we investigate the average bit error probability (ABEP) performance of a relaying radio- frequency/free-space optic (RF/FSO) coded and uncoded communication system employing an energy harvesting-based fixed gain amplify-and-forward (AF) relay. Along with maximal-ratio combining (MRC) at both nodes, the convolutional self orthogonal codes and majority logic decoding method (MLGD) are explicitly examined at the source and destination, respectively. In addition, the source-relay channel experiences i.n.i.d. Nakagami-m fading, while the relay-destination link is modeled by Málaga-$\mathcal{M}$ fading with the effect of pointing errors taking into account many apertures at the destination. Due to the significant coding benefits that these codes offer, the results of the Monte Carlo simulation proved that the proposed decoding technique is adequate for such communication.

Twelve lead electrocardiogram signals capture unique fingerprints about the body's biological processes and electrical activity of heart muscles. Machine learning and deep learning-based models can learn the embedded patterns in the electrocardiogram to estimate complex metrics such as age and gender that depend on multiple aspects of human physiology. ECG estimated age with respect to the chronological age reflects the overall well-being of the cardiovascular system, with significant positive deviations indicating an aged cardiovascular system and a higher likelihood of cardiovascular mortality. Several conventional, machine learning, and deep learning-based methods have been proposed to estimate age from electronic health records, health surveys, and ECG data. This manuscript comprehensively reviews the methodologies proposed for ECG-based age and gender estimation over the last decade. Specifically, the review highlights that elevated ECG age is associated with atherosclerotic cardiovascular disease, abnormal peripheral endothelial dysfunction, and high mortality, among many other cardiovascular disorders. Furthermore, the survey presents overarching observations and insights across methods for age and gender estimation. This paper also presents several essential methodological improvements and clinical applications of ECG-estimated age and gender to encourage further improvements of the state-of-the-art methodologies.

We propose a fixed-wing unmanned aerial vehicles (UAV)-based millimeter wave (mmWave) backhaul architecture that is offered as a cost effective and easy to deploy solution, to connect a disaster or remote area to the nearest core network. First, we fully characterize the single relay fixed-wing UAV-based communication system by taking into account the effects of realistic physical parameters, such as the UAV’s circular path, critical points of the flight path, heights and positions of obstacles, flight altitude, tracking error, the severity of UAV’s vibrations, the real 3D antenna pattern, mmWave atmospheric channel loss, temperature and air pressure. Second, we derive the distribution of the signal-to-noise ratio (SNR) metric, which is based on the sum of a series of Dirac delta functions. Using the SNR distribution, we derive analytical expressions for the outage probability and the ergodic capacity of the considered system as a function of all system parameters. To provide an acceptable quality of service for longer link lengths, we extend the analytical expressions to a multi-relay system. The accuracy of the analytical expressions are verified by Monte-Carlo simulations. Finally, by providing sufficient simulation results, we investigate the effects of key channel parameters such as antenna pattern gain and flight path on the performance of the considered system; and we carefully analyze the relationships between those parameters in order to maximize the average channel capacity.

The main contribution of this paper is to analyze a long networked flying platform (NFP)-based millimeter wave (mmWave) backhaul link that is offered as a cost effective and easy to deploy solution to connect a disaster or remote area to the nearest core network. The same network model can be considered for interlinking Low Earth Orbit (LEO) satellite constellations with different geometry and channel characteristics. For this aim, we characterize the backhaul channel as a function of realistic physical parameters such as heights and distances of obstacles along the route, flight altitude and the intensity of NFPs' vibrations, the actual 3D antenna pattern, etc. For the characterized channel, we derive an analytical closed-form expression for the outage probability. Finally, using the obtained results, we provide a fast algorithm for the optimal parameter design of the considered system that minimizes the cost.

Frequency scarcity implies the utilization of higher frequencies for wireless communications; however, spreading loss becomes a dominating issue as the frequency increases to the level of and beyond millimeter waves. To this end, massive multiple-input multiple-output structures introduce mitigation alternatives. However, to make these solutions possible, the channel estimation approach strives to be modified: since Rayleigh distance is very short for conventional systems, the only far-field channel is examined in that context. On the other hand, the implementation of massive antenna arrays in high frequencies increases Rayleigh distance; thus, both near-field and far-field analyses become necessary. Instead of a dual estimation process, it would be effective and efficient to develop hybrid-field channel estimation techniques. Therefore, in this study, a new channel estimation method which is based on convolutional autoencoder (CAE) and orthogonal matching pursuit (OMP) approach, is proposed for hybrid channel estimation. The results indicate that the proposed OMP-CAE method has much better error performance when compared to the conventional OMP algorithm, especially at low signal-to-noise ratio regimes.

Design of simple transceiver architectures is inevitable in order to provide low computational complexity, low power consumption and affordable cost in beyond 5G (B5G) wireless systems, but it results in hardware impairments that significantly degrade the performance reliability of transmission. In this paper, among these hardware impairments, we discuss in-phase and quadrature (IQ) imbalance in orthogonal time frequency space (OTFS), which is a recent waveform considered as a potential candidate for B5G systems to relax the vulnerability against time-variant wireless channels. To mitigate the effect of IQ imbalance for OTFS, we propose an energy and spectral efficient IQ imbalance compensation scheme with the aid of index modulation (IM), which provides an attractive flexibility in the system design. In contrast to conventional solutions used in classical wireless technologies, such as iterative and pilot-based techniques, the proposed scheme avoids additional energy consumption and significant spectral efficient loss during the estimation and compensation of the IQ imbalance effect. The obtained bit error rate (BER) results validate the accuracy of the proposed compensator for different OTFS system configurations considering perfect/imperfect channel state information in practical scenarios.

Impairments baseband model in-phase and quadrature-phase Imbalance (IQI) and Residual hardware impairments (RHI) are two key factors degrading the performance of wireless communication systems (WCSs), particularly when high-frequency bands are employed, as in 5G systems and beyond. The impact of either IQI or RHI on the performance of various WCSs has been investigated exclusively in a separate way. To fill this gap, in this paper, the joint effect of both IQI and RHI on the performance of a WCS subject to Hyper Fox’s H-fading (HFHF) channel, is investigated. Such a fading model generalizes most, if not all, of well-known fading and turbulence models. To this end, closed-form expressions for the outage probability (OP), Average channel capacity (ACC) under constant power with optimum rate adaptation (ORA) policy, and average symbol error probability (ASEP) for both coherent and non-coherent modulation schemes are derived. Specifically, all the analytical expressions are derived for three different scenarios: (i) ideal Tx and Rx impaired, (ii) Tx impaired and ideal Rx, and (iii) both Tx and Rx are impaired. Further, asymptotic expressions for OP, ACC under ORA policy, and ASEP are obtained, based on which, insightful discussions on the IQI and RHI impacts are made.$\alpha -\mu $and Málaga$\mathcal {M}$turbulence with pointing error distribution models have been considered as particular cases of the HFHF distribution. The analytical derivations, endorsed by simulation results, demonstrate that the RF impairments’ effects should be seriously taken into account in the design of next-generation wireless technologies.

The recently proposed index modulation-based up-link orthogonal frequency division multiple access (IM-OFDMA) scheme has outperformed the conventional schemes in terms of spectral efficiency and error performance. However, the induced computational complexity at the receiver forms a bottleneck in real-time implementation due to the joint detection of all users. In this paper, based on deep learning principles, a convolutional neural network (CNN)-based signal detector is proposed for data detection in IM-OFDMA systems instead of the optimum Maximum Likelihood (ML) detector. A CNN-based detector is constructed with the created dataset of the IM-OFDMA transmission by offline training. Then, the convolutional neural network (CNN)-based detector is directly applied to the IM-OFMDA communication scheme to detect the transmitted signal by treating the received signal and channel state information (CSI) as inputs. The proposed CNN-based detector is able to reduce the order of the computational complexity from O(n2n) to O(n2) as compared to the ML detector with a slight impact on the error performance.

Hybrid Free-Space Optical (FSO) and millimeter Wave (mmWave) systems have emerged as a promising candidate for high data rate wireless transmissions due to the unique complementary properties against the different channel and environment conditions. Consequently, in this study, we investigate the hybrid FSO-mmWave systems from a physical-layer security point of view in the presence of a hybrid type eavesdropper, where the communication between two legitimate peers takes place over both FSO and RF links simultaneously. We examine practical scenarios to eavesdrop the legitimate communication and discuss the effects of random radio power of mmWave link and optical irradiance of FSO link on the probability of achieving a secure transmission. The impact of the fundamental physical layer parameters on the secrecy performance of the hybrid system is analyzed by obtaining closed-form derivations of the probability of strictly positive secrecy capacity (SPSC) for correlated wiretap channels.

Orthogonal time frequency space (OTFS) technique is a recent two-dimensional (2-D) modulation aiming to exploit both time and frequency selectivity of doubly dispersive wireless channel, which significantly affects the reliability of conventional wireless communication systems. In OTFS transmission, delay-Doppler domain is utilized for conveying the data symbols. Besides channel characteristics, the performance of wireless communications systems is severely limited due to the impairments at the RF front-end. One of these impairments is the in-phase and quadrature (IQ) imbalance that occurs due to inevitable imperfections existing between in-phase and quadrature branches at either transmitter (Tx) or receiver (Rx) architecture. The aim of this paper is to reveal and investigate the physical effect of IQ impairment in delay-Doppler domain, which is unknown in the literature. Hence, we provide theoretical models to explicitly understand the impact of IQ imbalance at different stages of OTFS-based communication systems including Tx, Rx, and jointly Tx-Rx. Importantly, we show that although the performance of OTFS transmission depends on both delay and Doppler axes, IQ imbalance leads to an interference originating only from the mirror Doppler axes, which we name mirror Doppler interference (MDI), along with power degradation. Moreover, we assess the performance of IQ imbalanced OTFS under various communication scenarios considering ideal and practical pulse shapes with maximum likelihood (ML) and minimum mean square error (MMSE) detectors, respectively.

Abstract In 5G and beyond communication systems, distinct numerologies can coexist to serve diverse requirements for users and applications. However, the inter‐numerology interference (INI) is a main challenge that significantly impacts the system performance. Therefore, the performance under INI has become an essential evaluation metric for the suitability of the different transmission schemes in the future communication systems. This paper analyzes the impact of INI on the performance of orthogonal frequency division multiplexing with index modulation (OFDM‐IM) systems. Specifically, an analytical expression of the INI level in OFDM‐IM systems is presented as a function of the subcarrier activation ratio (SAR) and subcarrier activation probability (SAP). Furthermore, aiming at reducing the INI level, an adaptive subcarrier mapping scheme (SMS) is proposed based on the conventional combinatorial mapping scheme. Moreover, analysis and evaluation of SAR and SAP are performed regarding the requirements of 5G and beyond services. It is proved that the INI level in OFDM‐IM systems is highly dependent not only on the number of active subcarriers but also on their position in an OFDM block.

Hybrid Free-Space Optical (FSO) and millimeter Wave (mmWave) systems have emerged as a promising candidate for high data rate wireless transmissions due to the unique complementary properties against the different channel and environment conditions. A main issue in hybrid FSO-mmWave systems is the mechanism followed to activate one of the links. Most of the proposed selection mechanisms suffer from the high overhead and the required information at the transmitter. In this study, a novel selection mechanism is proposed for hybrid FSO-mmWave systems without a need for any feedback or channel state information at the transmitter side. The activation of each link, either FSO or mmWave, is determined by the use of Index Modulation (IM) concept. The proposed link selection mechanism, called IM-based mechanism, is compared to the conventional switching mechanisms under various scenarios including different modulation orders, link distances, and weather conditions. In the light of the numerical and simulation results, it is shown that the proposed system significantly improves the overall system performance in terms of the spectral efficiency and the bit-error-rate (BER).

Massive connectivity and spectral efficiency are among the main defining terms of the future communications era. Therefore, revolutionary technologies are required to keep up with the connectivity and spectrum demands. Non-orthogonal multiple access (NOMA) and Index modulation (IM) techniques have emerged as promising candidates to satisfy the spectral efficiency and capacity demands. In this paper, a novel downlink multiple access scheme, called IM-NOMA, is proposed reaping the advantages of both NOMA and IM. In IM-NOMA, the bit block to be sent to each user is divided into two sub-blocks. While the first sub-block is modulated, the second sub-block determines a subset from the available set of channels to carry the modulated symbol. As in power-domain NOMA, the base station (BS) superimposes the modulated symbols carried by the same frequency carrier after a proper power allocation. In such, spectral efficiency is boosted by the extra bits carried by the indexes of the used carriers and the error performance is improved by spreading the users' signals in power domain as well as diversifying the symbols of each user over multiple channels. An upper bound on the average BER is derived in a closed form expression under maximum likelihood (ML) detection method and Rayleigh fading channel. Simulation results show a significant improvement in the BER of the proposed IM-NOMA as compared to the conventional NOMA scheme.

With the expected explosive growth in the user density in wireless networks, recent works have investigated the integration of index modulation (IM) with multiple access schemes, namely the non-orthogonal multiple access (NOMA) scheme. IM-based NOMA schemes have shown appealing advantages in terms of error performance and power efficiency. However, the advantages come with higher detection complexity as an inherited disadvantage of applying IM. In this paper, we propose a constellation rotation-based approach to reduce the detection complexity of the successive interference cancellation (SIC) algorithm. Specifically, we assume two orthogonal constellations to be utilized for transmission. Hence, the introduced rotated-constellations result in orthogonality in the users' signals space which reduces the inter-user interference domains. Therefore the SIC detection complexity is reduced as well. The proposed approach is shown to have a 50% average reduced complexity as compared to classical SIC. Numerical simulations show a significant improvement in terms of error performance as compared to IM-NOMA scheme.

Estimating the frequencies of a multi-component sinusoidal signal is a fundamental problem in signal processing that has very wide and diverse application areas. Most of these applications require very fast and accurate estimation of the sinusoidal frequencies. This letter presents a fast, accurate, simple, and powerful DFT-based algorithm that estimates the frequencies of sums of multiple exponential sinusoidal signals. We show that the presented algorithm requires much less computational cost compared to conventional parametric and non-parametric methods. The simulation results show that the proposed method nearly reaches the Crámer-Rao lower limit after a certain SNR threshold.

Wavelength-domain multiplexing enables near parallel transmission for visible light communications (VLC). In this paper, we investigate an optimal bias allocation problem for the tri-color VLC channel when there is no color cross-talk (CoC), and propose a joint precoding and bias allocation algorithm when CoC exists. The optimization problems are formulated considering both lighting and communication requirements. The color constraint is depicted using the MacAdam ellipses on the chromaticity diagram, as an effective relaxation from a fixed point restriction. Also, for practical concerns, the addressed system is affected by signal-dependent noise (SDN). The bias allocation problem under SDN and related constraints is shown to be non-convex, thus a convex-concave procedure is utilized in this paper for convexification. The joint design problem is also non-convex, and an iterative optimization procedure is adopted, where the decoder is of Wiener filter form. Simulation results are given to show the impacts of SDN, CoC, and steps of MacAdam ellipses on system performance.

In this paper, we revisit the data of the San Antonio Heart Study, and employ machine learning to predict the future development of type-2 diabetes. To build the prediction model, we use the support vector machines and ten features that are wellknown in the literature as strong predictors of future diabetes. Due to the unbalanced nature of the dataset in terms of the class labels, we use 10-fold cross-validation to train the model and a hold-out set to validate it. The results of this study show a validation accuracy of 84.1% with a recall rate of 81.1% averaged over 100 iterations. The outcomes of this study can help in identifying the population that is at high risk of developing type-2 diabetes in the future.

In this paper, we analyze various kinds of hand tremors in the time and frequency domain, that are induced by performing a set of hand actions. We collected the tremor data using a simple, wearable accelerometer from 15 healthy individuals that had varying levels of athleticism. The overall results presented here show that the physiologic tremors in range of 8-14 Hz are most noticeable under fatigue.

