Low Earth Orbit (LEO) Satellites have been considered to expand the coverage of terrestrial networks, especially for collecting data from remote ground users unable to communicate directly with base stations (BSs). However, for reliable connectivity at specific data rates, a network over ground users with multiple LEO-Satellites is essential. To this end, in this paper, we study a LEO-Satellite network for integrated access and backhaul (IAB) in fifth generation (5G) and beyond systems, where a LEO-Satellite becomes an IAB node that is connected to other IAB nodes for backhaul transmissions and acts like a BS to ground users. Both the access network and backhaul are assume to be affected by large scale fading. Thus, terrestrial source transmits packets to the terrestrial destination via LEO-Satellite network. The proposed model is evaluated by analyzing the end-to-end packet transmission delay and propagation delay. Analytical formulas for transmission delay in both the access and backhaul networks are derived, and simulation results illustrate the system’s dependency to various parameters.

This paper proposes an IRS-aided design to mitigate the persistent outage floor issue frequently observed in multi-user full-duplex (FD) cooperative systems. It is assumed that the destination is affected by co-channel interference (CCI). Two antenna modes, namely dynamic antenna mode (DAM) and static antenna mode (SAM), are utilized for M FD relays and N IRS devices, each with K reflecting elements. A combined method for selecting the antenna mode, relay, and IRS devices is employed to enhance overall network performance. The effect of CCI is also investigated for the proposed schemes. For all SNR regions, the diversity gains achieved by DAM and SAM are NK + M and NK + 2M, respectively. The results demonstrate that using IRS devices with a parallel structure provides greater spatial diversity and outperforms traditional FD cooperative systems in the presence of CCI.

In this paper, a multi-connectivity based two-tiered self-backhauled millimeter wave (mmWave) network is considered. We assume both access and backhaul links are modelled by random binary blockage and Nakagami-m channels in order to model the impairments in mmWave bands. The system performance is evaluated for a downlink system with cooperation of multiple self-backhauled base stations in term of outage probability. Moreover, the derived end-to-end probability density function is utilized to calculate the ergodic capacity. Finally, simulation results are presented to show the impact of different parameters on the performance.

Concurrent with the rise of real-time wireless systems enabled by the Internet of Things, the age of information (AoI) has been widely perceived as a crucial destination-centric performance metric to quantify the timeliness of data delivery. This paper deals with the analysis of information freshness in a multi-source M/G/1 queueing system with utilization of idle server time, referred to as server vacation, in an effective manner. In particular, the status update packets in our model are generated independently by a finite set of source nodes and according to a Poisson process, while their service time follows a general random variable. Using stochastic decomposition and the Laplace-Stieltjes transform, we derive the average AoI (AAoI) expression for the multi-source M/G/1 queueing model with generally-distributed vacation time in closed form. Our numerical simulations validate the accuracy of the derived AAoI expression and assess the impact of different parameters on the system performance.

Recently, large intelligent surfaces/antennas (LISA) have been widely studied as an emerging technology for future wireless networks. In general, LISA contains a large number of passive sensors that are able to adjust a phase-shift on impinging signals. To this end, an intelligent module can control this phase-shift resulting in controlling the wireless multipath channel phase-distortion which is random in nature. In this work, we study on how a LISA can serve multiple device-to-device (D2D) communications. Here, LISA sensors are scarce resources which should be allocated among the D2D communications optimally. For this purpose, we propose a Genetic algorithm-based optimization to maximize the spectral efficiency and minimize the interference. Our approach has been evaluated with extensive simulations, thus providing new observations and findings.

In this paper, we consider a downlink self-backhauled mmWave cellular system with opportunistic selection of associated small cells, controlled by a centralized anchor base station (A-BS). We assume both backhaul and access links are modeled as Nakagami-m channels concatenate with random binary blockages. We analyze the system performance by deriving the equivalent end-to-end channel distributions. Then, the derived cumulative distribution function is used to calculate the outage probability. Finally, the simulation results show the impact of different parameters and correctness of our analytical results. It is also shown that our proposed scheme outperforms maximum ratio combining detection, in which all associated self-backhaled BSs are retransmitting the decoded user message toward the typical user equipment.

Due to the limited number of radio frequency (RF) chains in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) receivers using analog beamforming/hybrid beamforming, there is a restriction in scheduling the number of users in each transmission time interval. Therefore, fast and low-complexity user scheduling methods based on the instantaneous channel state information (CSI) are needed. In this paper, we propose novel user scheduling methods based on deep learning (DL) to reduce the size of the search space by using the learning capability of a deep neural network (DNN). We formulate the user scheduling combinatorial optimization problem as a regression problem followed by a user separation procedure through decision boundaries that are learned by a trained DNN. The decision boundaries are used to separate the users into two subsets. Then, one of the subsets is selected to be searched to find the users that maximize the sum-rate capacity. The proposed method can achieve a very low outage probability with a few number of searches. In order to achieve ergodic capacity with lower computation complexity, the proposed method is employed in combination with the genetic algorithm (GA) algorithm to take advantage of intelligent initial population selection. Our simulation results show that the proposed user scheduling methods can offer remarkably low complexity.

In this paper, we evaluate the performance of a multiple access edge computing system for task offloading over Rayleigh and Nakagami-m wireless fading channels. In our model, the user device simultaneously offloads a complex task to multiple edge nodes for processing by means of orthogonal frequency-division multiple access (OFDMA) scheme. The proposed scheme is suitable for millimeter Wave (mmWave) bands considered in 5G and beyond mobile networks. To assess the system efficiency, the delay-reliability metric is introduced in the context of the delay-outage probability. We investigate the delay-outage probability expression analytically for the proposed scheme and determine the optimized task size to minimize the offloading delay. Dependency of the system performance on various parameters is also analyzed in this work. Simulation results are provided to numerically evaluate the system reliability. It is found that the selection based scheme in which a single edge node is selected is recommended for OFDMA-based task offloading.

This paper investigates the optimum power allocation ratio of a jammer in order to ruin the sum spectral efficiency (SSE) of a user-centric cell-free network. In this regard, signal to interference plus noise ratio (SINR) is initially derived for each user in uplink, and then, a closed-form expression for SSE is provided. An optimization problem has been solved for two scenarios which finds the optimum power allocation that minimizes the SSE of the network, first for a single antenna jammer and next for a multi-antenna one. Additionally, the performance of the SSE has been studied in the presence of several single-antenna jammers in the proposed network and also one multi-antenna jammer. The result is compared with co-located multi-input multi-output (MIMO) network and it is found that unlike co-located MIMO, as the number of serving access points (APs) increases, the network becomes more robust against jamming. The effect of the jammer’s antenna on power allocation ratio and spectral efficiency is further presented. Moreover, the impact of the number of jammers and the number of serving APs on the SE has been surveyed.

The novel concept of Internet of Nano Things (IoNT) brings even larger groups of nanomachines collaborating to achieve more complex tasks in the military, medical, and security fields. Moreover, Internet of Bio-Nano Things (IoBNT) is an emerging technology defining the seamless connection of nanomachines and biological entities with each other where they can access the traditional wireless communication networks to provide novel Internet of Things (IoT) applications, such as health monitoring, healthcare, and targeted therapy. The exchange of information between biological cells is based on the synthesis, transformation, emission, propagation, and reception of molecules. This information exchange is recently classified in telecommunications as molecular communication which is a biologically inspired technique to communicate in very small dimension networks. In nanonetworks, a high number of nanothings will operate in the same medium and they interfere with each other. Multiuser interference will create significant limits. Hence, we introduce to use the direction of releasing molecules as a new property to convey information. Releasing the molecules to the specific directions enhances the performance of molecular communication systems due to multiusers interference mitigation. Hence, adjacent transmitters can convey information in different directions, simultaneously. Then, we propose the binary direction shift keying (BDSK) modulation scheme where the transmitter pumps molecules in two different directions. Next, we obtain the error probability and achievable bit rate of BDSK modulation. Finally, we evaluate the performance of BDSK modulation by numerical results. The result of this article can be useful for molecular communication relay systems where relay nodes convey information to the different destinations.

