This research paper investigates the secrecy performance in a vehicular network. A legitimate vehicular source aims to transmit confidential information to a legitimate vehicular destination, while a passive vehicular eavesdropper attempts to intercept this transmission. To enhance the practical relevance of the system model, the probabilistic existence of an obstructing vehicle is considered. This obstructing vehicle can potentially disrupt communication links between the source and the destination, the source and the eavesdropper, or both. To mitigate the adverse effects of obstruction and eavesdropping, a reconfigurable intelligent surface (RIS) is employed. Additionally, the source employs a power-splitting scheme to generate artificial noise (AN), a physical-layer security technique to degrade the wiretap channel. In this power-splitting scheme, the source’s transmission power is divided into two portions: confidential transmission and generating the AN signal. Closed-form expressions are derived for the outage probability, upper bound intercept probability, and upper bound secrecy outage probability (SOP), along with their asymptotic expressions. The influence of power-splitting ratio, transmission power, number of reflecting elements of the RIS, density of the obstructing vehicle, and the channel conditions on the performance metrics is investigated through numerical results. The results are extended to encompass practical impairments, specifically examining the impacts of node mobility, channel state information feedback delay, and AN leakage at the destination. It has been observed that an increase in the density of large obstructing vehicles leads to a reduction in the SOP. However, this degradation can be mitigated by increasing the number of passive reflectors of RIS. Additionally, based on the closed-form upper bound expression of the SOP, a power allocation optimization problem is solved to minimize the SOP in terms of the power-splitting ratio. The accuracy of the derived closed-form expressions has been verified through Monte Carlo simulations.

This study examines a real-time status update system featuring energy-harvesting sensing devices and intensive packet processing. Diverging from existing research in the same area, our approach employs partial offloading, where packets are split between local server and mobile edge computing server. Based on the available energy, the device determines the offloading ratio in order to minimize both the age of information (AoI) and the energy consumption. Due to the randomness of the environment and the need to take sequential decisions, the problem is formulated using a Markov decision process. The state transition over subsequent decision epochs is modelled using a multi-dimensional Markov chain to facilitate writing the Bellman equation and finding the optimal offloading ratio. The numerical results show that the partial offloading scheme exploits the available energy more effectively to decrease the AoI compared with both the total and binary offloading schemes unless the channel is in a good state with high probability.

Due to the rapid development of the Internet of Things (IoT) applications, which generate vast volumes of data at high speeds, security and privacy issues have become challenging. IoT devices use the advanced encryption standard algorithm before transmission. However, since the system communicates through amplify-and-forward relays, the data may be leaked through the untrusted relays. Depending on a mathematical tool may affect the data security vulnerability. Thus, to enhance the system security, physical layer security is used to transmit a jamming signal to confuse the untrusted relay nodes. Hence, the proposed framework ensures security by combining the physical and data layer security which comes with a cost regarding system complexity, system latency, and energy consumption. The proposed framework addresses the joint problem of physical and data layer security, multicell association, task offloading, users’ power allocation, and service caching in multitier communication and edge computing networks. The objective is to minimize the system latency and energy consumption under the secrecy capacity constraint. Due to the NP-hard nature of the joint problem, we use a low-complexity Lyapunov drift-plus-penalty optimization technique based on the Gibbs sampling algorithm. The simulation results demonstrate the proposed framework’s superiority over the state-of-the-art in terms of high secrecy capacity and low computational complexity. When the secrecy capacity threshold increases, the secrecy capacity is enhanced by approximately 5.72%, while the system latency and energy consumption increase by 38.18% and 69.99%, respectively, compared to the literature.

The security of a vehicular network utilizing wireless energy transfer in conjunction with near-field non-reconfigurable metasurface (NRMS) technology is analyzed in this article. The system involves an energy-limited mobile source that collects energy from a roadside power beacon using the time-switching (TS) scheme, after which it transmits signals to the destination while a passive eavesdropper tries to intercept them. Two cases of antennas are analyzed, namely, NRMS-coated and standalone antennas. We derived realistic statistical models for double Nakagami-mfaded channels to model the direct and reflected signal paths influenced by the NRMS-coated antenna. Analytical expressions are derived for secrecy outage probability (SOP), asymptotic SOP, secrecy diversity order (SDO), average secrecy outage duration, and average secrecy outage rate. A SOP minimization problem is formed and solved to find the optimal TS ratio using particle swarm optimization. Monte Carlo simulations validated the accuracy of our analytical closed-form expressions. The NRMS-coated antenna reaches the same SOP with 10 dB less power and achieves a higher SDO based on its number of reflective elements compared to the standalone antenna.