Underwater optical wireless communication (UOWC) systems support high-speed, reliable and cost-effective implementations that are demanded for extending the telecommunication networks to oceans. UOWC systems suffer from attenuation and scattering processes. Particularly, the scattering process can change the direction of the emitted photons and, hence, quantifying the signal attenuation and the time-dispersion produced by absorption and scattering is a crucial work. Therefore, we propose new closed-form expressions for modeling the channel impulse response and the path loss in turbid waters that are validated through Monte Carlo simulations and can be used for system design and optimization purposes. Moreover, the developed expression is used to quantify the delay spread, which represents a very useful and accurate measure of the severity of inter-symbol interference (ISI).

This paper focuses on the development of energy efficient visible light communication (VLC) networks. More specifically, since the quality-of-service and energy cost are key parameters in designing energy efficient networks, this paper optimizes the VLC base station (BS) density to minimize the area power consumption (APC) under an outage probability constraint. Using stochastic geometry, approximations of the outage probability of VLC networks are first introduced. The derived approximations are applicable to an arbitrary field-of-view at photodiodes and present low computational complexities. Leveraging the derived analytical results, a low complexity algorithm to find the VLC BS density that minimizes the APC of VLC networks is then proposed. The numerical simulations corroborate the tightness of the approximations on the outage probability and confirm that the proposed algorithm exhibits almost identical performance as the algorithm that exhaustively searches the optimal BS density.

Visible light communication (VLC) technology supports high-speed, reliable, flexible, and cost-effective designs which are demanded most of the underwater wireless communication (UWC) systems. Therefore, in this study, a comprehensive and completely adaptive asymmetrically clipped optical-OFDM based underwater VLC system is designed and demonstrated with widely used and commercially available light emitting diodes (LEDs) and photodiodes (PDs). The designed system is evaluated under twelve different test scenarios with varying fundamental system parameters such as sampling rate, modulation technique and order, and coding rates. In the light of experimental results, it is shown that the system is capable of transmitting and receiving the data supporting both QPSK and 16-QAM modulation techniques with sampling rates of 2 Mbps,5 Mbps, and 10 Mbps. The experimental results also show that bit-error-rate (BER) could still be maintained on the order of 10-6over 6.5 m long underwater pipeline channel. In addition, the performance analyses of cold white, blue and green LEDs at wavelengths of 430 nm, 470 nm, and 530 nm, respectively, are evaluated and compared. Their advantages and drawbacks are discussed in detail.

Despite the high directivity of optical beams, free-space optical (FSO) communications may be compromised by the presence of an external observer, particularly when the beam footprint at the receiver side is greatly wider than the receiver size. In this paper, a new framework is developed for the analysis of the secrecy outage probability (SOP) and the probability of strictly positive secrecy capacity (SPSC) in FSO systems over gamma-gamma (GG) fading channels with nonzero boresight pointing errors. As a key feature, we include the eavesdropper's location in the pointing error model corresponding to the wiretap channel model. In this way, new approximate and asymptotic solutions for both the SOP and the probability of SPSC are obtained in closed-form, which are validated by Monte Carlo simulations. Using the developed expressions, we can study some effects such as the impact of the eavesdropper's location and the beam width on the secrecy outage performance.

This study focuses on the analysis of a decode‐and‐forward relay‐based asymmetric radio frequency‐free space optical (RF‐FSO) communication system. These types of communication systems are of very high speed, secure, and cost‐effective. Such systems can be used to provide the last‐mile access to many household users and can provide temporary network access during disasters and link failures. In the communication model analysed, the RF path is considered as Rayleigh fading, and the FSO path is considered as Málaga ( )‐distributed turbulence fading with the pointing error. Two types of detection schemes consisting of intensity modulation/direct detection and heterodyne detection are considered at the receiver for the analysis. For this cooperative communication system, novel mathematical expressions for the cumulative distribution function, probability density function, and moment generating function of the end‐to‐end signal‐to‐noise ratio are derived. With the aid of these statistical characteristics, new closed mathematical formulations are obtained for outage probability and the average bit error rate for different binary and M‐ary modulation approaches.

In this paper, we propose privacy-preserving fine-grained data retrieval schemes for mobile social networks (MSNs). The schemes enable users to retrieve data from other users who are interested in some topics related to a subject of interest. We define a subject to be a broad term that can cover many fine-grained topics, e.g., History can be a subject and World War I can be a topic. We consider centralized and decentralized network models. Our centralized scheme allows users to securely outsource data to a server such that the server matches the users who are interested in same topic(s) and have defined social attributes with privacy preservation. Searchable encryption scheme and a proposed cryptography construct are used to enable the server to match the topics and attributes without knowing any private information. By using the social attributes, users can prescribe the other users who can be connected to. We also propose a decentralized scheme that can be used when there is no connection to the server, i.e, shortage of Internet connectivity. The scheme leverages friends-of-friends relationship and transferable trust concept, where each user trusts his friends and the friends of friends. If a friend is not interested in the requested subject, he/she can link him/her to his/her friends without knowing the requested subject to preserve privacy. Our schemes use Bloom filters to store the topics of interest to reduce the storage and communication overhead. This is important because the number of fine-grained topics can be large. Different techniques to store the topics in the filter are proposed and investigated. Performance metrics are proposed and evaluated using real implementations. Our analysis and implementation results demonstrate that our schemes can preserve the privacy of the MSN users with high performance.

This paper focuses on the development of energy efficient hybrid networks consisting of radio frequency (RF) base stations (BSs) and visible light communication (VLC) BSs. More specifically, since the quality-of-service and energy cost are key parameters in designing energy efficient networks, this paper optimizes the RF BS and VLC BS intensities to minimize the area power consumption (APC) under an outage probability constraint. Using stochastic geometry, approximations of the outage probability of VLC networks, which are applicable to an arbitrary field-of-view at photodiodes and present low computational complexities, are first introduced. Leveraging the derived analytical results, a low complexity algorithm to find the VLC BS intensity that minimizes the APC of VLC networks is then proposed. Furthermore, algorithms to identify the intensities of RF BSs and VLC BSs for energy efficient hybrid RF/VLC networks via one-dimensional search methods are also developed. The numerical simulations corroborate the tightness of the approximations on the outage probability and confirm that the proposed algorithms exhibit almost identical performances as the algorithms that exhaustively search the optimal BS intensities. Finally, it is shown that the hybrid RF/VLC networks achieve a lower outage probability with a reduced APC compared to the RF-only networks and VLC-only networks.

This work proposes a means to increase the effective modulation bandwidth of a visible light communication (VLC) system using phosphor-coated white light emitting diodes (LEDs) under wide-angle operation. The proposed remedy involves employing a response-flattening filter at the receiver's end of such a VLC system. Off-the-shelf component models are used to simulate the VLC system of interest in order to guarantee realistic results. A trade-off between satisfying a relatively large modulation bandwidth and wide-angle operation of the system is observed. The response- flattening filter proves to be an adequate remedy to mitigate such a trade-off. Analytical expressions and numerical results are used to verify the validity of our proposal.

Modern smart grids rely on advanced metering infrastructure (AMI) networks for monitoring and billing purposes. However, such an approach suffers from electricity theft cyberattacks. Different from the existing research that utilizes shallow, static, and customer-specific-based electricity theft detectors, this paper proposes a generalized deep recurrent neural network (RNN)-based electricity theft detector that can effectively thwart these cyberattacks. The proposed model exploits the time series nature of the customers' electricity consumption to implement a gated recurrent unit (GRU)-RNN, hence, improving the detection performance. In addition, the proposed RNN-based detector adopts a random search analysis in its learning stage to appropriately fine-tune its hyper-parameters. Extensive test studies are carried out to investigate the detector's performance using publicly available real data of 107,200 energy consumption days from 200 customers. Simulation results demonstrate the superior performance of the proposed detector compared with state-of-the-art electricity theft detectors.

Today, free-space optical (FSO) communication in the presence of an eavesdropper is considered as an important topic in the current literature. In this paper, security issues are investigated for FSO wiretap channels. Novel closed-form solutions, both approximate and asymptotic, for the average secrecy capacity (ASC) are derived over gamma-gamma (GG) atmospheric turbulence channels with pointing errors. As a significant aspect, misalignment errors at the eavesdropper's receiver follow the Rice distribution in order to take into consideration the spacing between the legitimate receiver and the eavesdropper's receiver, which is modeled as a nonzero boresight displacement. It is concluded that a greater normalized beam width is required to reduce the loss produced by such attacks in the high signal-to-noise-ratio (SNR) regime. Analytical results are further verified by Monte Carlo simulation results.

As the communication industry is progressing towards fifth generation (5G) of cellular networks, the traffic it carries is also shifting from high data rate traffic from cellular users to a mixture of high data rate and low data rate traffic from Internet of Things (IoT) applications. Moreover, the need to efficiently access Internet data is also increasing across 5G networks. Caching contents at the network edge is considered as a promising approach to reduce the delivery time. In this paper, we propose a marketplace for providing a number of caching options for a broad range of applications. In addition, we propose a security scheme to secure the caching contents with a simultaneous potential of reducing the duplicate contents from the caching server by dividing a file into smaller chunks. We model different caching scenarios in NS-3 and present the performance evaluation of our proposal in terms of latency and throughput gains for various chunk sizes.

Advanced metering infrastructure (AMI) networks are vulnerable against electricity theft cyber attacks. Different from the existing research that exploits shallow machine learning architectures for electricity theft detection, this paper proposes a deep neural network (DNN)-based customer-specific detector that can efficiently thwart such cyber attacks. The proposed DNN-based detector implements a sequential grid search analysis in its learning stage to appropriately fine tune its hyper-parameters, hence, improving the detection performance. Extensive test studies are carried out based on publicly available real energy consumption data of 5000 customers and the detector's performance is investigated against a mixture of different types of electricity theft cyber attacks. Simulation results demonstrate a significant performance improvement compared with state-of-the-art shallow detectors.

WiFi Direct is a new technology that enables direct Device-to Device (D2D) communication. This technology has a great potential to enable various proximity-based applications such as multimedia content distribution, social networking, cellular traffic offloading, mission critical communications, and Internet of Things (IoT). However, in such applications, energy consumption of battery-constrained devices is a major concern. In this paper, we propose a novel power saving protocol that aims at optimizing energy consumption and throughput of user devices by controlling the WiFi Direct group size and transmit power of the devices. We model a content distribution scenario in NS-3 and present the performance evaluation. Our simulation results demonstrate that even a small modification in the network configuration can provide a considerable energy gain with a minor effect on throughput. The observed energy saving can be as high as 1000% for a throughput loss of 12%.

Visible light communication (VLC) is an effective alternative technology to overcome the limitations related to the radio frequency (RF) spectrum. In the modern day of communication systems, the energy harvesting (EH) technique is considered as a promising technology to design more energy efficient communication systems. Integrating VLC with the EH technology in wireless networks guaranties the reliability of these networks. In this paper, we consider a dual-hop VLC/RF wireless communication, composed of two Light Emitting Diodes (LEDs) and two receivers, assisted by a decode-and-forward (DF) relaying system operating with EH in order to boost the coverage of VLC systems. Using successive interference cancellation, we derive achievable rates of both users. Afterwards, we determine the achievable rate-region for this communication system where we show that this region can take four shapes depending on the communication scenario. Then, we formulate the achievable rate-region maximization problem, and we develop solution to find the optimal design for the EH time switching protocol. Further, we show that EH enhances the performance of the communication system in a certain regime of its initial power. We finally present selected numerical result to verify the analytic results.

Full duplex (FD) communication promises significant performance gains under ideal network settings. Generally, it has been shown that the throughput and delay gains of FD communication are somewhat limited in realistic conditions, leading researchers to study other possible applications where significantly higher gains over half duplex communication can be availed. The potential of FD nodes in improving the physical layer security of a communication link is investigated in this contribution. Specifically, we present a thorough analysis of the achievable secrecy rate for a transceiver pair in FD mode in the presence of a passive eavesdropper assuming a generic system model. The ergodic secrecy rate with FD communication is found to grow linearly with the log of the direct channel signal to noise ratio as opposed to the flattened out secrecy rate with conventional half duplex communication and irrespective of the eavesdropper channel strengths.

In this paper, the secrecy outage performance of an underlay cognitive decode-and-forward (DF) relay network over independent and non-identical distributed (i.n.i.d) Nakagami-m fading channels is investigated, in which the secondary user transmitter communicates with the secondary destination via relays, and an eavesdropper attempts to overhear the information. We assume that the channel state information (CSI) of all links is available. The exact and asymptotic closed-form expressions for the secrecy outage probability with optimal relay selection are derived, and verified by Monte-Carlo simulations. Through asymptotic analysis, we find that the secrecy diversity order is determined by the number of relays and the fading parameters between relay and destination.

In this work, the performance of an underwater visible light communication system utilizing a vertical communication channel is evaluated. The inhomogeneity of underwater environment is taken into consideration. A mathematical model for the received power is derived and bit error rates (BER) are computed for different underwater environments. The validity of the model is verified by numerical results. Moreover, our results show that there exists an optimum transmitter-receiver separation, where BER is minimum, under a specific transmission orientation angle.

The satellite relaying system is a promising network architecture in next generation wireless communication systems, due to its large coverage and stability. In this paper, the performance of a dual-hop decode-and-forward based satellite relaying system over κ-μ shadowed fading channels is investigated, where a source earth station transmits information to a destination earth station via a satellite relay. We first obtain the exact closedform expressions of the outage probability of such a system in terms of bivariate confluent hypergeometric functions. By using a novel gamma approximation to the κ-μ shadowed distribution, the simple outage expression is derived. Moreover, the accurate expression of the average bit error rate (ABER) and the ergodic capacity are obtained in terms of Appell hypergeometric functions and hypergeometric functions, respectively. Again, with the help of the gamma approximation, we derive the approximate ABER and capacity expressions. In the high signal-to-noise ratio regime, the asymptotic ABER expression is obtained in terms of elementary functions. Finally, numerical and Monte-Carlo simulation results are provided to demonstrate the validity of the proposed unified expressions.

Full-duplex communication enables simultaneous transmission from both ends of a communication link, thereby promising significant performance gains. Generally, it has been shown that the throughput and delay gains of full-duplex communication are somewhat limited in realistic network settings, leading researchers to study other possible applications that can accord higher gains. The potential of full-duplex communication in improving the physical-layer security of a communication link is investigated in this contribution. We specifically present a thorough analysis of the achievable ergodic secrecy rate and the secrecy degrees of freedom with full-duplex communication in the presence of a half-duplex eavesdropper node, with both single-user decoding and multi-user decoding capabilities. For the latter case, an eavesdropper with successive interference cancellation and joint decoding capabilities is assumed. Irrespective of the eavesdropper capabilities and channel strengths, the ergodic secrecy rate with full-duplex communication is found to grow linearly with the log of the direct channel signal-to-noise-ratio (SNR) as opposed to the flattened out secrecy rate with conventional half-duplex communication. Consequently, the secrecy degrees of freedom with full-duplex is shown to be two as opposed to that of zero in half-duplex mode.

In vivo wireless body area networks and their associated technologies are shaping the future of healthcare by providing continuous health monitoring and noninvasive surgical capabilities, in addition to remote diagnostic and treatment of diseases. To fully exploit the potential of such devices, it is necessary to characterize the communication channel, which will help to build reliable and high-performance communication systems. This paper presents an in vivo wireless communication channel characterization for male torso both numerically and experimentally (on a human cadaver) considering various organs at 915 MHz and 2.4 GHz. A statistical path loss (PL) model is introduced, and the anatomical region-specific parameters are provided. It is found that the mean PL in decibel scale exhibits a linear decaying characteristic rather than an exponential decaying profile inside the body, and the power decay rate is approximately twice at 2.4 GHz as compared to 915 MHz. Moreover, the variance of shadowing increases significantly as the in vivo antenna is placed deeper inside the body since the main scatterers are present in the vicinity of the antenna. Multipath propagation characteristics are also investigated to facilitate proper waveform designs in the future wireless healthcare systems, and a root-mean-square delay spread of 2.76 ns is observed at 5 cm depth. Results show that the in vivo channel exhibit different characteristics than the classical communication channels, and location dependence is very critical for accurate, reliable, and energy-efficient link budget calculations.