In this paper, we consider a downlink Cloud Radio Access Network (Cloud-RAN) transmission, served by multiple beamformed remote radio head (RRHs) coordinated by base band units (BBUs), toward a typical mobile user. Assuming ultra-dense 5G and beyond network operating in millimeter wave (mm-Waves) bands, we modeled channels as a concatenation of Nakagami-m and binary blockage. In addition, it is assumed there are multiple interfering nodes nearby. We evaluate the system performance in terms of outage probability, after calculating channel distributions. Moreover, the impact of random blockage and interference on the performance of Nakagami-blockage channels with multiple RRHs are investigated by simulations.

In this paper, we investigate performance of an ultra-dense downlink millimeter wave (mm-Wave) coordinated multi-point (CoMP) system with opportunistic cell selection. The access links are modeled by concatenation of random blockage and Nakagami-m channel. After deriving channel distributions, we find closed form formulas for outage probability of the mobile user suffered by the interference. We show that the effects of both blockage and interference should be taken into account. As a feasible solution to tackle these impairments in mm-Wave based 5G and Beyond network, we increase the number of associated base stations to serve the CoMP user.

In this paper, a coordinated multi-point (CoMP) based mmWave communications operating over access links impaired by blockage is considered. By assuming realistic assumptions such as line-of-sight and non-line-of-sight channel components, fading, and random blockage, we propose a tractable analytical framework for mmWave communications. Moreover, the performance of the CoMP-based mmWave communication is evaluated by deriving the distribution of the received signal and presenting closed form expression for outage probability. Simulation results show the correctness of the analytical results and impact of blockage on the reliability of the mmWave communications.

With the increasing adoption of millimeter-waves (mmWave) over cellular networks, outdoor-to-indoor (O2I) communication has been one of the challenging research problems due to high penetration loss of buildings. To address this, we investigate the practicability of utilizing reconfigurable intelligent surfaces (RISs) for assisting such O2I communication. We propose a new notion of prefabricated RIS-empowered wall consisting of a large number of chipless radio frequency identification (RFID) sensors. Each sensor maintains its own bank of delay lines. These sensors which are built within the building walls can potentially be controlled by a main integrated circuit (IC) to regulate the phase of impinging signals. To evaluate our idea, we develop a thorough performance analysis of the RIS-based O2I communication in the mmWave network using stochastic-geometry tools for blockage models. Our analysis facilitates two closed-form approximations of the downlink signal-to-noise ratio (SNR) coverage probability for RIS-based O2I communication. We perform extensive simulations to evaluate the accuracy of the derived expressions, thus providing new observations and findings.

In this article, the performance of UAV-based mmW links is investigated when UAVs are equipped with square array antennas. The 3GPP antenna propagation patterns are used to model the square array antenna. It is shown that the square array antenna is sensitive to both horizontal and vertical angular vibrations of UAVs. In order to explore the relationship between the vibrations of UAVs and their antenna pattern, the UAV-based mmW channels are characterized by considering the large scale path loss, small scale fading along with antenna patterns as well as the random effect of UAVs' angular vibrations. To enable effective performance analysis, tractable and closed-form statistical channel models are derived for aerial-to-aerial (A2A), ground-to-aerial (G2A), and aerial-to-ground (A2G) channels. The accuracy of analytical models is verified by employing Monte Carlo simulations. Analytical results are then used to study the effect of antenna pattern gain under different conditions for the UAVs' angular vibrations for establishing reliable UAV-assisted mmW links in terms of achieving minimum outage probability. Simulation results show that the performance of UAV-based mmW links with directional antennas is largely dependent on the random fluctuations of hovering UAVs. Moreover, UAVs with higher antenna directivity gains achieve better performance at larger link length. However, for UAVs with lower stability, lower antenna directivity gains result in a more reliable communication link. Finally, based on the geometrical properties of a given region, we investigate the optimal antenna pattern along with the optimal aerial position for UAV relay to attain minimum outage probability.

Molecular communication is a biologically-inspired technique to communicate in very small dimension networks. Many different modulation schemes were proposed in the literature based on different properties of molecules. In this paper, we propose to use the direction of releasing molecules as a new property to convey information and we propose Direction Shift Keying (DSK) modulation scheme. Then, we obtain a solid analytical formulation for the concentration of molecules in the 3-D diffusion environment when the transmitter employs DSK modulation. We analyze the concentration of molecules by numerical results. It is observed that the concentration of molecules becomes maximum on the receiver surface in the releasing direction and at a specific time. The derived results may be useful for designing molecular communication systems and evaluating the performance of DSK scheme in the future works.

With the excessive growth in mobile users' traffic, radio resource management (RRM) techniques should undergo revolutionary changes to be competent enough to meet the ever-increasing users' demands. Virtualized wireless network (VWN) has emerged as a satisfactory solution in the fifth-generation (5G) cellular networks ensuring the required quality-of-service (QoS) of distinct slices. Yet, it seems that tackling RRM problems in VWNs using conventional optimization is not practical for real-time applications. In this paper, driven by the advancements of machine learning, we consider the throughput maximization problem in a cloud radio access network (C-RAN) assisted softly virtualized wireless network supporting different types of services and solve it with a deep Q-learning (DQL) algorithm. The performance of the proposed policy is thoroughly evaluated via simulation results with respect to the isolation rate, penalty value as well as the discount factor. It is shown that our proposed policy achieves a higher sum rate compared to the existing baseline namely a greedy search-based power allocation strategy.

In this paper, we consider an uplink Cloud Radio Access Network (RAN) transmission from a user served by multiple remote radio heads (RRHs) which are connected to each other via base band unit (BBU) pool which form a centralized processing. We assume opportunistic detection in which the best RRH is selected at a time to transfer the received message to BBU pool. In this case, we can achieve the diversity gain by choosing the proper RRH and reduce fronthaul traffic by occupying a single link. As another enabling technology for 5G and Beyond, we consider mmWave communications. Since LOS/NLOS components are essential in modeling mmWave bands, we use Nakagami-m channels. In addition, for blockage effect of mmWave bands, we assume random blockage model. For performance analysis, closed form expressions for outage probability and ergodic capacity are derived. Furthermore the analytical results are confirmed by comparing them with simulation results. It is shown that opportunistic scheme outperforms maximum ratio beamforming in which all RRHs are contributing in detection of the mobile user signal.

This paper investigates RF power leakage in millimeter wave (mmWave) networks operating on hybrid beamforming (HB) system where a base station with massive MIMO antennas communicates with user equipment (UE) nodes equipped with a single antenna. RF power leaks between spatially divided transmissions to different users, due to back/side lobes of antennas. A maximum sub-array transmission diversity technique implemented on HB is proposed to improve the system performance under RF power leakage and residual transceiver distortion noise. In this work, we emphasize how RF power leakage and residual transceiver distortion noise constraints degrade the quality of communication performance in terms of outage probability (OP) and ergodic capacity. An analytic model of mmWave connectivity is used, resulting in closed-form expressions for the OP and ergodic capacity. These are corroborated through Monte-Carlo simulations. Simulation results demonstrate that the effect of transceiver distortion noise is more severe at high signal power due to the proportionality of transceiver distortion noise to signal power.

In this paper, we consider a neuro-spike communication system between two neurons where nano-machines are used to enhance ability of neurons. Nano-machines can be employed for stimulation tasks when neurons have lost their ability to communicate. In the assumed system, information is conveyed via the time intervals between the input spikes train. For efficiency evaluation of temporal coding, we model the neuro-spike communication system by an additive Gamma noise channel. We present this model by considering different time distortion factors in the neuro-spike system. Then, we derive upper and lower bounds on the channel capacity. We analyze the channel capacity bounds as functions of the time intervals between the input spikes and the firing threshold of the target neuron. Moreover, we propose maximum likelihood and maximum a posteriori receivers and derive the resulting bit error probability when the system uses binary modulation. In addition, we obtain an upper bound for this error probability. Then, we extend this upper bound to the symbol error probability of the $T$ -ary modulations. Simulation results show that this upper bound is tight. The derived results show that temporal coding has a higher efficiency than spike rate coding in terms of achievable data rate.