This paper considers a computation-intensive status update system with energy harvesting technology. The status update packets can be processed locally or partially offloaded to a mobile edge computing server. Using the stochastic hybrid system approach, we analyze the moment generating function of the age of information (AoI) for three different disciplines (preemption, discarding, and blocking) under zero-wait policy. The numerical results show that the preemption discipline gives the best performance while the discarding discipline is the worst. The results demonstrate the importance of obtaining higher AoI moments and facilitate choosing an offloading ratio that satisfies a given average AoI constraint.

Integrating cognitive radio technology with energy harvesting capabilities to the Internet of Things networks offers a promising avenue for tackling spectrum scarcity and battery limitation issues. This study explores a single-channel cognitive radio network including two secondary users who generate two distinct traffic types: packets with deadlines and status update information. Packets are dropped only when failing to reach their destination within the deadline. Leveraging the drift-plus-penalty approach, we develop a scheduling policy to minimize the average drop rate of these packets subject to a data freshness constraint. Simulation results depict how variations in main system parameters, such as the primary user’s transmission power and energy arrival rate, impact the average drop rate. Additionally, experimental simulations confirm that our proposed policy outperforms the performance of a suggested baseline policy with a notable gap.

In this work, we investigate the security performance of an underlay cognitive radio network (CRN) with ambient backscatter communication (AmBC), where a backscattering device (BD) shares the spectrum and the receivers with the secondary user. Different from the related work, we consider a secondary user transmitter (ST) with multiple antenna in an AmBC-CRN with multiple receivers and multiple passive eavesdroppers. The ST performs joint antenna-user selection to enhance its security performance and overcome the performance degradation caused by BD interference. Considering the Nakagami-m fading model, closed-form expressions are derived for the secrecy outage probability for both the ST and the BD transmissions. Monte Carlo simulations are performed to validate the derived closed-form expressions. Numerical results show that employing joint antenna-user selection enhances the ST security performance by exploiting antenna and user diversity.

Currently, the pervasive adoption of internet of things technology sheds light on the significance of real-time status update systems. The age of information (AoI) metric has been devised to reflect the strict information timeliness of such systems. Bufferless packet management scheme has demonstrated higher effectiveness in the AoI minimization. However, the existing preemptive (PR) and non-preemptive (NP) service disciplines operate independently of the system state, thereby reducing the system’s adaptability to varying system parameter settings, such as service time distribution and traffic loading condition. Therefore, we propose an elapsed-time-based hybrid PR/NP discipline to govern the service preemptions in a single-source M/Er/1/1 queueing scheme. The preemption is declined when the elapsed service time surpasses a predetermined threshold (controlling parameter). The average AoI is analyzed using the stochastic hybrid system approach. The numerical study demonstrated that the proposed discipline, owing to its threshold parameter, fulfills the optimality of the AoI performance, especially under highly dispersed Erlang service time distributions and higher traffic loading conditions.

This paper presents a performance analysis of the Age of Information ($A$oI) in full-duplex (FD) cooperative (C) non-orthogonal multiple access (NOMA) integrated with simultaneous wireless information and power transfer (FD-C-SWIPT-NOMA). Particularly, approximated closed-form expressions for the average block error rate (BLER) are derived for the proposed scheme and validated by Monte Carlo simulations. Based on the derived expressions of the average BLER, the expected weighted sum of AoI (EWSAoI) is obtained for the proposed scheme. Additionally, the proposed scheme is compared with other baseline schemes such as orthogonal multiple access (OMA), NOMA, and half duplex (HD) cooperative SWIPT NOMA schemes in terms of EWSAoI. Finally, the effect of variable power allocation, distances, and residual self-interference (RSI) on the AoI is analysed and simulation results demonstrate the superiority of the proposed scheme compared to baseline schemes in terms of the EWSAoI.