Visible light communications (VLC) technology has recently emerged as a complementary technology to the indoor radio frequency (RF) networks. While the backhauling of the indoor RF networks has been supported by fiber optics, the backhauling of the VLC network is still an open research problem. Power line communications (PLC) has been considered as a possible solution for the VLC networks due to its ubiquity. However, given the noisy behaviour of the channels, the use of PLC backhauling requires further study to investigate the maximum rate which can be supported for VLC networks. In this paper, we continue our work on a single-user hybrid PLC/VLC/RF system [1] to study the effect of PLC backhauling in multi-user hybrid VLC/RF networks. To this end, we adopt an orthogonal frequency division multiplexing (OFDM)- based PLC backhaul system where we find the optimal power and subcarrier allocation algorithm that maximizes the multi-user rate utility function for the cascaded PLC and VLC links in parallel with the RF network. Moreover, we study numerically the impact of various parameters on the system performance including the PLC transmission power, the RF and VLC maximum allowable rates, and the numbers of mobile terminals and access points.

Based on the concept of reconfigurable antennas (RAs), SSK-RA has been recently proposed as a novel transmission scheme to improve the performance of space shift keying (SSK). In this context, it has been shown that RAs' reconfigurable properties can be used as additional degrees of freedom to enhance the throughput, implementation complexity, and error performance of SSK. In this paper, we extend SSK-RA to cognitive radio (CR) systems in an effort to improve the secondary system's performance in a spectrum sharing scenario. Taking advantage of the interplay between RAs and the propagation channels for both the secondary and interference links, we propose a RA-based scheme with pointing-direction reconfiguration aiming at improving the secondary system's performance while verifying an outage interference constraint to the primary user (PU). In this paper, we analyse the performance of the proposed scheme in Rician fading channels and provide simulation examples confirming these analytical results. The proposed schemes are shown to offer better bit error rate (BER) performance and lower implementation complexity when compared to conventional antenna-based spectrum sharing systems.

In this work, the outage performance analysis of a dual-hop transmission system composed of asymmetric radio frequency (RF) channels cascaded with free-space optical (FSO) links is presented. The RF links are modeled by the Rayleigh fading distribution and the FSO links are modeled by Malaga (M) turbulence distribution. The FSO links account for pointing errors and both types of detection techniques (i.e. heterodyne detection as well as intensity modulation/direct detection (IM/DD)). Transmit diversity is applied at the source, selection combining is applied at the destination, and the relay is equipped with single RF receive antenna and single aperture for relaying the information over FSO links. With this model, a new exact closed-form expression is derived for the outage probability of the end-to- end signal-to-noise ratio of such communication systems in terms of the Meijer's G function under fixed amplify-and-forward relay scheme. All new analytical results are verified via computer-based Monte-Carlo simulations and are illustrated by some selected numerical results.

In literature, dynamic planning (base station (BS) on-off switching) is proposed as an efficient approach for energy saving at a low call traffic load condition. All related research efforts aim to employ dynamic planning to save energy for the network operators while satisfying the quality-of-service (QoS) for downlink mobile users. On the other hand, although switching off a BS can save energy for network operators and satisfy the downlink QoS, it may lead to associating uplink mobile users with a faraway BS, and hence, degrade the uplink QoS. Such an impact of dynamic planning on uplink service quality is not well investigated in literature. In this paper, we aim to quantify this impact by considering two QoS metrics, namely, user required throughput and call dropping probability due to mobile terminal battery depletion for uplink data calls. Simulation results demonstrate that BS switching off decisions that do not account for the uplink QoS requirements can result in severe service quality degradation.

In this work, we consider the transmission of confidential message through independent and identically distributed generalized-K fading single-input multiple-output (SIMO) channels in the presence of an eavesdropper. The security performance of SIMO generalized-K systems are investigated using a mixture gamma (MG) distribution, and the analytical expressions for the average secrecy capacity (ASC) and the secure outage probability (SOP) of SIMO systems are derived. Numerical results are presented and verified via Monte-Carlo simulations.

In this work, bit error rate (BER) measurements of visible light communications (VLC) systems are introduced as an effective possible replacement of reflectivity measurements in a conventional optical plasmonic sensing procedure. In particular, we investigate a procedure where we exploit the phenomenon of the variations of BER values of the VLC systems with the sensed concentration of contaminations in the sensing medium. We consider a system composed of a VLC white LED source that transmits data through the sensing medium, which is then detected by a receiver and the BER values are computed. Our analysis proves that the information extracted from the BER measurements is sufficient to learn about the sensing medium and hence can replace conventional measurement techniques used in optical sensing. Thus, a simpler procedure of optical sensing is proposed due to the low cost of the proposed system and its flexibility in sensing medium in different environment scenarios. In this work, the proposed idea is verified for optical SPR sensors for their high impact state-of-art performance over other conventional optical sensors. Moreover, the VLC-based system is shown to have no negative effect on the performance of the designed optical SPR sensor in a way that undermines its operation.

In this paper, a novel devices-to-device (Ds2D) communication paradigm is proposed to enable green (energy efficient) wireless networks. Different from the conventional D2D communications, the sink device establishes simultaneous associations with multiple source devices for file download using its multiple radio interfaces and the multi-homing technique. In such a networking setting, we propose a network-controlled algorithm for optimal selection of source devices and their respective radio interfaces to support green Ds2D communications. Simulation results demonstrate that the proposed Ds2D communication paradigm under optimal selection of source devices and radio interfaces presents an improved energy efficiency performance compared with the conventional D2D communications, and leads to a lower energy consumption per source device.

Full duplex communication promises a theoretical 100% throughput gain by doubling the number of simultaneous transmissions. Such compelling gains are conditioned on perfect cancellation of the self interference power resulting from simultaneous transmission and reception. Generally, self interference power is modelled as a noise-like constant level interference floor. However, experimental validations have shown that the self interference power is in practice a random variable depending on a number of factors such as the surrounding wireless environment and the degree of interference cancellation. In this study, we derive an analytical model for the residual self interference power, and demonstrate various applications of the derived model in analysing the performance of a Full Duplex radio. In general, full duplex communication is found to provide only modest throughput gains over half duplex communication in a dense network scenario with practical self interference cancellation models.

In this paper, we propose a privacy-preserving power charging coordination scheme. Each energy storage unit (ESU) should send a charging request to an aggregator. The request does not reveal any private information to the aggregator. The aggregator forwards the requests to a charging controller that can know enough data to run a charging coordination scheme, but it cannot link the data to particular ESUs. Temporal charging coordination scheme is then proposed based on a modified knapsack problem formulation. The goal is to maximize the amount of power delivered to the ESUs before the charging requests expire without exceeding the available maximum charging capacity. Our simulation results demonstrate that both the optimal charging coordination and the privacy-aware charging coordination exhibit an improved performance compared with a first-come-first-serve charging coordination. More importantly, the privacy-aware scheme offers an attractive trade-off between the charging coordination performance and privacy preservation.

In this paper, we propose a trust-based and privacy-preserving fine-grained data retrieval scheme for mobile social networks (MSNs). The scheme enables users to create a log of trusted users who store (or are interested in) some topics related to a subject of interest. A subject is a broad term that can cover many fine-grained topics. In creating logs, we leverage friends-of-friends relationships and transferrable trust concept. Each user trusts its friends and the friends of friends. If a friend is not interested in a subject, he can help his friend in creating the log by linking the friend to his friends without knowing the subject to preserve privacy. In order to reduce the storage and computation overhead, we use Bloom filters to store the topics. A distinctive feature in our scheme is that it can query users who possess a fine-grained topic, rather than querying users who are interested in the broad subject but they may not have the specific topic of interest. We analyze the security and privacy of our scheme and evaluate the communication and computation overhead.

In this paper, the channel model is proposed to compute the path loss, delay and noise at THz band of interest (0.5 THz ~ 1.5 THz). The results shows that THz band channel is strongly dependent on both the type of the medium and the distance while the concentration of water have a lot of influence because it not only causes attenuation to the THz wave but also introduces non-white noise. Therefore, the proposed model paves the way to the further studies considering more body structures and tissue properties.

In this study, the secrecy performance of the classic Wyner's wiretap model over generalised‐ K fading channels is studied. The closed‐form expressions for the average secrecy capacity, the lower bound of secure outage probability, and the probability of strictly positive secrecy capacity are derived. The new expressions provide a unified form, which can handle several of the well‐known composite fading environments as special or limiting cases. Moreover, all the derived expressions are given in terms of Meijer's G ‐function, which can be simply realised in MATLAB and MATHEMATICA. Monte‐Carlo simulations are performed to verify the proposed analysis models.

In this study, the channel capacity performance of a dual‐hop asymmetric radio‐frequency–free space optical (RF–FSO) communication system in the presence of pointing errors is presented. Here, both fixed‐gain amplify and forward (AF) and decode and forward (DF) relays are considered. The RF link experiences Rayleigh fading and the FSO link experiences Málaga distributed turbulence channel. For this mixed RF–FSO cooperative system, novel mathematical expressions for cumulative distributive function (CDF) and the channel capacity are derived and performance is analysed with both fixed‐gain AF and DF relays in the presence of pointing errors. In addition, the authors derive the asymptotic expressions for the CDF and the channel capacity derived earlier in terms of Meijer's G function in the high signal‐to‐noise ratio regime.

Developing energy efficient wireless communication networks has become crucial due to the associated environmental and financial benefits. Visible light communication (VLC) has emerged as a promising candidate for achieving energy efficient wireless communications. Integrating VLC with radio frequency (RF)-based wireless networks has improved the achievable data rates of mobile users. In this paper, we investigate the energy efficiency benefits of integrating VLC with RF-based networks in a heterogeneous wireless environment. We formulate and solve the problem of power and bandwidth allocation for energy efficiency maximization of a heterogeneous network composed of a VLC system and an RF communication system. Then, we investigate the impact of the system parameters on the energy efficiency of the mixed RF/VLC heterogeneous network. Numerical results are conducted to corroborate the superiority in performance of the proposed hybrid system. The impact of hybrid system parameters on the overall energy efficiency is also quantified.

Dynamic planning has been used by network operators for energy saving by switching ON-OFF base stations (BSs) according to the traffic load condition while providing quality-of-service (QoS) guarantee for mobile users. In the literature, research efforts focus mainly on satisfying the QoS of downlink mobile users. However, the impact of dynamic planning on the QoS of uplink mobile users is overlooked. A dynamic planning approach that relies only on the downlink performance of mobile users to determine the BS switching decision can result in deactivating nearby small cells and associating uplink mobile users to a faraway macro BS. Consequently, uplink mobile users may suffer from QoS degradation due to the longer transmission distance. Hence, while saving energy for the network operators and satisfying the downlink QoS, the uplink QoS could be violated. In this paper, we propose a balanced dynamic planning approach that accounts for QoS requirements both in the uplink and downlink to specify the BS switching decision. The switching decision is formulated as a two-timescale average reward Markov decision process with finite horizon. Due to computational complexity, sub-optimal algorithms are proposed. Simulation results demonstrate the trade-off between energy saving and QoS guarantee.

In this paper, the transmission of confidential messages through single-input multiple-output (SIMO) independent and identically generalized- K ( K G ) fading channels is considered, where the eavesdropper overhears the transmission from the transmitter to the receiver. Both the receiver and the eavesdropper are equipped with multiple antennas, and both active and passive eavesdroppings are considered where the channel state information of the eavesdropper’s channel is or is not available at the transmitter. The secrecy performance of SIMO K G systems is investigated. Analytical expressions for secrecy outage probability and average secrecy capacity of SIMO systems are derived via two different methods, in which K G distribution is approximated by the Gamma and mixture Gamma distributions, respectively. Numerical results are presented and verified via the Monte-Carlo simulation.

In this letter, we consider a single-input multiple-output cognitive wiretap system over generalized-K channels, where the eavesdropper overhears the transmission from the secondary transmitter (ST) to the legitimate receiver. Both the primary user and the ST are equipped with a single antenna, whereas the legitimate and the eavesdropper receivers are equipped with multiple antennas. The close-form expression for the secrecy outage probability is derived. Simulations are presented to validate the accuracy of our proposed analytical results.

Based on the concept of reconfigurable antennas (RAs), space-shift keying (SSK)-RA has been recently proposed as a novel transmission scheme to improve the performance of SSK. In this context, it has been shown that RAs' reconfigurable properties can be used as additional degrees of freedom to enhance the throughput, implementation complexity, and error performance of SSK. In this paper, we study the implementation of SSK-RA within underlay cognitive radio systems in an effort to improve the performance of the secondary user while verifying the constraints set by the primary user (PU). Taking advantage of the interplay between RAs and the propagation channels for both the secondary and interference links, we propose an RA-based scheme with beam-direction reconfiguration aiming at improving the secondary system's performance while verifying an outage interference constraint to the PU. In this paper, we analyze the performance of the proposed scheme in Rician fading channels and provide simulation examples confirming these analytical results. The proposed schemes are shown to offer enhanced bit error rate performance and lower implementation complexity when compared with conventional antenna-based spectrum sharing systems.

Several corrections are necessary for the above-named work are presented.

In this work, we use the concept of the new emerging technology of reconfigurable antennas (RAs) in an effort to improve the performance of space shift keying (SSK). Indeed, the reconfigurable properties of RAs can be used as additional degrees of freedom to enhance the performance of SSK in terms of throughput, system complexity, and error performance. In this context, considering correlated and nonidentically distributed Rician fading channels, we propose a number of SSK-RA schemes using SSK with antenna-state selection while taking advantage of the effect of RAs on the multipath propagation channel. More specifically, based on the variation of the Rician K-factor and the correlation coefficients with different antenna states, the proposed schemes jointly optimize the fading and correlation parameters to enhance SSK's performance. In this paper, we analyze the performance of the proposed SSK-RA schemes over Rician fading channels in terms of average spectral efficiency (ASE) and bit error rate (BER). We also provide several simulation examples through which we corroborate these analytical results. The proposed schemes are shown to enhance the performance of SSK both in terms of ASE and BER. For the same ASE, compared to that of SSK, not only do the proposed SSK-RA schemes provide much better error performance, they also reduce the implementation cost and the overall system complexity considerably.

Abstract In future heterogeneous cellular networks, cognitive radio compatible with device to device communication technique can be an aid to further enhance system spectral and energy efficiency. The unlicensed smart devices (SDs) are allowed to detect the available licensed spectrum and utilise the spectrum resource which is detected as not being used by the licensed users. In this work, we propose such a system and provide comprehensive analysis of the effect of selection of SDs' frame structure on the energy efficiency, throughput and interference. Moreover, uplink power control strategy is also considered where the licensed users and SDs adapt the transmit power based on the distance from their reference receivers. The optimal frame structure with power control is investigated under high‐signal‐to‐noise ratio (SNR) and low‐SNR network environments. The impact of power control and optimal sensing time and frame length, on the achievable energy efficiency, throughput and interference are illustrated and analysed by simulation results. It has been also shown that the optimal sensing time and frame length which maximizes the energy efficiency of SDs strictly depends on the power control factor employed in the underlying network such that the considered power control strategy may decrease the energy efficiency of SDs under very low‐SNR regime. Copyright © 2016 John Wiley & Sons, Ltd.

The increased demands for indoor wireless data services with the limited available radio frequency (RF) spectrum are motivating researchers to investigate alternative technologies to augment the existing RF networks. Utilizing the visible light spectrum by exploiting visible light communication (VLC) has shown strong potential to augment RF networks in indoor scenarios. The ubiquity of the power-line network makes it an attractive choice as a communication medium between the data sources and the VLC transmitters through power line communication (PLC). Hence, integrating VLC and PLC systems can be a strong complementary hybrid wireline/wireless technology for indoor data networks. In this paper, we investigate the power allocation problem for a communication scenario in which data is transferred through a cascaded PLC/VLC channel in parallel to an RF wireless channel. We develop an algorithm for allocating the transmission powers among the communication nodes to maximize the achievable rate. Our results show that the proposed system provides appreciable rate gains compared to conventional RF communication systems for the same amount of total transmission power.