The human nervous systems is a complex network, which consists of neurons interacting with each other through a hybrid electro-chemical communication called neuro-spike communications. A first building-block in network analysis of the neuro-spike nano-network is multiple-input-single- output (MISO) diversity scheme. Thus, in this paper, we consider a MISO transmission in a axonal-synaptic channels. In addition, for the first time, we model axonal noise as a binary X-channel. We derive error probability in a system consisting of axonal and synaptic noises, random channel and random vesicle release in a network with multiple transmitting synapses.

In this paper, we derive the achievable rate of single-carrier frequency domain equalizer (SC-FDE) and orthogonal frequency division multiplexing (OFDM) systems, constrained on low resolution analog to digital converters (ADCs). We assume that there is a full knowledge of channels at both transmitter and receiver sides. We model low resolution ADCs with an additive uniform quantization noise. We consider an ultra-wide band millimeter wave (mm-Wave) system with a frequency selective channel. The channel is based on practical results at mm-Wave frequencies. Our numerical results show that SC-FDE systems with minimum mean square error (MMSE) equalizers outperform OFDM and SC-FDE systems with zero forcing (ZF) equalizers at high signal to noise ratio (SNR) regimes. Moreover, benefits of increasing the ADCs resolution are not significant due to exponentially increment in the power consumption of ADCs.

In large-scale multiple-input multiple-output (LS-MIMO) systems, by exploiting hundreds of antennas at the base station, spectral efficiency, power efficiency, and link reliability can be enhanced significantly. However, by increasing the number of antennas, the computational complexity of the detectors makes the hardware implementation intractable, and therefore, LS-MIMO systems require sub-optimal low complexity detection algorithms. In this paper, two novel approaches for improving factor graphbased belief propagation with Gaussian approximation of interference (FG-BP-GAI) algorithm is proposed to reduce the computational complexity of the belief propagation (BP) based receiver without bit error rate (BER) degradation. More specifically, two novel techniques, namely odd Taylor series and odd least square, are proposed to approximate the a posteriori probability in the FG-BP-GAI policy with few polynomial terms of low degree. In the simulation results, the performance of our proposed algorithms are assessed and it is shown that our proposed improved FGBP-GAI policies can achieve lower computational complexity compared with the other approaches in the literature like MRF-BP algorithm without BER degradation.

In this paper, a distributed, minimum overhead power control algorithm for underlay cognitive radio networks (CRNs) having multiple primary and secondary users is proposed. The problem is formulated as a noncooperative game and a learning algorithm is proposed for optimizing the power allocation of secondary users. In the considered network, secondary users (SUs) do not have full information on the interference and power control strategies of other SUs. As a result, they update their strategy using a simple feedback from the primary user base station that provides the total interference. Although there is no cooperation among secondary users, it is shown that, under incomplete information, the proposed learning algorithm converges to the strategy of the players in the Nash equilibrium of the complete information case. The Nash equilibrium point is derived analytically, and then it is demonstrated that, although each user individually tries to maximize its own payoff, at the end, the proposed algorithm will converge to the complete information game Nash equilibrium point. It is also shown that the algorithm will be capable of adapting to a time-varying environment if some conditions on the SUs' processing power are satisfied. This is due to the slotted time assumption of the algorithm. Simulation results are then used to corroborate the analytical derivations.

We consider a neuro-spike communication system between two nano-machines, with information conveyed in the time intervals of the input spike train. The main contribution of our paper is modeling of the neuro-spike communication channel by an additive Gamma noise channel model. In this channel, the information is corrupted by Gamma distributed noise. We show that the proposed channel model is efficient for the neuro-spike communication when it exploits temporal modulations to transfer information. Then, we consider the Gamma distributed noise and we derive the upper and lower bounds on the channel capacity. Unlike Additive White Gaussian Noise (AWGN) channels, there is no single quality measure like signal-to-noise ratio for this channel model. Thus, we analyze the channel capacity bounds versus different values of time intervals and the decision threshold of the receiver.

In a communication system, security and reliability have an important impact on the quality of services. In this paper, we investigate power and subcarrier allocation of a transmitter over the downlink of an OFDMA system with security considerations among users in the presence of a jammer. This paper considers the interaction between the jammer and the transmitter as a zero-sum game where the objective function is the transmitter's secrecy sum-rate. In order to allocate available resources, we solve the optimization problem of each player to characterize their optimal strategies. Considering the intractability of the closed form Nash equilibrium for general power regime, we show the existence of pure Nash equilibrium point for low total power regimes of the transmitter and the jammer and attain an expression for each regime. Finally, we examine the jamming power effect on the secrecy sum-rate and acquire lower and upper bounds of this rate using simulations.

Interference management and supporting quality‐of‐service (QoS) requirements are the main challenges for the spectral resource allocation in orthogonal frequency division multiple access (OFDMA) small cells networks. In this study, the authors propose an algorithm for assigning physical resource block (PRB) with QoS constraints to eliminate interference among femtocells. They formulate the proposed resource allocation scheme as an optimisation problem where interference among femtocells is entirely avoided and multiple QoS for different services are supported. The proposed optimisation problem imposes the fairness among different femtocells and maximises the PRB efficiency. However, this problem is NP‐complete, and thus, they offer a greedy algorithm for solving the problem. Simulation results show the throughput of their greedy algorithm is close to the optimal solution of the optimisation problem. Moreover, the proposed algorithm improves the network throughput by over 30–50% in different simulation scenarios with various femtocells densities in comparison to the previous methods. Furthermore, simulations illustrate the rejection ratio for all classes of services is lower than . Besides, the delays of different services are lower than the delay constraints.

In a communication system, security and reliability have an important impact on the quality of services. In this study, the authors investigate power and subcarrier allocation of a transmitter over the downlink of an orthogonal frequency division multiplexing access system with security considerations among users in the presence of a jammer. This study considers the interaction between the jammer and the transmitter as a zero‐sum game where the objective function is the transmitter's secrecy sum‐rate. To allocate the available resources, they solve the optimisation problem of each player to characterise its optimal strategies. Considering the intractability of the closed form Nash equilibrium for general power regime, they study a matrix game for obtaining maxmin and minmax solutions and demonstrate the validity of inequality . Moreover, they show the existence of pure Nash equilibrium point for low total power regimes of the transmitter and the jammer and attain an expression for each regime. Finally, they examine the jamming power effect on the secrecy sum‐rate and acquire lower and upper bounds of this rate using simulations.

In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.

One of the most promising approaches to overcoming the uncertainty of millimeter wave (mm-wave) communications is to deploy dual-mode small base stations (SBSs) that integrate both mm-wave and microwave (μW) frequencies. In this paper, a novel approach to analyzing and managing mobility in joint mmwave-μW networks is proposed. The proposed approach leverages device-level caching along with the capabilities of dual-mode SBSs to minimize handover failures and reduce inter-frequency measurement energy consumption. First, fundamental results on the caching capabilities are derived for the proposed dual-mode network scenario. Second, the impact of caching on the number of handovers (HOs), energy consumption, and the average handover failure (HOF) is analyzed. Then, the proposed cache-enabled mobility management problem is formulated as a dynamic matching game between mobile user equipments (MUEs) and SBSs. The goal of this game is to find a distributed HO mechanism that, under network constraints on HOFs and limited cache sizes, allows each MUE to choose between: 1) executing an HO to a target SBS; 2) being connected to the macrocell base station; or 3) perform a transparent HO by using the cached content. To solve this dynamic matching problem, a novel algorithm is proposed and its convergence to a two-sided dynamically stable HO policy for MUEs and target SBSs is proved. Numerical results corroborate the analytical derivations and show that the proposed solution will significantly reduce both the HOF and energy consumption of MUEs, resulting in an enhanced mobility management for heterogeneous wireless networks with mm-wave capabilities.

One of the most promising approaches to overcome the uncertainty and dynamic channel variations of millimeter wave (mmW) communications is to deploy dual-mode base stations that integrate both mmW and microwave (μW) frequencies. In particular, if properly designed, such dual-mode base stations can enhance mobility and handover in highly mobile wireless environments. In this paper, a novel approach for analyzing and managing mobility in joint μW-mmW networks is proposed. The proposed approach leverages device-level caching along with the capabilities of dual-mode base stations to minimize handover failures and provide seamless mobility. First, fundamental results on the caching capabilities, including caching probability and cache duration, are derived for the proposed dual-mode network scenario. Second, the average achievable rate of caching is derived for mobile users. Then, the impact of caching on the number of handovers (HOs) and the average handover failure (HOF) is analyzed. The derived analytical results suggest that content caching will reduce the HOF and enhance the mobility management in heterogeneous wireless networks with mmW capabilities. Numerical results corroborate the analytical derivations and show that the proposed solution provides significant reductions in the average HOF, reaching up to 45%, for mobile users moving with relatively high speeds.