Accurate channel estimation is crucial for the proper operation of reconfigurable intelligent surfaces (RIS). This paper introduces a convolutional neural network (CNN) approach for multi-user RIS channel estimation that incorporates the zero-shot noise-to-noise (N2N) methodology within its architecture. In contrast to techniques that rely on clean training data, the proposed method learns from the noisy data itself to figure out how to remove the noise. The proposed zero-shot N2N self-learning demonstrates improved performance and a fast convergence rate in the RIS channel estimation.

Due to the wide range of intensive computational applications and ubiquitous connectivity of the Internet of Things (IoT) paradigms, it has become crucial to develop a new platform that can achieve low delay, high network throughput, and enhanced quality of service (QoS). This paper proposes a joint user association, service caching, and task offloading strategy to reduce delay and enhance users’ QoS in multi-tier communication and multi-tier edge computing heterogeneous networks (HetNets). The considered system model consists of multi-users with different tasks and service data sizes communicating in a heterogeneous network of one massive multiple-input multiple-output (M-MIMO) macro base station and some small base stations. The proposed work investigates user association, power allocation , optimum service data caching, and task offloading strategies at the computing network edges. Thereby, the objectives of this work are to propose an efficient framework to reduce the system delay, increase the network throughput, and meet the user requirements in multi-tier communication and multi-tier edge computing heterogeneous networks . The simulation results show that the proposed algorithm outperforms the state-of-the-art with a 49.48% decrease in system delay, 80% reduction in cost and hardware complexity in terms of the reduced number of installed antennas, and 48.58% enhancement in the network throughput.

Abstract For many wireless sensor networks applications, a powerful localization algorithm is required to determine the exact positions of sensor nodes. In this paper, a new localization algorithm is presented which combines the distance vector hop (DV-Hop) algorithm with the shuffled shepherd optimization algorithm to determine the position for each unknown node within 3-D space. Studying the localization problem in 3-D space is more realistic, but more challenging due to the enlarged search space. Comparison of our proposed algorithm with its alternatives in literature shows that it offers improved accuracy and more stable performance with respect to changes in nodes density and communication range.

In vehicular communications environments, channels are characterized as dynamic and highly mobile. As uch, estimating the vehicular communication channel with a massive number of antennas installed at the transmitter and receiver is considered a daunting task for conventional estimators and deep-learning approaches. Classical estimators provide inaccurate estimation results, and the deep learning algorithms require a huge dataset for training the model. This paper proposes a transfer learning and meta-learning approach for channel estimation in outdoor vehicular environments with millimeter-wave transmission frequencies above 6 GHz. The proposed system learns a good initialization of the model weight parameters using a few samples and a small number of gradient steps to achieve model convergence. Simulation results show that the proposed algorithm outperforms the conventional least square estimator in the outdoor millimeter-wave vehicular environments.

Vehicular ad hoc networks (VANETs) have become a popular research area in recent years, particularly in vehicle-to-everything (V2V) applications for intelligent transportation systems (ITS). However, big vehicles can cause communication disruptions due to their size and position on the road, leading to unreliable V2V applications. In this paper, we propose a solution to the problem of broken communication links caused by big vehicle shadowing, by establishing connectivity between two clusters of vehicles disconnected by the big vehicles on a lane through communicating clusters on the adjacent lane. We analyse the connectivity probability in a two-way road section and demonstrate the effectiveness of our proposed solution. The proposed solution can enhance the performance of V2V applications. Simulated and numerical results indicate that, adjacent lane vehicle cluster on the road in a free-flow traffic can maintain the communications link shadowed by big vehicles.

The integration of unmanned aerial vehicles (UAVs) into wireless networks is gaining significant attention in the fifth generation (5G) and beyond technologies. The use of UAVs has the potential of expanding coverage and providing efficient and reliable communication services, especially in remote and inaccessible areas. While other studies have explored sum-rate maximization via user pairing considering a multi-armed bandit (MAB) for a single UAV, the use of MAB in multiple UAVs especially under non-orthogonal multiple access (NOMA) scheme is not fully explored. This paper presents an algorithm for user pairing targeting sum-rate maximization of multi-UAV NOMA networks by applying multi-agent bandits that employ two-sided matching. The proposed method performs user association and power allocation with no coordination among the UAVs. The simulation results demonstrate the superior performance of the proposed method which is very close to that achieved by exhaustive search and outperforms random matching.