In future smart grids, energy storage systems (ESSs) are expected to play a key role in reducing peak hour electricity generation cost and the associated level of carbon emissions. Considering their high acquisition, operation, and maintenance costs, ESSs are likely to serve a large number of users. Hence, optimal sizing of energy ESSs plays a critical role as over-provisioning ESS size leads to under-utilizing costly assets and under-provisioning it taxes operation lifetime. This paper proposes a stochastic framework for analyzing the optimal size of energy storage systems. In this framework the demand of each customer is modeled stochastically and the aggregate demand is accommodated by a combination of power drawn from the grid and the storage unit when the demand exceeds grid capacity. In this framework an analytical method is developed, which provides tractable solution to the ESS sizing problem of interest. The results indicate that significant savings in terms of ESS size can be achieved.

In this work, we use the concept of reconfigurable antennas (RAs) in an effort to improve the performance of space shift keying (SSK). Indeed, the reconfigurable properties of RAs can be used as additional degrees of freedom in order to enhance the performance of SSK in terms of throughput, system complexity, and error performance. In this context, we propose a number of SSK-RA schemes using SSK with antenna-state selection while taking advantage of the interplay between RAs and the propagation channel. In this paper, we analyse the performance of the proposed SSK-RA schemes in Rician fading channels in terms of average spectral efficiency (ASE) and average bit error rate (ABER).We also provide several simulation examples through which we corroborate these analytical results. The proposed schemes are shown to enhance the performance of SSK both in terms of ASE and ABER. For the same ASE as SSK, SSK-RA schemes not only provide much better error performance but also considerably reduce the implementation cost and the overall system complexity.

In a network with multiple relays, relay selection has been shown as an effective scheme to achieve diversity as well as to improve the overall throughput. This paper studies the impact of using outdated channel state information for relay selection on the performance of a network where two sources communicate with each other via fixed-gain amplify-and-forward relays. For a Rayleigh faded channel, closed-form expressions for the outage probability, moment generating function and symbol error rate are derived. Simulations results are also presented to corroborate the derived analytical results. It is shown that adding relays does not improve the performance if the channel is substantially outdated. Furthermore, relay location is also taken into consideration and it is shown that the performance can be improved by placing the relay closer to the source whose channel is more outdated.

This paper presents an energy efficient and quality of service aware dynamic cell zooming algorithm for dense heterogeneous networks. The exponential growth of mobile data traffic would lead to dense deployment of small base stations and eventually higher energy consumption in Fifth Generation (5G) wireless networks. We formulate a dynamic cell zooming and base stations sleep optimization algorithm for dense heterogeneous networks as a Linear Programming (LP) problem in order to not only minimize the system power consumption but also to guarantee the quality of service to end user. This is possible by optimally zooming the coverage area of macro base stations and small cells based upon real time traffic conditions. We characterize the optimal as well as provide an approximate solution, which, however, performs very closely to the optimum. The extensive performance evaluation of our proposed dynamic cell zooming algorithm shows that our proposed algorithm can significantly decrease both system energy consumption and outage probability.

We have recently proposed adaptive spatial modulation (ASM) for multiple antenna systems with the aim of improving the energy efficiency through spatial modulation (SM) and improving the average spectral efficiency (ASE) through adaptive modulation. In this paper, we extend ASM to spectrum sharing systems in an effort to improve the secondary system's performance in terms of energy efficiency and ASE. Based on a limited feedback from the primary user (PU), the secondary transmitter (ST) uses power adaptation in order to maximize its ASE while respecting a peak interference constraint to the PU. When compared to the recently-proposed fixed power scheme (FPS), the adaptive power scheme (APS) proposed in this paper offers lower transmission delays, higher effective throughput, and comparable error performance. In this work, we analyze the performance of APS in terms of ASE, effective throughput, and average bit error rate (ABER). We also provide several simulations through which we corroborate these analytical results.

This paper focuses on the resilience of routing protocols against malicious insiders willing to disrupt communications. Previous study showed that introducing randomness and data replication enhances the resilience of routing protocols. It makes them unpredictable for an attacker and provides route diversification. We propose a theoretical framework of the resilience based on biased random walks on a torus lattice. The objective is to evaluate analytically the influence of bias and data replication introduced to random walks. The bias allows to decrease the route length, thus reducing the probability of a data packet to meet a malicious insider along the route; however, it also decreases the degree of randomness (entropy). When combined with data replication, the reliability is improved thanks to route diversity despite an additional overhead in terms of energy consumption. The main goal is to provide a good tradeoff between shortest path and route diversity for a reasonable cost.

The paper presents an initial study of analyzing the propagation of electromagnetic waves at terahertz frequencies inside the human skin tissues in the frequency range 0.8-1.2 THz. The skin model is represented by three layers: stratum corneum (SC), epidermis, and dermis, and the effect of the presence of sweat ducts is also studied. The path loss resulting from the signal propagation between a transmitting antenna, located at the epidermis layer, and a receiving antenna, located at the dermis layer, is analyzed for different distances and different frequencies, in addition to changing the number of sweat ducts. Results show that the path loss through the skin tissues depends on the distance between the transmitter and the receiver, the frequency used, and the number of sweat ducts as the path loss decreases by approximately 1 dB for increasing the number of sweat duct from one duct to two ducts. Moreover, the path loss is statistically studied and its distribution is approximately Gaussian.

A novel frequency reconfigurable microstrip patch antenna has been presented for 3.6 GHz and 5 GHz. Compared to the traditional, complicated and high cost frequency reconfigurable antennas, our work is featured by a simple and concise design. The frequency reconfiguration is obtained by using layers of mercury and liquid crystal polymer (LCP) on conventional patch antenna. The proposed structure was modelled and simulated using CST Microwave Studio. The antenna was first simulated in free space to check the antenna parameters such as return loss, gain, radiation pattern and efficiency. After obtaining the results, the antenna was simulated for analysing the on-body performance by using numerical model of human body. The simulated return loss for both the configurations is less than -10 dB at the radiating frequencies. The free space simulated results show the close agreement with the on-body test results.

We have recently introduced adaptive spatial modulation (ASM) for multiple antenna systems, with the aim of improving the energy efficiency through spatial modulation (SM) and improving the average spectral efficiency (ASE) through adaptive modulation (AM). In this paper, we extend ASM to cognitive radio (CR) systems in an effort to improve the secondary system's performance in terms of energy efficiency and ASE. To this end, we propose two ASM schemes, one referred to as fixed power scheme (FPS) and the other as adaptive power scheme (APS). In both schemes, the secondary transmitter (ST) has limited knowledge of the channel state information (CSI) of the interference link. The difference between the two schemes, however, lies in the way the limited CSI is used to adapt the transmit power and/or modulation. As a benchmark, we also consider the scenario where the ST has perfect knowledge of the CSI of the interference link. For all cases, we analyze the performance in terms of ASE, average delay, and bit error rate (BER). We show that the proposed schemes offer tradeoffs in terms of the previously mentioned performance metrics, thus offering different options for applying ASM to CR systems. We also provide several simulation examples through which we corroborate the analytical results.

In this paper, energy efficient uplink communications are investigated for battery-constrained mobile terminals (MTs) with service quality requirements and multi-homing capabilities. A heterogeneous wireless medium is considered, where MTs communicate with base stations (BSs) and access points (APs) of different networks with overlapped coverage. Different from the existing works, we develop a quality of service (QoS)-based optimization framework for joint uplink bandwidth and power allocation to maximize energy efficiency for a set of MTs with multi-homing capabilities. The proposed framework is implemented in a decentralized architecture, through coordination among BSs/APs of different networks and MTs, which is a desirable feature when different networks are operated by different service providers. A suboptimal framework is presented with a reduced computational complexity as compared with the optimal framework. Simulation results demonstrate the improved performance of both the optimal and suboptimal frameworks over a state-of-the-art benchmark.

Reconfigurable antennas (RA) offer an emerging technology that allows wireless devices to alter their antenna states determined by different radiation patterns to maximize received signal strength. In this paper, we consider multiuser orthogonal frequency-division multiple access cognitive heterogeneous networks (HetNets) and we study the potential benefits of employing RA in terms of improving the overall network capacity. In cognitive HetNets, a secondary network is allowed to share the spectrum with the primary network under the condition that the interference level experienced by the primary network is below a predetermined threshold. To satisfy this interference constraint, a secondary user (SU) employs a power control mechanism, which typically limits its transmission power and thus reduces substantially its performance. Moreover, the large number of users expected for next-generation networks brings dense interference to the secondary network and, as such, even efficient interference mitigation and resource allocation techniques can fail in maintaining an acceptable performance level for the network. In this work, we consider utilizing RA technology at SUs to act as an additional resource in terms of selecting antenna radiation patterns that improve received signal strength among SUs. This also limits the mutual interference between the secondary and primary networks. We propose a game theoretical framework for jointly selecting the subcarriers as well as the RA antenna state at each SU that maximizes the overall capacity of the network while meeting the interference target in the primary network. Using potential games that guarantee the existence of a Nash equilibrium, our results show that, by selecting the best RA state and subcarriers for each SU, the capacity of the secondary network increases substantially compared to a scenario with conventional omni-directional antennas.

Abstract Consider a multi‐user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami‐m fading. The interference channel between the secondary users (SUs) and the primary users is assumed to have Rayleigh fading. A power allocation based on the instantaneous channel state information is derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each SU. The uplink scenario is considered where a single SU is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the moment‐generating function, outage performance, symbol error rate performance, and the ergodic capacity are derived. Numerical results corroborate the derived analytical results. The performance is also studied in the asymptotic regimes, and the generalized diversity gain of this scheduling scheme is derived. It is shown that when the interference channel is deeply faded and the peak transmit power constraint is relaxed, the scheduling scheme achieves full diversity and that increasing the number of primary users does not impact the diversity order. Copyright © 2014 John Wiley & Sons, Ltd.

Opportunistic relaying in cooperative communication depends on careful relay selection. However, the traditional centralized method used for opportunistic amplify-and-forward protocols requires precise measurements of channel state information at the destination. In this paper, we adopt the max-min criterion as a relay selection framework for opportunistic amplify-and-forward cooperative communications, which was exhaustively used for the decode-and-forward protocol, and offer an accurate performance analysis based on exact statistics of the local signal-to-noise ratios of the best relay. Furthermore, we evaluate the asymptotical performance and deduce the diversity order of our proposed scheme. Finally, we validate our analysis by showing that performance simulation results coincide with our analytical results over Rayleigh fading channels, and we compare the max-min relay selection with their centralized channel state information-based and partial relay selection counterparts.

A number of research programs are run at undergraduate level by government and private organizations across the globe that fund research activities beyond ordinary coursework during the academic year. This paper analyzes the performance of one such program called Undergraduate Research Experience Program (UREP), in Qatar. The grants provided under UREP render the recipients with the opportunity to conduct original research under faculty supervision. We collected detailed statistics about this program to analyze its significance in terms of research output, benefits to the students, skill development and faculty involvement. We conducted a survey among the participant faculty and students to have an impartial and balanced opinion about the program.

3D visualization has become one of the most sort after tool to display hidden information to the students utilizing their sense of vision. This tool has been successful in aiding education, more specifically in teaching engineering subjects. Intricate concepts and phenomenons can easily be visualized in motion to the emerging engineers. This gives great insight of otherwise hard to understand principles and constructs. Wireless communication subjects are a good example of the use of visualization tool in teaching engineering. Recent prolific growth in wireless devices such as smart phones, tablet computers and other easy to carry devices made the use of radio frequency omnipresent. The widespread use of these devices has also raised health concerns among the masses due to the possible malign effects of electromagnetic radiations on the human body, especially on the brain due to its proximity with the hand-held radio devices. These radiations are absorbed in the head while making phone calls, and thereby increasing the direct and indirect health risks. These risks include, the rise of temperature in human body tissues resulting in adverse physiological problems [1]. As a matter of fact, even a small change in temperature in brain can be detrimental; a few degrees rise in temperature in the hypothalamus may cause thermoregulatory behavior [2]. The most important aspect of these effects is the fact that they largely go un-noticed. There are also no means to verify or observe the RF absorption, termed as Specific Absorption Rate (SAR) on the human head and brain. This paper presents the significance of 3D visualization for engineering students and help elucidate the intricate and challenging scientific engineering concepts. A useful case study has been developed at Texas A&M University at Qatar's Immersive Visualization Facility (IVF) to visualize the impact of RF signals on human head and brain. We have presented our initial efforts to visualize and observe the effects of SAR on a human head model. The series of 3D visualizations are built by using the mathematical model of SAR to understand the distribution of RF over the layers of considered human head model.

Enquiry-based student-centered learning activities in engineering classrooms may lose its focus and success if the activities in classroom are biased due to the failure in forming mixed-ability oriented teams or groups of students. This paper proposes a technology driven team-building methodology to enhance enquiry-based learning in the conventional engineering classrooms, which is referred to as Heterogeneous Ability-Centered Team Building (H-ACT-B) method. The H-ACT-B method guarantees mixed-ability based team or group formation in classroom to promote effective communication, collaboration and critical thinking based on the programmed evaluation of individual student's aptitude. The proposed team building method is expected to aid the individual student and the team or group to ensure their progress toward achieving the common team task efficiently. Moreover, the study is strongly formulated by considering the useful insights about the current team building practices and methods by conducting survey among the engineering faculty and students.

In this paper, it is demonstrated for the first time that the problem of continuous downhole monitoring in the oil and gas industry is effectively addressed by the use of visible light communication (VLC). As a reliable, flexible and low-cost technique, VLC can fulfill a critical need of operators to maintain production efficiency and optimize gas well performance. The proposed VLC system makes use of a light emitting diode (LED) transmitter and a high sensitivity single photon detecting receiver referred to as single-photon avalanche diode (SPAD). The latter is instrumental in achieving long range communications, and the fact that ambient light is not present in a gas pipe is exploited. Specifically, the lack of ambient light enables high signal to noise ratio (SNR) at the receiver which operates in a photon counting mode. In this study, the bit error ratio (BER) performance of the system is simulated for a 4 kilometres long metal pipe. It is shown that the proposed system has superior power efficiency over conventional methods, which is important as it is assumed that the transmitter is battery operated. In addition, the theoretical BER performance is calculated and compared to the simulation results.

A vehicle-to-vehicle (V2V) (dis)charging strategy can provide charging plans for gridable electric vehicles (GEVs), aiming to offload the heavy power loads from the electric power system. However, designing an efficient online V2V (dis)charging strategy to achieve optimal energy utilization is still an open issue. In this paper, we propose a semi-distributed online V2V (dis)charging strategy at a swapping station based on price control. Specifically, based on the electricity price control strategy, GEVs are motivated to contribute to a V2V energy transaction due to expected high revenue for discharging GEVs and low cost for charging GEVs. The Oligopoly game and Lagrange duality optimization techniques are exploited to address the associated optimal V2V (dis)charging strategies. Simulation results are presented to demonstrate the performance of the proposed V2V (dis)charging strategy.

Reconfigurable antennas (RA) have been viewed as a hardware-efficient alternative solution to multiple-input multiple-output systems whereby network users can vary the antenna radiation patterns using a single antenna element to maximize the received signal strength. In this paper, we study the potential benefits of employing RA in multiuser orthogonal frequency division multiple access cognitive heterogeneous networks (Het-Nets) in terms of the overall network capacity. In cognitive HetNets, a secondary (unlicensed) network is allowed to share the spectrum with the primary (licensed) network under the condition that the interference level at the primary network is below a predetermined value. To account for this interference constraint, the secondary user (SU) can limit their transmission power and thus reducing substantially its performance. Moreover, the large number of users expected for next generation network brings dense interference to the secondary network and thus even efficient interference mitigation and resource allocation techniques can fail in maintaining the required performance level. Therefore, in this paper, we consider utilizing an RA at the SUs that acts as an additional resource which can be optimized by selecting the best state that maximizes the signal strength among the SUs and limits the mutual interference between the secondary and primary network. In particular, we propose a game theoretical framework for selecting the subcarriers based on best allocation techniques as well as the random antenna state selection that maximizes the overall capacity of the network while obeying the interference level in the primary network. We use potential games which guarantee the Nash equilibrium existence. Our results show that by selecting the optimal RA state and the subcarriers for each user, the capacity of the secondary network increases substitutionally with limited hardware complexity.