Novel nano-scale communications techniques are inspired by some naturally existing phenomena such as the molecular communication, neuro spike communication and controlling cellular signaling mechanisms. Among these, neuro-spike communication, which governs the communications between neurons, is a vastly unexplored area. It can be divided into three main blocks, i.e., the axonal transmission, the synaptic transmission and the spike generation. In this paper, we focus on the axonal transmission part as a separate channel. We model the input of this channel by a doubly Poisson process which is a Poisson process with a random intensity. Moreover, we consider an axonal noise modeled by a Poisson process. Then, we derive the capacity of Single-Input Single-Output (SISO) and Multiple-Input Single-Output (MISO) axonal channels, analytically. In the MISO channel case, we investigate the effect of the correlation among inputs on the channel capacity. Moreover, we derive a closed form description for the optimum value of input power to maximize the capacity of axonal channels in different cases. Furthermore, we verify the accuracy of the derived capacity of axonal transmission channels in different scenarios by simulation, i.e., it is shown that less than 10% mismatch exists in average between the analytical and simulation results.

Millimeter-wave (mm-wave) communication is a promising technology for supporting extremely high data rates in the next generation wireless networks. Mm-wave signals experience high path loss and directional transmission is required to compensate the severe channel attenuation. The special characteristics of the mm-wave propagation arise opportunities as well as challenges for the network resource allocation problems. In this paper, a fair user association, beamwidth selection and power allocation problem for indoor mm-wave networks is studied. The objective of the optimization problem is to maximize the minimum user throughput to provide a fair resource distribution among the users. In our model, we take into account the unique mm-wave communications features, namely beam alignment procedure and directional transmission. Simulation results confirm the superior performance of the proposed solution compared to the existing approaches.

Novel nano-scale communications techniques are inspired by some naturally existing phenomena such as the molecular communication, neuro spike communication and controlling cellular signaling mechanisms. Among these, neuro-spike communication, which governs the communications between neurons, is a vastly unexplored area. In this paper, we assume a point-to-point communication model for neuro-spike communication and consider several sources of randomness to achieve a realistic model. These random factors consist of axonal noise, random vesicle release, random amplitude and synaptic noise. We model the axonal transmission part as a binary channel through defining the axonal shot noise probability. Next, we investigate the second part of neuro-spike communication channel, i.e., synaptic transmission, to derive error probability of this part. Moreover, we derive a closed form description for the decision threshold to design an optimum spike detection receiver. Then, we assume the neuro-spike communication channel as two cascaded binary channels and derive its error probability. We investigate the impact of axonal noise, synaptic noise and the probability of vesicle release on the error probability of the neuro-spike communication channel.

One significant challenge in cognitive radio networks is to design a framework in which the selfish secondary users are obliged to interact with each other truthfully. Moreover, due to the vulnerability of these networks against jamming attacks, designing anti-jamming defense mechanisms is equally important. In this paper, we propose a truthful mechanism, robust against the jamming, for a dynamic stochastic cognitive radio network consisting of several selfish secondary users and a malicious user. In this model, each secondary user participates in an auction and wish to use the unjammed spectrum, and the malicious user aims at jamming a channel by corrupting the communication link. A truthful auction mechanism is designed among the secondary users. Furthermore, a zero-sum game is formulated between the set of secondary users and the malicious user. This joint problem is then cast as a randomized two-level auctions in which the first auction allocates the vacant channels, and then the second one assigns the remaining unallocated channels. Simulation results show that the distributed algorithm can achieve a performance that is close to the centralized algorithm.

Machine-to-machine (M2M) communications consist of a large number of smart devices that communicate automatically without human intervention. The Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) and LTE-Advanced (LTE-A), due to some features such as IP connectivity and scalability, are ready-to-use infrastructures for the M2M communications implementation. In the next generation of cellular networks with M2M devices, radio resource allocation is a major issue. In order to solve the issue, this paper addresses the efficient resource block (RB) allocation problem for different relay-aided cellular and M2M user equipments (UEs) to maximize the end-to-end data rate under different constraints of Single Carrier Frequency Division Multiple Access (SC-FDMA). The proposed solution also satisfies the maximum power budget, the minimum data rate and statistical QoS delay requirements for prioritizing different traffics under total power constraint. Numerical results demonstrate the effectiveness of the proposed scheme.

Heterogeneous face recognition (HFR) has a prominent importance in sophisticated face recognition systems. Thermal to visible scenario, where the gallery and the probe images are respectively captured in visible and long wavelength infrared (LWIR) band, is one of the most challenging and interesting HFR scenarios. Since the formation of thermal images does not require an external illumination source, the deployment of thermal probe images is practical even in totally darkness conditions such as night security surveillance systems. In this paper, we propose an ensemble classifier which uses the random subspace idea for defining different representations of each image in distinct base learners, and exploits the sparse representation algorithm for the classification of thermal probe images. According to the experimental results, our proposed algorithm leads significant performance improvements in the area of thermal to visible face recognition and achieves the average Rank-1 accuracy of 89.33 percent.

One key challenge in heterogeneous cellular networks is the presence of wireless backhaul links whose resources must be jointly allocated with those of the radio access network. In this paper, a novel approach for joint backhaul and radio resource allocation in a two-tier small cell network is proposed. The problem is formulated as a Stackelberg game, in which the macrocell base station (MBS) acts as a leader and overlaid picocell base stations (PBSs) as followers. In this game, the MBS maximizes its sum rate transmission by properly allocating the subcarriers over the backhaul links and the PBSs seek to maximize their transmission rate by allocating power and the subcarriers. A self- backhauling model and an orthogonal frequency allocation between the backhaul and the access links are adopted, in which the subcarrier allocation over the backhaul and the access links will be captured in the leader's and followers' optimization problems, respectively. The optimal power allocation problem is studied for the followers problem. Furthermore, the uniqueness of the Stackelberg equilibrium point is investigated. Simulation results show the effectiveness of the proposed algorithm which yields up to 14.2% and 24.9% transmission rate improvement compared to the baseline method.

In this paper, the problem of adversarial learning is studied for a wireless powered communication network (WPCN) in which a hybrid access point (HAP) seeks to learn the transmission power consumption profile of an associated wireless transmitter. The objective of the HAP is to use the learned estimate in order to determine the transmission power of the energy signal to be supplied to its associated device. However, such a learning scheme is subject to attacks by an adversary who tries to alter the HAP's learned estimate of the transmission power distribution in order to minimize the HAP's supplied energy. To build a robust estimate against such attacks, an unsupervised Bayesian learning method is proposed allowing the HAP to perform its estimation based only on the advertised transmisson power computed in each time slot. The proposed robust learning method relies on the assumption that the device's true transmission power is greater than or equal to advertised value. Then, based on the robust estimate, the problem of power selection of the energy signal by the HAP is formulated. The HAP optimal power selection problem is shown to be a discrete convex optimization problem, and a closed-form solution of the HAP's optimal transmission power is obtained. The results show that the proposed robust Bayesian learning scheme yields significant performance gains, by reducing the percentage of dropped transmitter's packets of about 85% compared to a conventional Bayesian learning approach. The results also show that these performance gains are achieved without jeopardizing the energy consumption of the HAP.

In this paper, we investigate the spectral efficiency of a communication link in a wireless body area network (WBAN) capable of harvesting energy from the environment. We consider two scenarios for the transmission which are single- and dual-hop and achieve the power management policy for each scenario. In the first scenario, the aim is to maximize the link's spectral efficiency over N time slots subject to the battery capacity, energy harvesting constraint, and WBAN limitations including power and outage probability. In the second scenario, a decode-and-forward relay node is considered, and a spectral efficiency optimization problem with constraints similar to the first scenario is evaluated. In addition, since the channel distribution information is available at the transmitters, the lower and upper bounds of the average spectral efficiency are also derived in both scenarios. Finally, numerical results corroborate the analytical results.