In the recent decades, free-space optical (FSO) communication technology has gained significant importance owing to its promising unique features: high user capacity, license-free spectrum, ease and quick deploy-ability. However, the performance of FSO communication systems depends on the uncontrollable terrestrial atmospheric effects. The second main challenge is that the FSO system performance degrades as a line-of-Sight (LoS) technology due to the misalignment transmitter and receiver. The third challenge is the consideration of time value of money, which is central to most engineering economic analyses in employing communication systems. The opportunity cost of making one choice over another must also be considered. This paper presents a proposed FSO system design model for mitigating the three performance challenges we mentioned. The results show an enhancement by 83.34% in system efficiency in case of moderate scintillation (using gamma-gamma model). This proposed hybrid model is proved to be applicable to any atmospheric channel conditions.

In this paper, a general spectrum access scheme is introduced for multi-class secondary users operating in a hybrid interweave/underlay cognitive radio network. The hybrid channel access mode combines the benefits of interweave transmission (opportunistic access with high throughput) and that of the underlay transmission (anytime transmission with controlled power). Additionally, classifying the SUs helps to meet their different quality of service (QoS) requirements. The proposed scheme tackles three challenges: resolving the contention of the SUs to access the channel, scheduling an arbitrary number of SU classes, and providing a tunable spectrum resources allocation scheme. Specifically, each class of SUs is assigned a number of time slots for exclusive hybrid channel access according to their QoS requirements. The numerical results show the superiority and flexibility of the proposed scheme compared to other related work in literature.

In this paper, the hybrid interweave/underlay channel access mode is studied for an energy harvesting (EH) cognitive radio network with multi-class secondary users (SUs). The hybrid channel access mode combines the benefits of interweave transmission (opportunistic access with high throughput) and that of the underlay transmission (any time transmission with controlled power). EH upgrades the SUs' devices to be self sustainable. Additionally, classifying the SUs helps to meet their different quality of service (QoS) requirements. The system is modelled as a mixed observable Markov decision process (MOMDP) to handle the uncertainty in the primary user (PU) activity and consider future rewards. The MOMDP model is solved to maximize the SUs' throughput using two algorithms, namely, the point-based value iteration and the heuristic search value iteration (HSVI). Moreover, skipping the schedule of some SUs is proved to increase the channel utilization. The HSVI is proved to be efficient and reduces the time complexity significantly. Compared to related work in literature, the proposed model is proved to be superior in terms of throughput, tunable to meet the different QoS requirements of SU classes, and can accommodate any number of SU classes. Finally, the effect of some system parameters on the proposed system performance is studied and some insights are derived about the structure of the optimal policy and the system parameters values.

In this paper, we investigate the mutual mobility effect for independent multiple primary users and numerous secondary users on the spectrum sensing capability of secondary users. The proposed system model adopts two different mobility models; namely, the random walk (RWL) model and random waypoint (RWP) model with varying numbers of primary mobile users and secondary mobile users in the network. Closed-form expressions for the detection capability and normalized sensing capacity were derived. The results show that the increase in the number of independent mobile users following a random mobility model has an impact on the total sensing capacity over unoccupied bands.

Spectrum sensing task is an essential operation in cognitive radio networks. As such, this paper considers the impact of primary mobile users whose location and dynamic spectrum use can be tracked and sensed by collaborative secondary users. We evaluate the probability of detection for two simplistic random mobility models by acquiring compressed signal measurements at the fusion center. The collaborative signal acquisition is to reduce the computation at the secondary user side. Combined with the recovered signal via compressed sensing, a localization technique by Kalman filtering is used to track a primary mobile user in the network region. For a random mobility model, it is shown that better spectrum sensing performance can be achieved with a high probability of detection. Further, for pseudo-static movements having pause time factor, the detection performance increases. Simulation results are given to corroborate the approach used in the evaluation.