In underlay cognitive networks, the unlicensed (secondary) user is allowed to share the spectrum with the licensed (primary) user under the constraint that the interference at the primary user should be below a specific threshold. This constraint forces the cognitive network to apply power control techniques, which typically result in limited transmission power and hence limited coverage area. As a solution to reach the intended far destinations, relaying techniques can be used to improve the performance of underlay cognitive networks in terms of signal-to-noise ratio (SNR). Recently, single best relay selection schemes have been proposed that maintain a desired SNR for the cognitive network while satisfying the interference level at the primary network. However, these schemes suffer from high outage probability especially at low SNR, where the probability of finding a single relay that satisfies both constraints is reduced. Therefore, in this paper, we propose a multiple relay selection scheme, where at each channel realization, we allow for multiple relay selection in case the best relay, among those that satisfy the interference constraint, does not satisfy the desired SNR. In particular, we select the least number of relays whose sum of their individual SNR's achieves the desired level. This scheme leads to a reduced outage probability especially for low SNR. We derive a closed form expression for the cumulative density function (CDF) of the selected relay(s) SNR for a certain number of relays. Simulation results confirm the analytical results and show that the proposed relay(s) selection algorithm in an underlay cognitive environment improves the outage probability and symbol error rate (SER) in low SNR regions.

We have recently introduced adaptive spatial modulation (ASM) [1], which comprises both adaptive modulation (AM) and spatial modulation (SM), with the aim of enhancing the average spectral efficiency (ASE) of multiple antenna systems. This technique was shown to offer high energy efficiency and low system complexity thanks to the use of SM while achieving high data rates thanks to the use of AM. Motivated by this technique and the need of such performance in a cognitive radio (CR) scenario, we extend in this paper the concept of ASM to a spectrum sharing system. In this context, we propose the ASM-CR scheme as an energy-efficient, spectrally-efficient, and low-complexity scheme for CR systems. Compared to selected existing spectrum sharing schemes, ASM-CR is shown to offer a considerable ASE improvement while experiencing a slight degradation in the average bit error rate (ABER) performance. In order to address this, a hybrid scheme compromising between ASE and ABER is proposed. The performance of both proposed schemes is analyzed in terms of ASE and ABER and confirmed with selected numerical results using Monte-Carlo simulations.

The operations of smart metering heavily rely on the communication network for efficient data gathering, thus eliminating manual meter reading. Smart electronic devices are deployed in open, unattended and possibly hostile environment such as consumer's home and office areas, making them particularly vulnerable to physical attacks. Resilience is needed to mitigate such inherent vulnerabilities and risks related to security and reliability. In this article, a general overview of the resilience including definition, metric and resilient techniques relevant for smart metering is presented. A quantitative metric, visual and meaningful, based on the graphical representation is adopted to compare routing protocols in the sense of resilience against active insider attacks. Five well-known routing protocols from the main categories have been studied through simulations and their resilience is evaluated according to the given metric. Resilient techniques introduced to these protocols have enhanced significantly the resilience against attacks providing route diversification.

In this paper, the performance of a visible light communication (VLC) network exploiting power control is considered. The achievable rate region of two VLC communication pairs is characterized. The system employs optical orthogonal frequency division multiplexing (O-OFDM) with power control performed at the transmitters. The optical signal clipping effect is taken into consideration which results from the physical limitations at the transmitters. Also, the system is constrained by the desired illumination power for each transmitter. We prove that the achievable rate region is defined as the union of two regions where the boundary of each of these regions can be obtained by a single variable optimization problem. Our numerical results show the effects of the system parameters including direct current (DC) bias, the desired illumination power, clipping noise and the relative positions of the receivers relative to the LED transmitters on the achievable rate region of the two users. We show the enhancement in the performance resulted from using power control compared to orthogonal resource allocation techniques.

In this work, we present the performance analysis of a dual-hop transmission system composed of asymmetric radio frequency (RF) and free-space optical (FSO) links in underlay cognitive networks. For the RF link, we consider an underlay cognitive network where the secondary users share the spectrum with licensed primary users, where indoor femtocells act as a practical example for such networks. More specifically, we assume that the RF link is subject to an interference constraint. The FSO link accounts for pointing errors and both types of detection techniques (i.e. intensity modulation/direct detection (IM/DD) as well as heterodyne detection). On the other hand, RF link is modeled by the Rayleigh fading distribution that applies power control to maintain the interference at the primary network below a specific threshold whereas the FSO link is modeled by a unified Gamma-Gamma fading distribution. With this model, we derive new exact closed-form expressions for the cumulative distribution function, the probability density function, the moment generating function, and the moments of the end-to-end signal-to-interference plus noise ratio of these systems in terms of the Meijer's G functions. We then capitalize on these results to offer new exact closed-form expressions for the outage probability, the higher-order amount of fading, and the average error rate for binary and Mary modulation schemes, all in terms of Meijer's G functions. All our new analytical results are verified via computer-based Monte-Carlo simulations and are illustrated by some selected numerical results.

Using spatial modulation (SM) jointly with adaptive modulation (AM), we propose a low-complexity and spectrally-efficient transmission scheme in a multiple-input multiple-output (MIMO) system. While in the conventional SM technique a fixed data rate is achieved, the proposed adaptive spatial modulation (ASM) technique is throughput-optimized by taking advantage of the wireless channel variations in order to increase the spectral efficiency of SM. ASM has been previously studied in [1] in order to improve the average bit error rate (ABER) performance of SM while only providing a fixed data rate. On the other hand, the ASM technique is introduced in this paper in order to achieve high data rates while keeping the ABER below a certain threshold. We propose two variations of ASM compromising between the spectral efficiency and the error performance. The ABER and the average spectral performance results of both variations are presented via Monte-Carlo simulations and confirmed with analytical results including asymptotic performance bounds on the ABER. These results show that the proposed ASM techniques come with a considerable spectral efficiency gain compared to SM while only requiring a limited feedback from the receiver.

Heterogeneous networks (HetNets) represent a promising solution for the next generation wireless networks (NGWNs), where many low power, low cost small-cells (e.g., fem-tocells) are planned to support the existing macrocell networks to reduce the over the air signaling and uplink power consumption, and thereby enhance the spectral efficiency compared to the macro-only network. In this context, the massive deployment of many lightly loaded small-cells is anticipated to increase the downlink power consumption of the HetNets. This paper investigates the end-to-end downlink power consumption of the HetNets, which consists of the power consumed by the macrocell and small-cell base stations and the backhaul to carry the traffic from the access to the core network. The downlink power consumption depends probabilistically on the population of the active mobile users in both the macrocell and small-cell networks such that the regulating factor is referred to as active user population factor (AUPF). A mathematical framework is presented to derive AUPF by assuming that the total population of active mobile users is a random variable and has a Binomial probability distribution. The number of active users and small-cells are calculated by the proposed probabilistic traffic model which assures the reduction in downlink power consumption since it now consists of the power consumption due to the base stations and backhaul for only the active population of mobile users. This model helps to evaluate the power consumption of HetNets. The simulations results indicate that AUPF and traffic load have significant impact on the downlink power consumption of HetNets.

Consider a multi-user underlay cognitive network where multiple cognitive users, having limited peak transmit power, concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami-m fading. The interference channel between the secondary users and the primary users is assumed to have Rayleigh fading. The uplink scenario is considered where a single secondary user is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the momentgenerating function, outage performance and the symbol-error-rate performance are derived. The outage performance is also studied in the asymptotic regimes and the generalized diversity gain of this scheduling scheme is derived. Numerical results corroborate the derived analytical results.

With the cell coverage area of current and future mobile networks becoming smaller, heterogeneous small-cell networks (HetSNets), where multiple low-power, low-cost base stations (BSs) complement the existing macrocell infrastructure, are considered constitutive elements of future mobile networks. In this paper, we propose a K-tier HetSNet, where multiple tiers of small-cells are padded between macrocells which in turn expand the network coverage and significantly increase in capacity without compromising the frequency reuse factor. In this context, we derive analytical capacity bounds of the K-tier HetSNets based on the distance of the desired user from its serving BS and all other interfering BSs. It was observed that the upper bound of the capacity becomes tighter as the number of small-cell tiers increases due to the increase in the number of small-cells. Simulation results show the performance of the proposed K-tier HetSNets against the macro-only network in terms of frequency reuse factor, capacity and area spectral efficiency.

In this paper, we investigate the impact of using outdated channel state information for incremental opportunistic relay selection in a spectrum sharing cognitive network. In our work, we present the outage performance of two schemes where the power allocation is based on the instantaneous outdated channel state information and the statistical knowledge of the interference links, referred to as CSI-based scheme and LF-based scheme, respectively. By investigating the effect of the rank of the selected relay and the correlation coefficients imbalance on outage performance, a comparison reveals that LF-based scheme outperforms its CSI-based counterpart. We validate our analysis with simulation results in a Rayleigh fading environment.

Cognitive heterogeneous networks (HetNets) have been recently introduced as a promising solution to meet the user demand for higher data rate. Due to the physical coexistence of microcells, femtocells and the lack of available spectrum, there is a need for techniques that allows users to share the same spectrum while maintaining required performance level for each user by adopting interference mitigation techniques. In this paper, we focus on resource allocation algorithm for orthogonal frequency-division multiple access (OFDMA) cognitive networks using game theory. In particular, we consider supermodular game theory, where given the problem meets specific requirement, the game has two significant features; it has at least one pure Nash Equilibrium (NE) and its best responses are monotonically increasing. Our objective is that each femtocell user selects a specific number of subcarriers determined by its needs. In comparison where at each iteration of the game, the femtocell user search all the subcarriers to maximize its payoff, our algorithm is based on selecting the subcarriers randomly and checks only those subcarriers that achieve higher payoff. Our results show that our algorithm reaches NE and can provide lower feedback compared to the sweeping-all subcarriers.

We consider in this paper, a spectrum sharing cognitive radio system with a ratio selection scheme; where one out of N independent-and-identically-distributed transmit antennas is selected such that the ratio of the secondary transmitter (ST) to the secondary receiver (SR) channel gain to the interference from the ST to the primary receiver (PR) channel gain is maximized. Although previous works considered perfect, outdated, or partial channel state information at the transmitter, we stress that using such assumptions may lead to a feedback overhead for updating the SR with the ST-PR interference channel estimation. Considering only statistical knowledge of the ST-PR channel gain, we investigate a ratio selection scheme using a mean value (MV)-based power allocation strategy referred to as MV-based scheme. We first provide the exact statistics in terms of probability density function and cumulative distribution function of the secondary channel gain as well as of the interference channel gain. Furthermore, we derive exact cumulative density function of the received signal-to-noise ratio at the SR where the ST uses a power allocation based on instantaneous perfect channel state information (CSI) referred to as CSI-based scheme. These statistics are then used to derive exact closed form expressions of the outage probability, symbol error rate, and ergodic capacity of the secondary system when the interference channel from the primary transmitter (PT) to the SR is ignored. Furthermore, an asymptotical analysis is also carried out for the MV-based scheme as well as for the CSI-based scheme to derive the generalized diversity gain for each. Subsequently, we address the performance analysis based on exact statistics of the combined signal-to-interference-plus-noise ratio at the SR of the more challenging case; when the PT-SR interference channel is considered. Numerical results in a Rayleigh fading environment manifest that the MV-based scheme outperforms the CSI-based scheme provided that a low interference power constraint is deployed, implying that the MV-based scheme is more suitable for practical systems.

In this paper, we propose a number of adaptive transmission techniques in order to improve the performance of the secondary link in a spectrum sharing system. We first introduce the concept of minimum-selection maximum ratio transmission (MS-MRT) as an adaptive variation of the existing MRT (MRT) technique. While in MRT all available antennas are used for transmission, MS-MRT uses the minimum subset of antennas verifying both the interference constraint (IC) to the primary user and the bit error rate (BER) requirements. Similar to MRT, MS-MRT assumes that perfect channel state information (CSI) is available at the secondary transmitter (ST), which makes this scheme challenging from a practical point of view. To overcome this challenge, we propose another transmission technique based on orthogonal space-time block codes with transmit antenna selection (TAS). This technique uses the full-rate full-diversity Alamouti scheme in order to maximize the secondary's transmission rate. The performance of these techniques is analyzed in terms of the average spectral efficiency (ASE), average number of transmit antennas, average delay, average BER, and outage performance. In order to give the motivation behind these analytical results, the tradeoffs offered by the proposed schemes are summarized and then demonstrated through several numerical examples.

Cognitive radio systems are a promising solution to the spectrum scarcity problem but accurate modeling of both primary and secondary user activity, spectrum utilization, and system throughput are vital to achieve good performance in such systems. In this paper, we consider a set of primary users that are distributed in space based on a Poisson point process and demand for the available spectrum. We assess the effect of these demands on primary user activity, spectrum occupancy, and total system throughput under various subcarrier-request distributions and fading environments. The asymptotic mean number of active primary users and occupied subcarriers are analytically derived and evaluated further considering the primary network traffic and the average probability of miss-detection of an occupied subcarrier by a single sensing secondary user. It is seen that the average probability of miss-detection is a function of system traffic and the subcarrier-request distribution of primary users and that for extreme primary user traffic, the applied subcarrier-request distribution and total number of provided subcarriers cannot improve further the asymptotic sensing accuracy of the secondary user. Finally, the primary network and the secondary user throughputs in the presence of mutual interference due to imperfect detection of secondary users are investigated and their asymptotic values for large primary network traffic, primary user transmit power, and secondary user transmit power are analytically derived. The results are critically investigated, formulated as theorems and compared with simulations. It is observed that analytical and simulation results are in perfect agreement. It is shown that increasing the primary network transmit power benefits both the primary network and the secondary user throughputs.

Ubiquitous availability of wireless and electronic devices has raised some health alarms among the masses. There exist possible malign effects of electromagnetic radiations on the human body, and especially on the brain due to existence of radio frequency (RF) signals close to the human head. The increased usage of contemporary wireless technologies around us has raised major concerns about their harmful impact on human brain's communication signals (neural oscillations). Thorough investigations are required to answer whether or not these wireless devises and RF signals interfere with human brain's signals and are directly responsible for physiological and behavioral aspects. This answer is mutually valuable for health care providers and technology experts. This paper investigates the effects of RF radiations emitted by electronic devices on the cognition ability of the brain and its behavioral impingement. In this context, this study utilized the Emotiv EEG signal recording tool to study the behavior of the brain's EEG signals both under normal conditions and under the influence of RF signals. The findings are interesting and the experiments have indicated some possible effects and abnormalities due to the RF radiations on the normal conditions and cognition of the brain's signal. Further investigations is anticipated to open a plethora of useful applications and investigations.

This article investigates the usefulness of using two sensors and a blind-separation algorithm in reducing the effect of surface noise in downhole communication systems. The acoustic channel provides a challenging environment for the acoustic waves that propagate from the downhole to the surface of an oil or gas well. As a result, acoustic waves experience a noticeable attenuation before reaching the surface of the well. Consequently, surface noise, which is generated by the surface tools, dominates the performance of acoustic downhole communication systems that have the receiver unit close to the well surface. The application of a two-receiver noise cancellation algorithm is investigated. The article also describes a testbed that was designed to study the effectiveness of the proposed algorithm in reducing the impact of the surface noise. The communication system was built using two speakers, five connected segments of 7 inch production pipes, and two microphones. One of the speakers was used to transmit a noise-like signal in order to simulate the surface noise. The noise cancellation algorithm was applied to the outputs of the two microphones, and the quality of the acoustic signals is investigated after applying the noise cancellation solution. Results of this work emphasize the usefulness of the proposed solution in enhancing the performance of the acoustic downhole communication systems.