Millimeter-wave (mm-wave) communication is a promising technology for the next generation cellular networks. Motivated by the huge available bandwidth at these bands, it can be used to support the fastest-growing demands for the mobile data traffic such as multimedia applications. However, there are some challenges on the network connectivity at the mm-wave frequency bands. The high path loss, the limited diffraction capability due to the short wavelength, and having difficulties in penetrating through solid materials necessitate the line-of-sight and multi-hop communication in mm-wave networks. In this paper, we develop a multi-hop routing protocol which maximizes the sum quality of the uncompressed high-definition video applications for the device-to-device connections. The quality is measured as a function of the rate in this paper. We take into account the unique characteristics of the mm-wave propagation in our model. Simulation results show that the proposed algorithm achieves the optimal solution for high cooperation probability. It is also verified by the simulation that our algorithm outperforms the max-min flow routing protocol solution.

In this paper, we propose a novel online centralized algorithm for enabling non-cooperative and energy harvesting capable base stations (BSs) to trade energy in multi-tier cellular networks. BSs are connected to the non-renewable energy source used by a BS when it cannot harvest enough energy to serve its connected users. A double auction trading framework is proposed to motivate BSs with the extra harvested energy to share their surplus energy with BSs that have not harvested sufficient energy. In addition, BSs with energy deficit are stimulated to buy surplus energy of other BSs which results in reducing of the non-renewable energy consumption. The algorithm satisfies truthfulness, individual rationalities and budget balance. Moreover, it reaches the Nash equilibrium. The extra harvested energy is distributed by the smart grid that prevents energy accumulation which results in the waste of the harvested energy due to limited battery capacities. To reduce smart grid usage in distributing energy, an optimization is embodied in the proposed algorithm to assign BSs with energy deficit to near BSs with extra harvested energy. Simulations results show that the non-renewable energy consumption reduces dramatically when the algorithm is applied. In addition, BSs gain more profit, consequently, their utility functions enhance.

Frame aggregation (FA) mechanisms improve the throughput of WLANs. In this paper, the effect of the FA mechanism on the throughput of wireless local area networks (WLANs) has been investigated. To this end, we propose an analytical model in order to analyze an IEEE 802.11n network comprised of an access point (AP) and several conventional nodes (CNs), all in the coverage area of each other. With respect to the heavier download traffic compared to the upload one, in our scenario, only the AP uses an FA mechanism and the other nodes use the basic IEEE 802.11 standard. In our proposed analytical model, the maximum downlink (DL) throughput is derived. Regarding the asymmetry among nodes, our analytical model consists of two different queueing networks: one for the AP and the other one for CNs. We verify the accuracy of our analytical results by simulations, i.e., less than 5% mismatch between the analytical and simulation results. We show that there is a tradeoff between the DL saturation throughput and performance of CNs. In other words, the FA improves the AP saturation throughput at the cost of a little degradation of the performance for CNs.

Millimeter-wave (mm-wave) communication is a promising technology for the next generation wireless networks. Motivated by the immense amount of bandwidth at these bands, it can be used to support the quality of service requirements for the bandwidth-intensive purposes, like the backhaul demands of the small cell base stations. However, the high path loss, the limited penetration ability and the intermittent connectivity necessitate utilizing the multi-hop transmission techniques to maintain network connectivity. In this paper, the outage performance of the mm-wave relaying systems is studied. We take into account the unique propagation characteristics of the mm-wave bands, namely the intermittent connectivity, and obtain the closed-form expression for the outage probability of the mm-wave multi-hop regenerative relaying system. Moreover, the closed-form approximation for the outage probability in a dual-hop nonregenerative case is also derived. The analytical expressions are verified by the simulation results.

With multimedia dominating the main traffic load of the wireless networks, device-to-device (D2D) communication is an efficient way of data offloading. By the growth of video data traffic, quality of experience (QoE), which is a user-centric measure, has become the focus of the research academia. In this paper, the video quality and fluency are considered as the factors that influence the user experience in D2D video streaming services. Aiming to enhance the user experience, we propose a QoE-aware power allocation for D2D video transmissions. The resource allocation target is to maximize the video quality while minimizing the data rates variations over the time-varying wireless channels. We then show that using dual decomposition technique, the problem can be implemented in a distributed way by the exchange of demand and price among the network and D2D users. Simulation results demonstrate that the proposed scheme can significantly improve the QoE in D2D video services.

In this paper, we consider a cooperative underlay cognitive radio network in which the primary network (PN) consists of a transmitter and receiver and the secondary network (SN) has K bidirectional half-duplex relays. In the SN, two secondary transceivers adopt multiple access broadcast protocol for the secondary data transmission and at each bidirectional relay, there exist two buffers of size L data elements. Hence, each relay can store the incoming secondary data and retransmit it in an appropriate time slot later. We propose a novel buffer-aided bidirectional relay selection policy with secondary power minimization and successive interference cancellation in which the interference between the PN and SN is eliminated. Since buffers are used at the relays, data transmission in the SN is not limited to a predefined schedule. Hence, at each time slot, based on the instantaneous buffer state information of the relays and the instantaneous or statistical channel state information of the involved links, the SN makes a decision. The SN decides optimally when to use one of the relays for the multiple access, use one of the relays for the broadcast mode or be silent provided that the data transmission in both the PN and SN are error free and the secondary power expenditure is minimized. Simulation results show that the proposed scheme minimizes the secondary power expenditure, and achieves up to 40% improvement in the secondary throughput for 6 middle relays compared to the other recently proposed policies without buffer.

In this paper, a novel approach for interference pricing and power control in the uplink of a two-tier small cell network is proposed. To model this problem, a Stackelberg game is formulated in which the macrocell base station (MBS) and the femtocell user equipments (FUEs) are the players that seek to maximize their utility. In this game, the MBS optimizes its revenue which depends on the interference quota sold to the FUEs while the FUEs optimize the utility that captures the tradeoff between rate and payment to the MBS. Here, the MBS (leader) must choose an optimal price in order to manage the interference level from the FUEs (followers). To solve this game, a two-step distributed interference price bargaining algorithm is proposed. Using a number of techniques, the convergence of the proposed algorithm to a Stackelberg equilibrium is shown analytically. Simulation results show that this approach converges for a wide range of channel power gains while maintaining a certain energy efficiency level for the transmitting users.

In this paper, a cognitive machine-to-machine (M2M) communication network is considered, in which a cellular network shares the spectrum with the M2M communication network with M machine-type devices (MTDs), one half-duplex relay, and one MTD gateway for data gathering. One key challenge is that in the future 5G wireless networks, there will be billions of those small MTDs, and therefore, a MTD selection protocol is required for managing data transmission between MTDs. A joint buffer-aided MTD selection and power allocation protocol is proposed to maximize the MTDs' sum-rate provided that the induced interference to the cellular network is limited. In particular, in the proposed scheme, at each time slot and each subcarrier, the cognitive M2M network optimally decides on whether to be silent or to select either the relay or one of the MTDs for data transmission. To this end, for each MTD, there exists a buffer at the relay to avoid data loss. The closed-form expressions for the power coefficients of MTDs are calculated. Simulation results show that the proposed policy improves the sum-rate of the MTDs in comparison with the other proposed schemes for M2M communication without buffer.

Deploying small cells in cellular networks, as a technique for capacity and coverage enhancement, is an indispensable characteristic of future cellular networks. In this paper, a novel online decentralized algorithm for enabling energy trading in multi-tier cellular networks with selfish energy harvesting capable base stations (BSs) is proposed. A BS uses the non-renewable energy when it cannot harvest sufficient energy to serve its connected users. To minimize the non-renewable energy consumption, we establish a framework for trading energy such that BSs with energy deficit are stimulated to compensate their energy shortage with the extra harvested energy of other BSs. BSs with energy deficit are assigned to BSs with extra harvested energy by using matching theory. The extra harvested energy is distributed by the smart grid. Along with energy trades, BSs gain more profit and their utility functions enhance. Simulation results show that the waste of energy due to limited batteries and the non-renewable energy consumption decreases considerably when the proposed algorithm is applied.