Interference cancellation is expected to have significant importance for next-generation wireless communication systems due to various co-channel deployment scenarios and dense frequency reuse. In this study, an interference cancellation receiver that exploits the unique characteristics of single-carrier frequency-division multiple access based systems is proposed. The proposed receiver suppresses the co-channel dominant interference by employing a soft window to the frequency-domain samples where the desired and interfering signals overlap. In order to improve the performance, demodulation and regeneration stages are repeated multiple times by initially accommodating a group of reliable symbols before the iterations. The simulation results indicate that proposed methods work particularly well for low overlap ratios compared to interference coordination and no cancellation methods.

In this paper, we consider a spectrum sharing cognitive radio system with ratio selection using a mean value-based power allocation strategy. We first provide the exact statistics in terms of probability density function and cumulative density function of the secondary channel gain as well as of the interference channel gain. These statistics are then used to derive exact closed form expression of the secondary outage probability. Furthermore, asymptotical analysis is derived and generalized diversity gain is deduced. We validate our analysis with simulation results in a Rayleigh fading environment.

We consider a joint Slepian-Wolf/Dirty-paper coding (SW-DPC) setup where a binary source needs to be transmitted over an additive white-Gaussian channel in the presence of interference known only at the encoder, as well as correlated side-information available only at the decoder. We propose a practical joint SW-DPC framework that uses a single low-density parity-check code coupled with trellis coded quantization to simultaneously provide error protection (in the face of noise and interference) and compression (in the face of correlated side-information available at the decoder). Simulation results indicate that the proposed joint SW-DPC scheme with finite-length codes outperforms a scheme with separate SW and DPC by 0.3 dB. In addition, we show that our joint SW-DPC code designed for one set of channel conditions is capable of achieving negligible bit-error rates for many other channel conditions as well. More specifically, it achieves successful decoding for a wide variety of channel conditions for which a separation-based scheme fails.

Heterogeneous networks (HetNets) are considered as a standard part of the future generation of wireless networks where masses of low power, low cost smallcells (e.g., femtocells) are anticipated to support the existing macrocell networks. While HetNets are increasing the spectral efficiency and decreasing the over-the-air signaling and uplink power consumption compared to macro networks, the large scale deployment of many lightly loaded smallcells is expected to increase the downlink power consumption of the HetNets. This paper studies the impact of smallcell population on the downlink power consumption of the HetNets. In this context, we propose that the population of smallcells is strictly depending on the traffic load due to active mobile users, which is a random variable and time-varying. We derive the mathematical framework to calculate the required population of smallcells based on the probabilistic traffic models where the number of total mobile users and number of active mobile users have different probabilistic distributions such as different combinations of Binomial and Poisson distributions. The proposed method guarantees the reduction in downlink power consumption of HetNets by forcing the smallcells to turn on the sleeping mode under low and medium traffic load conditions. Several simulation results are included to illustrate the impact of traffic load dependent population of smallcells on the downlink power consumption of HetNets. Moreover, it is shown that the mathematical and simulation results are in perfect agreement.

The scarcity of radio spectrum caused the emergence of spectrum sharing systems in which unlicensed users can exploit unused licensed primary bands. Due to unavailability of contiguous unused bands, services requiring large bandwidths can not be supported within unlicensed or cognitive networks. This could be overcome by using few disjoint idle bands and generating a larger bandwidth, also known as spectrum aggregation. In this paper, we analyze idle band integration in a cooperative network using multiple relays between a source-destination pair. We propose a simple protocol which allows some relays in the system to assist the source in aggregating a few idle bands through to the destination. As a whole, this enables the source-destination link to utilize a larger integrated bandwidth. We analyze amplify-and-forward (AF) and decode-and-forward (DF) relaying and derive a generalized closed form expression for the outage probability of the system applicable to both scenarios. We also investigate the system performance under different sets of conditions and discover some important tradeoffs.

This paper proposes a reduced-complexity downlink multi-channel assignment scheme when feedback links are capacity-limited. The system model treats the case when multiple access points are allocated to serve scheduled users in over-loaded (i.e. dense) pico/femtocell networks. It assumes that the deployed access points can be shared simultaneously and employ isotropic antenna arrays of arbitrary sizes. Moreover, they transmit their data on a common physical channel and can not coordinate their transmissions. On the other hand, each scheduled user can be served by single transmit channel from each active access point at a time, and it lacks coordination with concurrent active users. The scheme operates according to the occupancy of available transmit channels, wherein extensively occupied access points are avoided adaptively, while reducing the load of processing. The operation is linked to a target performance via controlling the observed aggregate interference from the projected set of serving points. Through the analysis, results for the scheduled user outage performance, and the average number of active access points are presented. Numerical and simulations studies clarify the gains of the proposed scheme for different operating conditions.

In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation error and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use these expressions to evaluate the outage probability and error probability. Numerical results show that the approximate closed-form expressions are very close to the exact ones.

In cognitive radio (CR) systems, one of the main implementation issues is spectrum sensing because of the uncertainties in propagation channel, hidden primary user (PU) problem, sensing duration and security issues. This paper considers an orthogonal frequency-division multiplexing (OFDM)-based CR spectrum sharing system that assumes random access of primary network subcarriers by secondary users (SUs) and absence of the PU's spectrum utilization information, i.e., no spectrum sensing is employed to acquire information about the PU's activity or availability of free subcarriers. In the absence of information about the PU's activity, the SUs randomly access (utilize) the subcarriers of the primary network and collide with the PU's subcarriers with a certain probability. In addition, inter-cell collisions among the subcarriers of SUs (belonging to different cells) can occur due to the inherent nature of random access scheme. This paper conducts a stochastic analysis of the number of subcarrier collisions between the SUs' and PU's subcarriers assuming fixed and random number of subcarriers requirements for each user. The performance of the random scheme in terms of capacity and capacity (rate) loss caused by the subcarrier collisions is investigated by assuming an interference power constraint at PUs to protect their operation.

In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we first consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation errors and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use them to evaluate the outage probability, error probability, and achievable rate. Subsequently, to investigate the joint effects of the channel estimation error and CCI on the system performance, we extend our analysis to a multiple-relay network and derive several asymptotic performance expressions. For comparison purposes, we also provide the analysis for the relay selection scheme under the total power constraint at the relays. For AF TWRN with channel estimation error and CCI, numerical results show that the performance of the relay selection scheme is not always better than that of the all-relay participating case. In particular, the relay selection scheme can improve the system performance in the case of high power levels at the sources and small powers at the relays.

This paper proposes a unifying variational approach for proving and extending some fundamental information theoretic inequalities. Fundamental information theory results such as maximization of differential entropy, minimization of Fisher information (Cramér-Rao inequality), worst additive noise lemma, entropy power inequality, and extremal entropy inequality are interpreted as functional problems and proved within the framework of calculus of variations. Several applications and possible extensions of the proposed results are briefly mentioned.

In spectrum sharing systems, a secondary user (SU) is allowed to share the spectrum with a primary (licensed) network under the condition that the interference observed at the receivers of the primary users (PU-Rxs) is below a predetermined level. In this paper, we consider a secondary network comprised of a secondary transmitter (SU-Tx) equipped with multiple antennas and a single-antenna secondary receiver (SU-Rx) sharing the same spectrum with multiple primary users (PUs), each with a distinct spectrum. We develop transmit antenna diversity schemes at the SU-Tx that exploit the multi-spectrum diversity provided by the existence of multiple PUs so as to optimize the signal-to-noise ratio (SNR) at the SU-Rx. In particular, assuming bounded transmit power at the SU-Tx, we develop switched selection schemes that select the primary spectrum and the SU-Tx transmit antenna that maintain the SNR at the SU-Rx above a specific threshold. Assuming Rayleigh fading channels and binary phase-shift keying (BPSK) transmission, we derive the average bit-error-rate (BER) and average feedback load expressions for the proposed schemes. For the sake of comparison, we also derive a BER expression for the optimal selection scheme that selects the best antenna/spectrum pair that maximizes the SNR at the SU-Rx, in exchange of high feedback load and switching complexity. Finally, we show that our analytical results are in perfect agreement with the simulation results.

Cooperative relay technology was recently introduced into cognitive radio networks in order to enhance network capacity, scalability, and reliability of end-to-end communication. In this paper, we investigate an underlay cognitive network where the quality of service of the secondary link is maintained by triggering an opportunistic regenerative relaying once it falls under an unacceptable level. We first provide the exact cumulative density function (CDF) of received signal-to-noise (SNR) over each hop with co-located relays. Then, the CDFs are used to determine very accurate closed-form expression for the outage probability for a transmission rate R. We validate our analysis by showing that simulation results coincide with our analytical results in Rayleigh fading channels.

Cognitive networks in underlay settings operate simultaneously with the primary networks satisfying stringent interference limits. This condition forces them to operate with low transmission powers and confines their area of coverage. In an effort to reach remote destinations, underlay cognitive sources make use of relaying techniques. Selecting the best relay among those who are ready to cooperate is different in underlay settings than traditional non-cognitive networks. In this paper, we present a relay selection scheme which uses the quotient of the relay link signal to noise ratio (SNR) and the interference generated from the relay to the primary user to choose the best relay. The proposed scheme optimizes this quotient in a way to maximize the relay link SNR above a certain value whereas the interference is kept below a defined threshold. We derive closed expressions for the outage probability and bit error probability of the system incorporating this scheme. Simulation results confirm the validity of the analytical results and reveal that the relay selection in cognitive environment is feasible in low SNR regions.

Best relay selection is a bandwidth efficient technique for multiple relay environments without compromising the system performance. The problem of relay selection is more challenging in underlay cognitive networks due to strict interference constraints to the primary users. Generally, relay selection is done on the basis of maximum end-to-end signal to noise ratio (SNR). However, it requires large amounts of channel state information (CSI) at different network nodes. In this paper, we present and analyze a reactive relay selection scheme in underlay cognitive networks where the relays are operating with fixed gains near a primary user. The system model minimizes the amount of CSI required at different nodes and the destination selects the best relay on the basis of maximum relay to destination SNR. We derive close form expressions for the received SNR statistics, outage probability, bit error probability and average channel capacity of the system. Simulation results are also presented to confirm the validity of the derived expressions.

This paper illustrates the equivalence between two fundamental results: Stein identity, originally proposed in the statistical estimation realm, and de Bruijn identity, considered for the first time in the information theory field. Two distinctive extensions of de Bruijn identity are presented as well. For arbitrary but fixed input and noise distributions, the first-order derivative of differential entropy is expressed by means of a function of the posterior mean, while the second-order derivative of differential entropy is manifested in terms of a function of Fisher information. Several applications exemplify the utility of the proposed results.

This paper focuses on developing an alternative proof for an extremal entropy inequality, originally presented in [1]. The proposed alternative proof is simply based on the classical entropy power inequality and the data processing inequality. Compared with the proofs in [1], the proposed alternative proof is simpler, more direct, and information theoretic, and presents the advantage of providing the structure of the optimal solution covariance matrix. Also, the proposed proof might also be used as a novel method to address applications such as calculation of the vector Gaussian broadcast channel capacity, establishing a lower bound for the achievable rate of distributed source coding with a single quadratic distortion constraint, and the secrecy capacity of the Gaussian wire-tap channel.

Cognitive Radio systems are a promising solution to the spectrum scarcity problem, but precise modeling of spectrum utilization is vital to the analysis and design of such systems. In this paper, we mathematically derive the Probability Mass Function (PMF) of the fraction of available subcarriers for the secondary users in an OFDMA based cognitive radio system for different requesting distributions. The PMF of the total number of requested subcarriers from all primary users is derived and the effect of the requesting distribution on the asymptotic spectrum availability for secondary users is studied. It is shown that if a requesting distribution is undesired, providing more subcarriers will not increase the spectrum availability for the secondary network.

Selective cooperation is a well investigated technique in non-cognitive networks for efficient spectrum utilization and performance improvement. However, it is still a nascent topic for underlay cognitive networks. Recently, it was investigated for underlay networks where the secondary nodes were able to adapt their transmit power to always satisfy the interference threshold to the primary users. This is a valid assumption for cellular networks but many non-cellular devices have fixed transmit powers. In this situation, selective cooperation poses a more challenging problem and performs entirely differently. In this paper, we extend our previous work of selective cooperation based on either hop's signal to noise ratio (SNR) with fixed gain and fixed transmit power relays in an underlay cognitive network. This work lacked in considering the primary interference over the cognitive network and presented a rather idealistic analysis. This paper deals with a more realistic system model and includes the effects of primary interference on the secondary transmission. We first derive end-to-end signal to interference and noise ratio (SINR) expression and the related statistics for a dual-hop relay link using asymptotic and approximate approaches. We then derive the statistics of the selected relay link based on maximum end-to-end SINR among the relays satisfying the interference threshold to the primary user. Using this statistics, we derive closed form asymptotic and approximate expressions for the outage probability of the system. Analytical results are verified through simulations. It is concluded that selective cooperation in underlay cognitive networks performs better only in low to medium SNR regions.

Spectrum sharing systems have been introduced to alleviate the problem of spectrum scarcity by allowing secondary unlicensed networks to share the spectrum with primary licensed networks under acceptable interference levels to the primary users. In this paper, we develop interference-aware random beam selection schemes that provide enhanced throughput for the secondary link under the condition that the interference observed at the primary link is within a predetermined acceptable value. For a secondary transmitter equipped with multiple antennas, our schemes select a random beam, among a set of power- optimized orthogonal random beams, that maximizes the capacity of the secondary link while satisfying the interference constraint at the primary receiver for different levels of feedback information describing the interference level at the primary receiver. For the proposed schemes, we develop a statistical analysis for the signal-to-noise and interference ratio (SINR) statistics as well as the capacity of the secondary link. Finally, we present numerical results that study the effect of system parameters including number of beams and the maximum transmission power on the capacity of the secondary link attained using the proposed schemes.

In a spectrum sharing underlay context, we investigate the exact derivation of the outage probability for relay-aided cognitive radio communications. To give more degrees of freedom to the secondary system in acquiring a targeted quality-of-service (QoS) under the primary system interference constraint, the secondary link is assisted by a set of relays acting in a two-hop decode-and-forward selective relaying mode. By means of the cumulative distribution functions of the received signal-to-noise ratio (SNR) at the secondary receiver, we derive the end-to-end outage probability of the secondary system in its closed form. The analytical and simulation results are then compared and interestingly shown to perfectly match over the entire interference threshold region.

In a communication system with multiple cooperative relays, selecting the best relay utilizes the available spectrum more efficiently. However, selective relaying poses a different problem in underlay cognitive networks compared to the traditional cooperative networks due to interference thresholds to the primary users. In most cases, a best relay is the one which provides the maximum end-to-end signal to noise ratio (SNR). This approach needs plenty of instantaneous channel state information (CSI). The CSI burden could be reduced by partial relay selection. In this paper, a partial relay selection scheme is presented and analyzed for an underlay cognitive network with fixed gain relays operating in the vicinity of a primary user. The system model is adopted in a way that each node needs minimal CSI to perform its task. The best relay is chosen on the basis of maximum source to relay link SNR which then forwards the message to the destination. We derive closed form expressions for the received SNR distributions, system outage, probability of bit error and average channel capacity of the system. The derived results are confirmed through simulations.

In this paper, we consider a distributed beamforming scheme (DBF) in a spectrum sharing system where multiple secondary users share the spectrum with the licensed primary users under an interference temperature constraint. We assume that DBF is applied at the secondary users. We first consider optimal beamforming and compare it with the user selection scheme in terms of the outage probability and bit-error rate performance. Since perfect feedback is difficult to obtain, we then investigate a limited feedback DBF scheme and develop an outage probability analysis for a random vector quantization (RVQ) design algorithm. Numerical results are provided to illustrate our mathematical formalism and verify our analysis.

Under the scenario of an underlay cognitive radio network, we propose in this paper two adaptive schemes using switched transmit diversity and adaptive modulation in order to increase the spectral efficiency of the secondary link and maintain a desired performance for the primary link. The proposed switching efficient scheme (SES) and bandwidth efficient scheme (BES) use the scan and wait combining technique (SWC) where a transmission occurs only when a branch with an acceptable performance is found, otherwise data is buffered. In these schemes, the modulation constellation size and the used transmit branch are determined to minimize the average number of switched branches and to achieve the highest spectral efficiency given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver (PR). For delay-sensitive applications, we also propose two variations of the SES and BES schemes using power control (SES-PC and BES-PC) where the secondary transmitter (ST) starts sending data using a nominal power level which is selected in order to minimize the average delay introduced by the SWC technique. We demonstrate through numerical examples that the BES scheme increases the capacity of the secondary link when compared to the SES scheme. This spectral efficiency improvement comes at the expense of an increased average number of switched branches and thus an increased average delay. We also show that the SES-PC and the BES-PC schemes minimize the average delay while satisfying the same spectral efficiency as the SES and BES schemes, respectively.

In this paper, taking into account realistic propagation conditions, namely, spatial correlation, keyhole channels, and unequal-power co-channel interference, we investigate the performance of a wireless relay network where all the nodes are equipped with multiple antennas. Considering channel state information assisted amplify-and-forward protocol, we present analytical expressions for the symbol error rate (SER) and outage probability. More specifically, we first derive the SER expressions of a relay system with orthogonal space-time block coding (OSTBC) over correlated/keyhole fading channels. We also analyze the outage probability of interference corrupted relay systems with maximal ratio combing (MRC) at the receiver as well as multiple-input multiple-output MRC (MIMO MRC). Numerical results are given to illustrate and verify the analytical results.

This paper focuses on illustrating 1) the equivalence between Stein's identity and De Bruijn's identity, and 2) two extensions of De Bruijn's identity. First, it is shown that Stein's identity is equivalent to De Bruijn's identity under additive noise channels with specific conditions. Second, for arbitrary but fixed input and noise distributions under additive noise channels, the first derivative of the differential entropy is expressed by a function of the posterior mean, and the second derivative of the differential entropy is expressed in terms of a function of Fisher information. Several applications over a number of fields, such as signal processing and information theory, are presented to support the usefulness of the developed results in this paper.

In this paper we develop a framework for optimizing the performance of the secondary link in terms of the average spectral efficiency assuming quantized channel state information (CSI) of the secondary and the secondary-to-primary interference channels available at the secondary transmitter. We consider the problem under the constraints of maximum average interference power levels at the primary receiver. We develop a sub-optimal computationally efficient iterative algorithm for finding the optimal CSI quantizers as well as the discrete power and rate employed at the cognitive transmitter for each quantized CSI level so as to maximize the average spectral efficiency. We show via analysis and simulations that the proposed algorithm converges for Rayleigh fading channels. Our numerical results give the number of bits required to sufficiently represent the CSI to achieve almost the maximum average spectral efficiency attained using full knowledge of the CSI.

ABSTRACT Cognitive radio (CR) with spectrum‐sharing feature is a promising technique to address the spectrum under‐utilization problem in dynamically changing environments. In this paper, the achievable capacity gain of spectrum‐sharing systems over dynamic fading environments is studied. To perform a general analysis, a theoretical fading model called hyper‐fading model that is suitable to the dynamic nature of CR channel is proposed. Closed‐form expressions of probability density function (PDF) and cumulative density function (CDF) of the signal‐to‐noise ratio (SNR) for secondary users (SUs) in spectrum‐sharing systems are derived. In addition, the capacity gains achievable with spectrum‐sharing systems in high and low power regions are obtained. The effects of different fading figures, average fading powers, interference temperatures, peak powers of secondary transmitters, and numbers of SUs on the achievable capacity are investigated. The analytical and simulation results show that the fading figure of the channel between SUs and primary base‐station (PBS), which describes the diversity of the channel, does not contribute significantly to the system performance gain. Copyright © 2011 John Wiley & Sons, Ltd.

In this paper, we analyze the performance of a dual- hop system with partial relay selection and feedback delay over Rayleigh fading channels in the presence of multiple identical interferers at the destination. Based on the new closed-form expressions for the cumulative distribution function of the effective signal-to-interference plus noise ratio, we present closed-form expressions for the outage probability and average symbol error rates for both fixed and CSI-assisted gain relaying systems. To gain further insights, the asymptotic outage probability and average symbol error rates at the high signal to noise ratio regimes are examined. Monte-Carlo simulation results confirm the accuracy of the our analytical results.

Recently, the maximum likelihood estimator (MLE) and Cramer-Rao Lower Bound (CRLB) were proposed with the goal of maximizing and assessing the synchronization accuracy in wireless sensor networks (WSNs). Because the network delays may assume any distribution and the performance of MLE is quite sensitive to the distribution of network delays, designing clock synchronization algorithms that are robust to unknown network delay distributions appears as an important problem. By adopting a Bayesian framework, this paper proposes a novel clock synchronization algorithm, called Iterative Gaussian Mixture Kalman Particle Filter (IGMKPF), which is shown to achieve good and robust performance in the presence of unknown net work delay distributions. The Posterior Cramer-Rao Bound (PCRB) and the Mean-Square Error (MSE) of IGMKPF are evaluated and shown to exhibit improved performance and robustness relative to MLE.

In this paper, we investigate the performance of a dual-hop amplify-and-forward relay system in Nakagami-\emph{m} fading channels in the presence of multiple interferers. Based on the new closed-form expression for the cumulative distribution function of a new type of random variable involving a number of independent gamma random variables, we present closed-form expressions for the outage probability, general moments for the end-to-end signal to interference and noise ratio and ergodic capacity of the system. In addition, we look into the high signal to noise ratio regime and characterize the diversity order and coding gain achieved by the system. Our result shows that the diversity of the system is limited by the hop experiencing more severer fading. Moreover, the interference does not reduce the diversity order of the system, instead, it degrades the outage performance by affecting the coding gain of the system.

In this study, the behavior of interference is investigated for cellular mobile radio networks. More explicitly, this work focuses on examining how interference evolves with respect to time under long and short term fading together for the uplink of an FDD system. The results show that decorrelation distance of shadowing plays a crucial role in predicting future interference conditions. Given the initial interference measurement, it is shown that the future interference levels are highly dependent on maintaining the decorrelation distance through the observation interval. On the one hand, if the observation interval is kept too short in a mobile environment, then a drastic deviation in the new interference level from the previous one is not expected. On the other hand, if the observation interval is kept too long, then spatial correlation of shadowing loses its significance and drastic deviations are more likely in the new interference levels; furthermore, path loss might dominate the interference status due to longer displacements.

Inefficient spectrum usage is a crucial issue in wireless communications and methods for dynamic spectrum access are proposed based on spectrum sensing methodology of the cognitive radio systems. Beside the detection and estimation methods, spectrum sensing procedures can also benefit from the modeling and prediction of the wireless spectrum usage. Markovian, regressive and other approaches are introduced for time or frequency domain channel modeling however, the research on the spectrum allocation methods indicates that location information has also an important influence on the spectrum occupancy characterization. In this paper, linear autoregressive prediction approach for binary time series is employed to investigate channel occupancy prediction performance based on spectrum measurements conducted in four different locations synchronously. Through the modeling procedure, dependency in frequency domain is also taken into consideration by modeling the adjacent frequency bands together. The model order is selected based on mean residual magnitudes and Akaike information criterion, mode order parameters are tabulated, and comparative prediction analysis considering the observation time is given for each location. The performance of the proposed linear modeling method is also compared with continuous-time Markov chain modeling in one of the locations.

Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using switched transmit diversity and adaptive modulation in order to increase the spectral efficiency of the secondary link. The proposed bandwidth efficient scheme (BES) uses the scan and wait (SWC) combining technique where a transmission occurs only when a branch with an acceptable performance is found, otherwise data is buffered. In our scheme, the modulation constellation size and the used transmit branch are determined to achieve the highest spectral efficiency given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver. Selected numerical examples show that the BES scheme increases the capacity of the secondary link when compared to an existing switching efficient scheme (SES). This spectral efficiency comes at the expense of an increased average number of switched branches and thus an increased average delay.

In this paper, we study applying dual branch transmit switch-and-stay combining (SSC) technique for underlay cognitive radio (UCR) networks. In UCR, the secondary user is allowed to share the spectrum with the primary (licensed) user under the condition that interference at the primary receiver is below a predetermined threshold. Assuming binary phase-shift keying (BPSK) modulation and Rayleigh fading channels, we develop a closed form expression for the average bit error rate (BER) of the secondary link as a function of the switching threshold. We then find a closed form expression for the optimal switching threshold in the sense of minimizing the average BER. For the sake of comparison we derive an expression for the average BER of the dual branch transmit selection combining (SC) technique. We finally investigate the effect of correlation between secondary and interference channels on the average BER and the associated optimal switching threshold.

Spectrum sensing is one of the most essential characteristics of cognitive radios (CRs). Robustness and adaptation to varying wireless propagation scenarios without compromising the sensing accuracy are desirable features of any spectrum sensing method to be deployed in CR systems. In this study, an online adaptive cooperation technique for spectrum sensing is proposed in order to maintain the level of reliability and performance. Cooperation is achieved by sensors which employ energy detection. These sensors send their output to a center where data fusion operation is carried out in an online and adaptive manner. Adaptation is realized by the use of orthogonal projections onto convex sets (POCS). In conjunction with the proposed method, an end-to-end methodology for a flexible experimental setup is also proposed in this study. This setup is arranged to emulate the proposed adaptive cooperation scheme for spectrum sensing and validate its practical use in cognitive radio systems. Comparative performance results for both inphase and quadrature branches are presented.

In this letter, we investigate the performance of dual-hop channel state information-assisted amplify-and-forward relaying systems over Nakagami-mfading channels in the presence of multiple interferers at the relay. Assuming integer fading parameterm, we derive closed-form expressions for the exact outage probability and accurate approximation for symbol error rate of the system. Furthermore, we look into the asymptotical high signal to noise ratio regime, and characterize the diversity order achieved by the system. All the analytical results are validated via Monte Carlo simulations.

Adaptive modulation and diversity combining represent very important adaptive solutions for future generations of wireless communication systems. Indeed, in order to improve the performance and the efficiency of these systems, these two techniques have been recently used jointly in new schemes named joint adaptive modulation and diversity combining (JAMDC) schemes. Considering the problem of finding low hardware complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario and capitalizing on some of these recently proposed JAMDC schemes, we propose and analyze in this paper three joint adaptive modulation, diversity combining, and power control (JAMDCPC) schemes where a constant-power variable-rate adaptive modulation technique is used with an adaptive diversity combining scheme and a common power control process. More specifically, the modulation constellation size, the number of combined diversity paths, and the needed power level are jointly determined to achieve the highest spectral efficiency with the lowest possible processing power consumption quantified in terms of the average number of combined paths, given the fading channel conditions and the required bit error rate (BER) performance. In this paper, the performance of these three JAMDCPC schemes is analyzed in terms of their spectral efficiency, processing power consumption, and error-rate performance. Selected numerical examples show that these schemes considerably increase the spectral efficiency of the existing JAMDC schemes with a slight increase in the average number of combined paths for the low signal-to-noise ratio range while maintaining compliance with the BER performance and a low radiated power which yields to a substantial decrease in interference to co-existing users and systems.

Cognitive radio is regarded as a novel approach for improving the utilization of precious radio spectrum resource. The detection of very low signal-to-noise ratio (SNR) signals with relaxed a priori information on the signal parameters is of high importance to such radios. This paper proposes a detection algorithm based on the first-order cyclostationarity for amplitude modulated (AM) signals that only requires rough information on the signal bandwidth and carrier frequency. A theoretical asymptotic analysis is performed. Simulation results show that the proposed algorithm performs well at low SNRs.

In this paper, we investigate the performance of a cooperative relay network performing location estimation through time of arrival (TOA). We derive Cramer-Rao lower bound (CRLB) for the location estimates using the relay network. The analysis is extended to obtain average CRLB considering the signal fluctuations in both relay and direct links. The effects of the channel fading of both relay and direct links and amplification factor and location of the relay node on average CRLB are investigated. Simulation results show that the channel fading of both relay and direct links and amplification factor and location of relay node affect the accuracy of TOA based location estimation.

Spectrum sensing is one of the most important tasks of cognitive radios (CRs) in future wireless systems and of user equipments (UEs) in next generation wireless networks (NGWNs). Therefore, deciding whether a specific portion of radio frequency (RF) spectrum is occupied or not is of paramount importance for all sorts of future wireless communications systems. In this study, a spectrum sensing method that employs a second-order statistical approach is proposed for detecting fast fading signals in spatially correlated shadowing environments. Analysis and performance results are presented along with the discussion related to the performance comparison of energy detection method.

A sender-receiver paradigm, in which a master and slave node exchange timing packets to estimate the clock offsets of the slave node and other nodes located in the common broadcast region of master and slave nodes, is adopted herein for synchronizing the clocks of individual nodes in a wireless sensor network (WSN). The maximum likelihood estimate of the clock offset of the listening node hearing the broadcasts from both the master and slave nodes was derived, assuming symmetric exponential link delays. This paper advances those results in two directions. First, some improved estimators, each being optimal in its own class, are derived for the clock offset of the listening node and mean link delays. Second, the results are generalized by addressing the more realistic problem of clock offset estimation under asymmetric exponential delays. The results presented in this paper are important for time synchronization of WSNs, where these techniques can be utilized to achieve accurate clock estimates with reduced power consumption.

For many applications, distributed networks require the local clocks of the constituent nodes to run close to an agreed upon notion of time. Most of the widely used clock synchronization algorithms in such systems employ the sender-receiver protocol based on a two-way timing message exchange paradigm. Maximum likelihood estimator (MLE) of the clock offset based on the timing message exchanges between two clocks was derived in D. R. Jeske, On maximum likelihood estimation of clock offset[IEEE Trans. Commun., vol. 53, pp. 53-54, Jan. 2005], when the fixed delays are symmetric and the variable delays in each direction assume an exponential distribution with an unknown mean. Herein, the best linear unbiased estimate using order statistics (BLUE-OS) of the clock offset between two nodes is derived assuming both symmetric and asymmetric exponential network delays, respectively. The Rao-Blackwell-Lehmann-Scheffe¿ theorem is then exploited to obtain the minimum variance unbiased estimate (MVUE) for the clock offset which it is shown to coincide with the BLUE-OS. In addition, it is found that the MVUE of the clock offset in the presence of symmetric network delays also coincides with the MLE. Finally, in the presence of asymmetric network delays, although the MLE is biased, it is shown to achieve lesser mean-square error (MSE) than the MVUE in the region around the point where the bidirectional network link delays are symmetric and hence its merit as the most versatile estimator is fairly justified.

Cognitive radio with spectrum sharing feature is a promising technique to address the spectrum under-utilization problem in dynamically changing environments. In this paper, achievable capacity gain of spectrum sharing systems over dynamic fading environments is studied. For the analysis, a theoretical fading model called hyper fading model that is suitable to the dynamic nature of cognitive radio channel is proposed. Closed-form expression of probability density function (PDF) and cumulative density function (CDF) of the signal-to-noise ratio (SNR) for secondary users in spectrum sharing systems are derived. In addition, the capacity gains achievable with spectrum sharing systems in high and low power regions are obtained. Numerical simulations are performed to study the effects of different fading figures, average powers, interference temperature, and number of secondary users on the achievable capacity.

In this paper, we consider the effect of feedback error on the performance of the joint adaptive modulation and diversity combining (AMDC) scheme which was previously studied with an assumption of perfect feedback channels. In order to compensate for the performance degradation due to feedback error, we propose the path adjustment algorithm for diversity combining. We quantify the performance of the joint AMDC scheme in the presence of feedback error, in terms of the average spectral efficiency, the average number of combined paths, and the average bit error rate. Selected numerical examples are presented and discussed to illustrate the effectiveness of the proposed feedback error compensation strategy with adaptive combining.