In this paper, we propose a novel online centralized algorithm for energy cooperation among energy harvesting capable base stations (BSs) in multi-tier cellular networks. BSs are connected to the non-renewable source used by a BS when it cannot harvest sufficient energy to serve its connected users. BSs with the extra harvested energy operate cooperatively and share their surplus energy with BSs that have not harvested sufficient energy. To stimulate BSs with energy deficit to use the shared energy of other BSs, an energy pricing framework is established which results in reducing of the non-renewable energy consumption. We formulate the problem of maximizing the fairness of the renewable energy distribution. The closed-form of energy share given to each BS with energy deficit is found, by which the renewable energy distribution fairness is maximized. Energy is shared by the smart grid. The problem of minimizing the smart grid usage cost for distributing energy is formulated and an online algorithm is proposed to approximate its solution. Simulation results show that the approximate algorithm reduces the non-renewable energy consumption significantly and reduces the cost of smart grid usage near to the optimal solution.

This paper focuses on the two-user relay-assisted X channel with no channel state information (CSI) available at the transmitter side. Two relaying modes, namely half-duplex decode-and-forward (DF) and cognitive relays, are considered and the degrees of freedom (DoF) are characterized. It is shown that assisted by a half-duplex DF relay that is equipped with 2M antennas, the X channel with two M-antenna users has 4M/3 DoF, which is achievable through interference alignment (IA). Furthermore, it is shown that in this channel, an M-antenna cognitive relay (with non-causal access to information streams) provides 2M DoF using interference cancellation (IC) technique. In this setting, IC outperforms interference alignment in the cognitive relay mode, since the latter achieves 4M/3 DoF.

Random wireless networks with finite number of nodes distributed uniformly in a square-shaped finite region are considered. The transmission channels are assumed to experience Nakagami-m fading. A closed-form expression for the cumulative distribution function (CDF) of the interference power imposed on two randomly-located communicating nodes is derived. In contrast to most of the existing literature, the receiving node is not necessarily required to be located at the center of the network region. Two packet traffic patterns, viz., slotted-synchronous and slotted-asynchronous are considered and closed-form expressions for the CDF of the interference is obtained for each traffic pattern. Computer simulation illustrates the validity of the theoretical analyses.

Small cell networks are seen as a promising technology for boosting the performance of future wireless networks. In this paper, we propose a novel context-aware user-cell association approach for small cell networks that exploits the information about the velocity and trajectory of the users while also taking into account their quality of service (QoS) requirements. We formulate the problem in the framework of matching theory with externalities in which the agents, namely users and small cell base stations (SCBSs), have strict interdependent preferences over the members of the opposite set. To solve the problem, we propose a novel algorithm that leads to a stable matching among the users and SCBSs. We show that the proposed approach can better balance the traffic among the cells while also satisfying the QoS of the users. Simulation results show that the proposed matching algorithm yields significant performance advantages relative to traditional context-unaware approaches.

The deployment of small cells, overlaid on existing cellular infrastructure, is seen as a key feature in next-generation cellular systems. In this paper, the problem of user association in the downlink of small cell networks (SCNs) is considered. The problem is formulated as a many-to-one matching game in which the users and SCBSs rank one another based on utility functions that account for both the achievable performance, in terms of rate and fairness to cell edge users, as captured by newly proposed priorities. To solve this game, a novel distributed algorithm that can reach a stable matching is proposed. Simulation results show that the proposed approach yields an average utility gain of up to 65% compared to a common association algorithm that is based on received signal strength. Compared to the classical deferred acceptance algorithm, the results also show a 40% utility gain and a more fair utility distribution among the users.

In this paper, we consider a three-node wireless network comprising of a source and two users. Both users need to decode the transmitted data correctly. User 1 has better position to the source than user 2 most of time slots. User 1 has buffer to store the transmitted information by the source. Thus, in the case of wrong decoding at user 2, user 1 can resend data to user 2 some time slots later. In this paper, we propose a novel incremental relaying based adaptive link selection policy that exploits incremental relaying and buffer to maximize the throughput of the network. That is, based on the channel quality of the available links, each time slot is allocated either to the source or user 1 to transmit data. Both delay constrained and delay tolerant transmission schemes are studied. We model the variation of the buffer at user 1 as a Markov Chain and calculate the outage probability of the proposed policy. Our simulation results show that the proposed scheme achieves higher throughput and lower outage probability compared to the recently proposed link selection policies with or without buffer.

Wireless small cell networks and device-to-device (D2D) communications are seen as two major features of next-generation wireless networks. In this paper, a novel approach for enabling D2D communication underlaid on a wireless small cell network is proposed. Unlike existing works which focus on network performance analysis given a chosen communication mode, in this paper, the strategic selection of a desired wireless communication mode between pairs of users is studied. On the one hand, communication using the small cells can provide reliable transmission but is limited by interference and backhaul constraints. On the other hand, D2D communication can provide high capacity due to devices' proximity but is limited by increased interference. To capture these properties, the problem is modeled as a noncooperative game in which pairs of communicating users can strategically decide on whether to communicate with one another via the small cell infrastructure or via direct D2D communication. In this proposed game, each device selects its preferred communication mode while optimizing a utility function that captures the various involved tradeoffs between communication performance and associated costs. For solving this game, a distributed best response-based approach is proposed using which the users can reach a Nash equilibrium. Simulation results show that the resulting network at the equilibrium is composed of a mixture of D2D and small cell communication links. The results also show that the proposed approach yields a significant improvement in terms of the average utility per communicating pair when compared with the cases in which the users communicate via only the small cells or via only D2D.

One major issue in the design of active Radio Frequency IDentification (RFID) systems is the need for increasing the coverage, since it is essential for many applications to have a large communication range. In this paper, we propose an active RFID system based on ISO/IEC 18000-7, an energy efficient RFID standard, in which a two-hop relay system is utilized. It is shown that our proposed two-hop relay system can increase the coverage of the reader. In order to increase the efficiency of the two-hop system, we propose a Participation ID (PID) two-hop system. In our modified method, active tags do not participate more than once in a collection round. Hence, the power consumption of active tags is decreased and the throughput of the system is increased. We also evaluate the performance improvement of our modified method in comparison to the existing two-hop relay systems through simulation.

We consider a cellular based primary network coexisting with a secondary network. The primary network consists of multiple service providers (SP) and there are several independent users in the secondary network. The SP are operating on the different frequency spectrum and a group of secondary users intend to share these spectrum with the primary services. This situation is formulated as a bandwidth auction game where each user bids a demand curve and each SP offers a supply curve. We consider two cases of complete information case and incomplete information case or learning games. For two cases, we derive the optimal strategies of the players and the distributed algorithms are presented to obtain the solution of these dynamic games.

In this paper, we consider a decode-and-forward-based wireless multihop network with a single source node, a single destination node, and N intermediate nodes. To increase the spectral efficiency and energy efficiency of the system, we propose a cooperative multihop communication protocol with spatial reuse, in which interference is treated as noise or can be canceled. The performance of a spatial-reused space-time-coded cooperative multihop network is analyzed over Rayleigh fading channels. In particular, the exact closed-form expression for the outage probability at the nth receiving node is derived when there are multiple interference sources over non-i.i.d. Rayleigh fading channels. Furthermore, the outage probability expressions are derived when nodes are equipped with more than one antenna. In addition, to reduce the effect of interference on multihop transmission, we propose a simple power control scheme that is only dependent on the statistical knowledge of channels. In the second approach for managing the interference, linear interference cancelation schemes are employed for both noncooperative and cooperative spatial-reused multihop transmissions. Finally, the analytic results were confirmed by simulations. Simulation results show that the spatial-reused multihop transmission outperforms the interference-free multihop transmission in terms of energy efficiency in low- and medium-signal-to-noise scenarios.

One of the most significant challenges in cognitive radio networks is to design a framework in which the selfish secondary users are obliged to interact with each other truthfully. Moreover, due to the vulnerability of these networks against the jamming attack, providing the security defense is also challenging. In this paper, we investigate a dynamic stochastic medium consisting of some selfish secondary users and a malicious user. Each secondary user participates in an auction and wish to use the unjammed spectrum, and the malicious user aims at jamming a channel by corrupting the communication link. We design a truthful game amongst the secondary users. Furthermore, we propose a zero sum game between the whole set of secondary users and the malicious user. We prove that this problem can be converted to the randomized two-level auctions in which the first auction allocates the vacant channels, and then the second one assigns the remaining unallocated channels. This solution can be changed to a trustful distributed fashion. Finally, simulation results show that the distributed algorithm with much less complexity has almost similar performances to the centralized one.