Cognitive Radio (CR) systems with spectrum awareness feature is a promising approach to use spectrum effectively. However, accurate modeling of spectrum utilization is crucial for the development and performance evaluation of such systems. Hence, in this paper, a wideband multidimensional spectrum occupancy measurement campaign is conducted to study the evolution of RF spectrum over time, frequency, and space dimensions simultaneously. The measurements are performed over three consecutive days considering 700-3000 MHz frequency band at four different locations concurrently. The measurement results show low utilization of the 700-3000 MHz frequency band with different utilization percentage at each location. Furthermore, the measurements confirm that the spectrum occupancy highly depends on the time, frequency, and location. As a result, multidimensional spectrum measurement and analysis are vital for accurate spectrum utilization modeling and performance evaluation of CR systems.

Adaptive modulation and diversity combining represent very important adaptive solutions for the future generations of communication systems. In order to improve the performance and the efficiency of wireless communication systems these two techniques have been recently used jointly in new schemes named joint adaptive modulation and diversity combining (JAMDC) schemes. Considering the problem of finding low-complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario and capitalizing on one of these recently proposed JAMDC schemes, we propose and analyze in this paper two fully joint adaptive modulation, diversity combining, and power control (FJAMDC) schemes. More specifically, the modulation constellation size, the number of combined diversity paths, and the needed power level are jointly determined to achieve the highest spectral efficiency with the lowest possible combining complexity, given the fading channel conditions and the required error rate performance. Selected numerical examples show that the newly proposed schemes considerably increase the spectral efficiency with a slight increase in the average number of combined path for the low signal to noise ratio (SNR) range while maintaining compliance with the bit error rate (BER) performance and a low radiated power which yields to a substantial decrease in interference to co-existing systems/users.

Location awareness is a prominent feature of cognitive radio (CR) systems. In order to support goal driven and autonomous location aware applications using CR systems, range accuracy adaptation is an essential task. Therefore, in this paper, performance analysis of optimal maximum likelihood (ML) time of arrival (TOA) range accuracy adaptation technique is conducted to study performance limits of location aware systems. The performance of ML-TOA range accuracy adaptation method is evaluated in dynamic spectrum access environments through computer simulations. The results show that range accuracy adaptation can be achieved by ML-TOA method with a relative error for each desired range accuracy.

We propose and analyze in this letter new finger management techniques which are applicable for RAKE receivers operating in the soft handover region. These schemes employ "distributed" types of generalized selection combining (GSC) and minimum selection GSC schemes in order to minimize the impact of sudden connection loss of one of the active base stations. By accurately quantifying the average error rate, we show through numerical examples that our newly proposed distributed schemes offer a clear advantage in comparison with their conventional counterparts.

This letter investigates the effect of feedback error on the performance of the joint adaptive modulation and diversity combining (AMDC) scheme which was previously studied with an assumption of error-free feedback channels. We also propose to utilize adaptive diversity to compensate for the performance degradation due to feedback error. We accurately quantify the performance of the joint AMDC scheme in the presence of feedback error, in terms of the average number of combined paths, the average spectral efficiency, and the average bit error rate. Selected numerical examples are presented and discussed to illustrate the effectiveness of the proposed feedback error compensation strategy with adaptive combining. It is observed that the proposed compensation strategy can offer considerable error performance improvement with little loss in processing power and spectral efficiency in comparison with the no compensation case.

Exploiting multi-user diversity is one solution to efficiently use the wireless medium. The basic principle is to assign the resources to the user experiencing the best channel conditions based on a feedback information provided by different users. In this paper, we propose three multiuser scheduling schemes which are combinations between the switch and examine transmission scheme in the network layer and the joint minimum-selection generalized selection combining and adaptive modulation in the physical layer. As a first step, fairness of access is not taken into account in the design of the proposed scheduling schemes. Then, in a second step, the proposed schemes are modified in order to enable them to achieve a certain short term fairness of access. In both cases, we study the performance of the proposed schemes in terms of spectral efficiency, feedback load and rate, and average number of combined and estimated paths. Using some selected numerical examples, the proposed schemes are compared among themselves and also to some recently published schemes.

In this paper, we propose two new threshold based parallel multiuser scheduling schemes, namely (i) an on-off based scheduling (OOBS) scheme and (ii) a switched based scheduling (SBS) scheme. The objective is to reduce the complexity of implementation without a considerable performance loss in comparison with conventional selection based scheduling. While the OOBS scheme schedules all the users with an SNR above a fixed preselected signal to noise ratio (SNR) threshold, the SBS scheme schedules only the Ksusers with an acceptable SNR if there are enough acceptable users. Otherwise, the scheduler selects the best Ksusers. We analyze statistical characteristics and performances of these proposed schemes. Numerical results show that the proposed schemes can offer some decrease in the average feedback load without an important degradation in average bit error rate and average spectral efficiency.

In this paper, we propose threshold-based power allocation algorithms for a recently proposed down-link parallel multiuser scheduling (SBS) scheme. The proposed algorithms re-allocate the extracted excess transmit power from some acceptable users to those unacceptable users among scheduled users. After the power allocation process, more unacceptable users will enjoy acceptable link reliability as the number of effective acceptable users with an acceptable receive SNR level among the scheduled users is increased without any additional down-link transmit power. Some selected numerical results, show that the proposed power allocation algorithms offer a certain improvement in average spectral efficiency (ASE) and an increase in the average number of effective acceptable users. Although the average bit error rate (BER) performance degrades, especially when the average SNR is close to the SNR threshold, this average BER performance still meets the average BER requirement.

We analyze the performance of the hard handoff algorithm used in the 1xEV-DO Rev. A systems. A theoretical approach is presented to calculate the slot error probability (SEP). The approach enables us to evaluate the effects of filtering, hysteresis as well as the system introduced delay of handoff execution. Unlike previous work the model used considers multiple base stations (BS) and accounts for correlation of shadow fading affecting different signal powers received from different BS's. The theoretical results are verified over ranges of parameters of practical interest using simulations which are also used to evaluate the packet error rate (PER) and the number of handoffs.

In this paper, the time-space correlation function for narrowband MIMO channels is derived. We consider two 3D models, the cylinder model and the sphere model. In both cases, Rician fading is assumed. Scatterers are assumed around the mobile station alone to model macrocell situation. The results show that under reasonable assumptions, both models simplify to the 2D model proposed in (Abdi et al., 2002). Eventually, the construction of the correlation matrix used in the vector autoregressive (VAR) simulation method is studied.

We propose and analyze new finger assignment schemes which are applicable for RAKE reception in the soft handover region. These schemes rely on variants of the conventional generalized selection combining (GSC) and the minimum selection GSC schemes in order to choose an acceptable base station and its corresponding paths. Relying on some recently derived results on order statistics, we investigate the average error rate performance as well as the average number of estimated and combined paths of the proposed schemes over independent and identically distributed Rayleigh fading channels. The mathematical formalism is illustrated with few selected numerical results that show the tradeoff between performance and processing power consumption.

This paper investigates the effect of feedback error on the performance of the joint adaptive modulation and diversity combining (AMDC) scheme which was previously studied with an assumption of error-free feedback channels. We also propose to utilize adaptive diversity to compensate for the performance degradation due to feedback error. We accurately quantify the performance of the joint AMDC scheme in the presence of feedback error, in terms of the average number of combined paths, the average spectral efficiency, and the average bit error rate. Selected numerical examples are presented and discussed to illustrate the effectiveness of the proposed feedback error compensation strategy with adaptive combining. It is observed that the proposed compensation strategy can offer considerable error performance improvement with little loss in processing power and spectral efficiency in comparison with the no compensation case.

We propose and analyze in this paper a new finger assignment technique that is applicable for RAKE receivers when they operate in the soft handover (SHO) region. This scheme employs a new version of generalized selection combining (GSC). More specifically, in the SHO region, the receiver uses by default only the strongest paths from the serving base station (BS) and only when the combined signal-to-noise ratio (SNR) falls below a certain pre-determined threshold, the receiver uses more resolvable paths from the target BS to improve the performance. Hence, relying on some recent results on order statistics we attack the statistics of two correlated GSC stages and provide the approximate but accurate closed-form expressions for the statistics of the output SNR. By investigating the tradeoff among the error performance, the path estimation load, and the SHO overhead, we show through numerical examples that the new scheme offers commensurate performance in comparison with more complicated GSC-based diversity systems while requiring a smaller estimation load and SHO overhead.

We propose and analyze in this paper two new adaptive power controlled minimum selection generalized selection combining (MS-GSC) diversity schemes. The key idea behind these two schemes is to request the transmitter to vary its power level during very adverse channel conditions in order to communicate with the minimum required quality of service. For each scheme, four power control variants accounting for practical implementation constraints including discrete power levels and transmitter gain saturation are proposed and studied. Selected numerical examples, show that ideal continuous power control lowers the average bit error rate of MS-GSC and makes it always meet the specified target quality of service at the expense of an increase in the transmitter gain. Additional numerical examples, show that the power control variants that take into account practical implementation constraints conserve the main features of the ideal continuous power algorithm.

We propose and analyze new finger assignment techniques that are applicable for RAKE receivers in the soft handover (SHO) region. Specifically, extending the results for the case of two-base station (BS), we consider the multi-BS situation, attack the statistics of several correlated generalized selection combining (GSC) stages, and provide closed-form expressions for the statistics of the output signal-to-noise ratio (SNR). By investigating the tradeoff among the error performance, the average number of required path estimations/comparisons, and the SHO overhead, we show through numerical examples that the new schemes offer commensurate performance in comparison with more complicated GSC-based diversity systems while requiring a smaller estimation load and SHO overhead.

We propose and analyze a new finger replacement technique that is applicable for RAKE receivers in the soft handover (SHO) region. More specifically, the receiver uses in the SHO region by default the strongest paths from the serving base station (BS) and only when the combined signal-to-noise ratio falls below a certain pre-determined threshold, the receiver uses more resolvable paths from the target BS to improve the performance. Instead of changing the configuration for all fingers, the receiver just compares the sum of the weakest paths out of the currently connected paths from the serving BS with the sum of the strongest paths from the target BS and selects the better group. Using accurate statistical analysis, we investigate in this letter the tradeoff between error performance, average number of required path comparisons, and SHO overhead offered by this newly proposed scheme.

We propose and analyze new finger assignment schemes which are applicable for RAKE reception in the soft handover region. These schemes rely on variants of the conventional generalized selection combining (GSC) and the minimum selection GSC schemes in order to choose an acceptable base station and its corresponding paths. Relying on some recently derived results on order statistics, we investigate the average error rate performance as well as the average number of estimated and combined paths of the proposed schemes over independent and identically distributed Rayleigh fading channels. The mathematical formalism is illustrated with few selected numerical results that show the tradeoff between performance and processing power consumption.

This letter proposes an energy-efficient clock synchronization scheme for Wireless Sensor Networks (WSNs) based on a novel time synchronization approach. Within the proposed synchronization approach, a subset of sensor nodes are synchronized by overhearing the timing message exchanges of a pair of sensor nodes. Therefore, a group of sensor nodes can be synchronized without sending any extra messages. This paper brings two main contributions: 1. Development of a novel synchronization approach which can be partially or fully applied for implementation of new synchronization protocols and for improving the performance of existing time synchronization protocols. 2. Design of a time synchronization scheme which significantly reduces the overall network-wide energy consumption without incurring any loss of synchronization accuracy compared to other well-known schemes.

Abstract We introduce in this paper a new adaptive power‐controlled diversity combining scheme that reduces the average transmitted power of the mobile units (MUs) while meeting a certain minimum required quality of service. The key idea is (i) to collect and combine all the available diversity paths at the base station (BS) and then (ii) to request the MU to increase or decrease its transmitted power just to track the required target signal‐to‐noise ratio (SNR). Four power control variants accounting for practical implementation constraints including discrete power levels and transmitter gain saturation are proposed and studied. Some selected numerical results show that the proposed scheme offers considerable savings in the transmitted power levels over a wide SNR range but amplifier saturation leads to a violation of the target BER requirement in the low average SNR range. Additional numerical examples show that the power control variants that take into account practical implementation constraints conserve the main features of the ideal continuous power algorithm. Copyright © 2007 John Wiley & Sons, Ltd.

We propose and analyze in this paper new linger management techniques which are applicable for RAKE receivers operating in the soft handover region. These schemes employ "distributed" types of generalized selection combining (GSC) and minimum selection GSC schemes in order to minimize the impact of sudden connection loss of one of the active base stations. By accurately quantifying the average error rate, we show through numerical examples that our newly proposed distributed schemes offer a clear advantage in comparison with their conventional counterparts.

We propose and analyze new finger replacement techniques for RAKE reception in the soft handover (SHO) region with multiple base stations. The proposed schemes are basically based on the block comparison among groups of resolvable paths and lead to the reduction of complexity while offering commensurate performance in comparison with previously proposed schemes. Relying on the newly derived analytical expressions, we investigate not only the complexity in terms of the average number of required path estimations/comparisons and the SHO overhead but also the error performance of the proposed scheme over independent and identically distributed fading channels.

In this paper, we propose two new threshold based parallel multiuser scheduling schemes, namely (i) an on-off based scheduling (OOBS) scheme and (ii) a switched based scheduling (SBS) scheme. The objective is to reduce the complexity of implementation without a considerable performance loss in comparison with selection based scheduling. While the OOBS scheme schedules all the users with an SNR above a fixed preselected signal to noise ratio (SNR) threshold, the SBS scheme schedules only the Ks users with an acceptable SNR if there are enough acceptable users. Otherwise, the scheduler selects the best Ks users. We analyze statistical characteristics and performances of these proposed schemes. Numerical results show that the proposed schemes can offer some decrease in the average number of feedback load without an important degradation in average bit error rate and average spectral efficiency.

The authors propose and analyze new finger assignment techniques that are applicable for rake receivers in the soft handover (SHO) region. More specifically, in the SHO region, the receiver uses by default only the strongest paths from the serving base station (BS) and only when the combined signal-to-noise ratio (SNR) falls below a certain pre-determined threshold, the receiver uses more resolvable paths from the target BSs to improve the performance. Relying on the previous results for the case of two-BS case, the authors consider the multi-BS situation by attacking the statistics of several correlated generalized selection combining (GSC) stages and provide closed-form expressions for the statistics of the output SNR. By investigating the tradeoff among the error performance, the path estimation load, and the SHO overhead, the authors show through numerical examples that the new schemes offer commensurate performance in comparison with more complicated GSC-based diversity systems while requiring a smaller estimation load and SHO overhead.

We introduce in this paper a new adaptive power-controlled diversity combining scheme that reduces the average transmitted power of the mobile units while meeting a certain minimum required quality of service. The key idea is (i) to collect and combine all the available diversity paths at the base station and then (ii) to request the mobile unit to increase or decrease its transmitted power just to track the required target signal-to-noise ratio (SNR). Four power control variants accounting for practical implementation constraints including discrete power levels and transmitter gain saturation are proposed and studied. Some selected numerical results, show that the proposed scheme offers considerable savings in the transmitted power levels over a wide SNR range but amplifier saturation leads to a violation of the target BER requirement in the low average SNR range. Additional numerical examples, show that the power control variants that take into account practical implementation constraints conserve the main features of the ideal continuous power algorithm

We introduce in this paper a new adaptive power-controlled minimum selection generalized selection combining (MS-GSC) diversity scheme. The key idea is to request the transmitter to increase its power level during very adverse channel conditions in order to reach the minimum required quality of service. Four power control variants accounting for practical implementation constraints including discrete power levels and transmitter gain saturation are proposed and studied. Selected numerical examples, show that ideal continuous power control lowers the average bit error rate of MS-GSC and makes it always meet the specified target quality of service at the expense of an increase in the transmitter gain. Additional numerical examples, show that the power control variants that take into account practical implementation constraints conserve the main features of the ideal continuous power algorithm