In the commons model for the spectrum sharing, cognitive users can access the spectrum as long as the target performance in the legitimate primary system is not violated. In this paper, we consider a downlink primary multiple-input-single-output (MISO) system which operates under a controlled interference from the downlink MISO cognitive radio, also called secondary system. We derive exact expressions for outage probability of the primary user under Rayleigh fading, when the primary system is exposed to interference from a secondary base station. Moreover, in high-SNR scenario, a closed-form asymptotic formula for the outage probability is derived, which shows that the primary receiver achieves full spatial diversity under given interference from the secondary user. Next, the optimum transmit power in the secondary system is investigated for maximizing the ergodic capacity when there is an outage constraint at the primary system, and a simple solution is proposed. Finally, the analytical results are confirmed by simulations, in which we analyze the impact of different parameters, such as the number of antennas and the amount of the interference on the system performance; these could be used as system design guidelines.

We consider a decode-and-forward based wireless multihop network with a single source node, a single destination node, and N intermediate nodes. To increase the spectral efficiency and energy efficiency of the system, we propose a cooperative multihop communication with spatial reuse, in which interference is treated as noise. The performance of spatial-reused space-time coded cooperative multihop network is analyzed over Rayleigh fading channels. More specifically, the exact closed-form expression for the outage probability at the nth receiving node is derived when there are multiple interferences over non-i.i.d. Rayleigh fading channels. In addition, we propose a simple power control scheme which is only dependent on the statistical knowledge of channels. Finally, the analytic results were confirmed by simulations. It is shown by simulations that the spatial-reused multihop transmission outperforms the interference-free multihop transmission in terms of energy efficiency in low and medium SNR scenarios.

One of the serious imperfections affecting OFDM systems is transceiver I/Q imbalance. In this letter, closed-form expressions for the outage probability of beamforming OFDM systems with transmit and receive I/Q imbalances are derived. Moreover, the asymptotic behavior and diversity order of the system is investigated. The analytical results are confirmed by simulations.

Physical layer security has emerged as a promising technique that complements existing cryptographic approaches and enables the securing of wireless transmissions against eavesdropping. In this paper, the impact of optimizing physical layer security metrics on the architecture and interactions of the nodes in multi-hop wireless networks is studied. In particular, a game-theoretic framework is proposed using which a number of nodes interact and choose their optimal and secure communication paths in the uplink of a wireless multi-hop network, in the presence of eavesdroppers. To this end, a tree formation game is formulated in which the players are the wireless nodes that seek to form a network graph among themselves while optimizing their multi-hop secrecy rates or the path qualification probabilities, depending on their knowledge of the eavesdroppers' channels. To solve this game, a distributed tree formation algorithm is proposed and is shown to converge to a stable Nash network. Simulation results show that the proposed approach yields significant performance gains in terms of both the average bottleneck secrecy rate per node and the average path qualification probability per node, relative to classical best-channel algorithms and the single-hop star network. The results also assess the properties and characteristics of the resulting Nash networks.

Existing studies on physical layer security often assume the availability of perfect channel state information (CSI) and overlook the importance of channel training needed for obtaining the CSI. In this letter, we discuss how an active eavesdropper can attack the training phase in wireless communication to improve its eavesdropping performance. We derive a new security attack from the pilot contamination phenomenon, which targets at systems using reverse training to obtain the CSI at the transmitter for precoder design. This attack changes the precoder used by the legitimate transmitter in a controlled manner to strengthen the signal reception at the eavesdropper during data transmission. Furthermore, we discuss an efficient use of the transmission energy of an advanced full-duplex eavesdropper to simultaneously achieve a satisfactory eavesdropping performance whilst degrading the detection performance of the legitimate receiver.

First, I would like to thank the associate editor and the author of the Comment for bringing this issue to our attention. While I agree with the mentioned comment, I think the error is rather trivial. The difference is only on a proportional constant for the derived asymptotic expression. Since the main contributions of our paper were the SER expressions in Section III-A and the diversity analysis of the system in Section III-B, the main results are correct. Moreover, in our paper, we used an asymptotic formula based on [Ribeiro et al., 2005, eq. (10)]. The authors in [Ribeiro et al.] also considered the case of M-QAM and M-PSK (see the footnote in p. 1265 of [Ribeiro et al.]), and thus, the expression we used can be a good approximation without multiplying with the constant "c".

Due to the limited energy supplies of nodes in many applications such as wireless sensor networks, energy efficiency is crucial for extending the lifetime of these networks. This paper addresses the cooperative transmission for outage-restricted multihop wireless ad hoc networks. The source node wants to transmit messages to a single destination. Other nodes in the network may operate as relay nodes. In this paper, new multihop cooperative protocol is proposed using the space-time codes for the purpose of energy savings, subject to a required outage probability at the destination. We restrict the cooperation to nodes along a chosen route. Two efficient power allocation schemes are derived, which depend only on the statistics of the channels. Furthermore, three efficient cooperative multihop transmissions are proposed when arbitrary distributed space-time codes are used. The proposed cooperative protocols offer different degrees of energy efficiency, spectral efficiency, complexity, and signalling overhead. Compared to non-cooperative multihop routing, an energy saving of up to 72% is achievable in line networks with 3 relays and an outage probability constraint of 10-3at the destination.

This paper investigates the problem of spectrally efficient operation of a multiuser uplink cognitive radio system in the presence of a single primary link. The secondary system applies opportunistic interference cancelation (OIC) and decodes the primary signal when such an opportunity is created. We derive the achievable rate in the secondary system when OIC is used. This scheme has a practical significance, since it enables rate adaptation without requiring any action from the primary system. The exact expressions for outage probability of the primary user are derived, when the primary system is exposed to interference from secondary users. Moreover, approximated formulas and tight lower and upper bounds for the ergodic sum-rate capacity of the secondary network are found. Next, the power allocation is investigated in the secondary system for maximizing the sum-rate under an outage constraint at the primary system. We formulate the power optimization problem in various scenarios depending on the availability of channel state information and the type of power constraints, and propose a set of simple solutions. Finally, the analytical results are confirmed by simulations, indicating both the accuracy of the analysis, and the fact that the spectral-efficient, low-complexity, flexible, and high-performing cognitive radio can be designed based on the proposed schemes.

Due to the limited energy supplies of nodes, in many applications like wireless sensor networks, energy-efficiency is crucial for extending the networks lifetime. We study the routing problem for multihop wireless ad hoc networks based on cooperative transmission. The source node wants to transmit messages to a single destination. Other nodes in the network may operate as relay nodes. In this paper, we propose a cooperative multihop routing for the purpose of power savings, constrained on a required bit error rate (BER) at the destination. Two efficient power allocation schemes are proposed, which depend only on the statistics of the channels. In the first scheme, each node needs to know only the local channel statistics, and can be implemented in a distributed manner. The second scheme is a centralized power control strategy, which has a higher energy efficiency, at the expense of more complexity and signaling overhead. It is shown that energy savings of 75% are achievable in line networks with 3 relays for BER = 10-4constraint at the destination.

Due to the limited energy supplies of nodes in wireless networks, achieving energy efficiency is crucial for extending the lifetime of these networks. Thus, we study efficient power allocations and transmission protocols for outage-restricted multihop wireless networks based on cooperative transmission. In such multihop networks, a number of nodes, acting as relays, can assist a source node in the transmission of its messages to a single destination. In this paper, several multihop transmission protocols with cooperative routing are proposed. Each of the proposed protocols offers a different rate and energy efficiency. Cooperative routing protocols are introduced using arbitrary distributed space-time codes for the purpose of energy savings, given a required outage probability at the destination. Three efficient cooperative multihop transmissions are proposed, and their corresponding distributed power allocation schemes, which depend only on the statistics of the channels, are also derived. The proposed cooperative protocols offer different degrees of energy efficiency, spectral efficiency, complexity, and signalling overhead. Simulations show that, using the proposed cooperative protocols, substantial energy savings are achievable, compared to non-cooperative multihop routing, in a network having an outage probability constraint.

We consider a wireless relay network with with hybrid-automatic retransmission request (HARQ) and Rayleigh fading channels. In this paper, we analyze the outage probability of the multi-relay delay-limited HARQ system with opportunistic relaying scheme in decode-and-forward mode. A simple and distributed relay selection strategy is proposed for multi-relay HARQ channels. Then, we analyze the performance of the system. We first derive the cumulative density function (CDF) and probability density function (PDF) of the selected relay channels. Then, the CDF and PDF are used to determine the outage probability in the l-th round of HARQ. The packet delay constraint is represented by L, the maximum number of HARQ rounds. Furthermore, closed-form upper-bounds on outage probability are derived, which are used to investigate the diversity order of the system. Based on the derived upper-bound expressions, it is shown that the proposed schemes achieve the full spatial diversity order of N + 1, where N is the number of potential relays. Our analytical results are confirmed by simulation results.

This paper is on the design and performance analysis of practical distributed space-time codes for wireless relay networks with multiple antennas terminals. The amplify-and-forward scheme is used in a way that each relay transmits a scaled version of the linear combination of the received symbols. We propose distributed generalized quasi-orthogonal space-time codes which are distributed among the source antennas and relays, and valid for any number of relays. Assuming M-PSK and M-QAM signals, we derive a formula for the symbol error probability of the investigated scheme over Rayleigh fading channels. For sufficiently large SNR, this paper derives closed-form average SER expression. The simplicity of the asymptotic results provides valuable insights into the performance of cooperative networks and suggests means of optimizing them. Our analytical results have been confirmed by simulation results, using full-rate full-diversity distributed codes.

Estimating channel state information (CSI) in the fast fading conditions is very challenging. In this study, a simple structure for cooperative diversity in decode-and-forward mode is examined, in which the transmitter, the relay and the receiver do not know the CSI. In this scheme, transmission of information is done in a two-phase process. In the first phase, differential modulated signals are radiated from the source. After decoding the received signal in the relay, the source and the relay collectively send information using differential space–time codes. A closed-form optimum power allocation in the sense of minimising pairwise error probability (PEP) for high signal-to-noise ratio (SNR) scenarios has been obtained. An interesting property of the optimum point is that it is independent of the channel statistics and the position of the relay, which improves its feasibility in the future communication systems. Numerical simulations verify the analytical results.

Due to the limited energy supplies of nodes in many applications like wireless sensor networks, energy efficiency is crucial for extending the lifetime of these networks. This paper addresses the routing problem for outage-restricted multihop wireless ad hoc networks based on cooperative transmission. The source node wants to transmit messages to a single destination. Other nodes in the network may operate as relay nodes. In this paper, a new cooperative routing protocol is introduced using the Alamouti space-time code for the purpose of energy savings, given a required outage probability at the destination. Two efficient power allocation schemes are derived, which depend only on the statistics of the channels. In the first scheme, each node needs to know only the local channel statistics, and can be implemented in a distributed manner. In the second scheme, a centralized power control strategy is proposed, which has a higher energy efficiency, at the expense of more complexity and signalling overhead. Compared to non-cooperative multihop routing, an energy saving of 80% is achievable in line networks with 3 relays and an outage probability constraint of 10-3at the destination.

We consider a wireless relay network with multiple antennas terminals over Rayleigh fading channels, and apply distributed space-time coding (DSTC) in amplify-and-forward (A&F) mode. It turns out that, combined with power allocation in the relays, A&F DSTC results in an opportunistic relaying scheme, in which the best relay is selected to retransmit the source's space-time coded signal. Next, assuming M-PSK or M-QAM modulations, we analyze the performance of the cooperative diversity wireless networks using A&F opportunistic relaying with the multiple-antennas source and destination. We first derive the probability density function (PDF) of the received SNR at the destination. Then, the PDF is used to determine the symbol error rate in Rayleigh fading channels. Then, we derived closed-form approximations for SER in high SNR scenario, from which we find the diversity order of system Rmin{Ns, Nd}, where R, Ns, and Nd are the number of the relays, the source antennas, and the destination antennas, respectively. Simulation results show that the proposed system obtain 2 dB gain in SNR over DSTC for BER 10-5, when R = 2, Ns= 2, Nd= 2.

This letter analyzes the performance of single relay selection cooperative wireless networks usingamplify-andforwardrelaying. The network channels are modeled as independent, nonidentical, Rician distributed coefficients. We derive approximate formulas for the symbol error rate (SER) of the opportunistic relaying cooperative network. We first derive the PDF of the approximate value of the total SNR. Then, assumingM-PSK orM-QAM modulations, the PDF is used to determine the SER. For sufficiently large SNR, this letter derives the close-form average SER. The simplicity of the asymptotic results provides valuable insights into the performance of cooperative networks and suggests means of optimizing them. We also use simulation to verify the analytical results. Results show that the derived error rates are tight bounds particularly at medium and high SNR.

Cooperative communications via distributed space-time codes has been recently proposed as a way to form virtual multiple-antennas that provide dramatic gains in slow fading wireless environments. In this paper, we consider the design of practical distributed space-time codes for wireless relay networks using the amplify-and-forward (AF) scheme, where each relay transmits a scaled version of the linear combinations of the received symbols and their complex conjugate. We employ GABBA codes, which are systematically constructed, orthogonally decodable, full-rate, full-diversity space-time block codes, in a distributed fashion. Our scheme is valid for any number of relays with linear orthogonal decoding in the destination, which make it feasible to employ large numbers of potential relays to improve the diversity order. We generalize the distributed space-time codes in AF mode when the source-destination link contributes in both phases of the transmission. Assuming MPSK or M-QAM constellations and maximum likelihood (ML) detection, we derive an approximate formula for the symbol error probability of the investigated scheme in Rayleigh fading channels. The analytical results are confirmed by simulations, indicating both the accuracy of the analysis, and the fact that low-complexity, flexible, and high-performing distributed space-time block codes can be designed based on GABBA codes.

The minimum power allocation strategy for the repetition-based amplify-and-forward (AF) relaying scheme given a required symbol error rate (SER) at the destination is first derived. We consider the scenario where one source and multiple partners cooperate to transmit messages to the destination. The power allocation strategy that demands the minimum transmit power of all cooperating partners is described and analyzed. However, this power minimization strategy does not necessarily maximize the lifetime of battery-limited systems. Then, we propose two other AF cooperative schemes to exploit the statistical channel state information (CSI), the residual battery energy, and the quality-of-service (QoS) requirement. It is shown that the network lifetime can be extended considerably by taking all these three factors into account.

Estimating channel state information (CSI) in the fast fading conditions is very challenging. In this paper, a simple structure for cooperative diversity in decode-and-forward mode is examined, in which the transmitter, the relay and the receiver do not require to know CSI. In this scheme, transmission of information is done in a two phase process. In the first phase, differential modulated signals are radiated from the source. After decoding the received signal in the relay side, the source and the relay collectively send information using differential space-time codes. The optimum power allocation in a sense of minimizing pairwise error probability (PEP) in high SNR scenarios has been obtained using an analytical method. An interesting property of the optimum point is that it is independent of the channel statistics and the position of the relay, which improves its feasibility in the future communication systems. Numerical simulations verify the analytical results.

The idea of space-time coding, devised for multiple-antenna systems, can be applied to communication over a wireless relay network. This paper is on the design of practical distributed space-time codes for wireless relay networks, in which uses amplify-and-forward (AF) scheme in a way that each relay transmits a scaled version of linear combination of the received symbols. We use the recently presented GABBA codes, which are systematically constructed, orthogonally decodable, full-rate, full-diversity space-time block codes, in a distributed fashion. Our scheme is generalized to any number of relays with linear orthogonal decoding in the destination, which make it feasible to employ large number of potential relays to improve diversity order. Assuming BPSK modulation and maximum likelihood (ML) detection, we derive a formula for the bit error probability of the investigated scheme in Rayleigh fading channels. Our analytical results have been confirmed by simulation results, using full-rate, full-diversity distributed codes.