The introduction of cognitive radio technology in licensed 5G networks could significantly enhance the overall system capacity and number of served users. In this context, this work discusses the admission of new cognitive radio secondary users (SUs) in the fifth generation (5G) Heterogeneous Networks (HetNets) as well as the allocation of the channels over the secondary cognitive network, using a many-to-one matching game and auctions theory. Simulation results show that the used matching algorithm for users admission is of low complexity as well as the existence of a Walrasian equilibrium point for the channels allocation problem.

This paper investigates the secrecy performance of a multiuser system that utilizes transmit antenna selection scheme at the base station and adopts threshold-based selection diversity opportunistic scheduling over legitimate nodes. The legitimate transmission suffers from the presence of noncolluding (Non-Col) and colluding (Col) multiple passive eavesdroppers. Both the legitimate and eavesdropping nodes are assumed to suffer from co-channel interference (CCI) signals from independent channels that follow Rayleigh fading. Closed-form expressions for the probability density functions and cumulative density functions of the end-to-end signal-to-interference-plus-noise ratio for both eavesdropping scenarios in the presence of CCI signals are derived. In addition, closed-form expressions for the network secrecy outage probability (SOP) for Non-Col/Col scenarios are derived. At the high signal-to-noise ratio values, closed-form expressions for the asymptotic secrecy outage probabilities are obtained. Following this obtained asymptotic analysis, an optimization problem for power allocation is formulated and solved to improve the secrecy performance of the network by minimizing the asymptotic SOP for both Col and Non-Col cases. The derived analytical expressions are then validated using both simulations and numerical results.

In this paper, we investigate the performance of the energy harvesting (EH) concept in full-duplex multiple-input-single-output cognitive radio networks (FD-MISO-CRNs). In the proposed model, a single secondary user (SU) harvests energy from a hybrid base station (HBS) and the primary user (PU) transmission on the downlink and transmits its data on the uplink over Nakagami-m fading channels. Assuming underlay CRN, the total SU transmitted power (i.e., data and energy) cannot exceed the maximum allowable PU interference threshold. In practice, the HBS might have no prior knowledge on the SU battery status. A closed-form expression for the SU exact outage probability is derived and simplified to its asymptotic formula for the high signal-to-noise-ratio (SNR) regime. Based on the derived expressions, a power allocation optimization problem is formulated to minimize the SU asymptotic outage probability. Simulation results are obtained to validate the derived analytical formulas. Moreover, The proposed power allocation model shows a significant enhancement of the system performance compared to conventional equally distributed power allocation model.

This paper presents the application of a particular class of matching game models, namely the Boston school choice approach, to the problem of user association in heterogeneous networks. Simulation results are provided to assess the performance of the Boston mechanism and the Gale-Shapley algorithm used in the college admission game concerning overall performance, average user utility and execution time.

Non-Orthogonal Multiple Access (NOMA) is a promising multiple access technique for the 5thgeneration (5G) mobile communication systems. In this paper, an energy efficient power allocation scheme is derived for a general number of users per cluster multiple input multiple output (MIMO) downlink NOMA system. The proposed scheme idea is based on converting the difficult energy efficiency power allocation problem into an equivalent spectral efficiency power allocation problem and then dividing this equivalent problem into multiple simple cluster sum rate maximization problems. In addition, a user clustering scheme is proposed to maximize the NOMA system energy efficiency by first designing the detection vectors to convert the MIMO users channel matrices into their equivalent channel vectors and distribute the users on the clusters based on their equivalent channel gains. The users are clustered such that those with the largest equivalent channel gains are selected as cluster heads and the rest of users in each cluster are selected to maximize the equivalent channel gain difference between each other. Numerical results show that the proposed framework improves the system energy efficiency of the MIMO NOMA system at different values of the total transmit power, the minimum required date rates, the number of users per cluster and at different users' distance distribution scenarios.

This paper investigates the secrecy performance of a multiuser threshold-based transmit antenna selection scheme (TAS/tSD) in the presence of co-channel interference (CCI) signals and the existence of a passive eavesdropping node. In particular, an exact closed-form expression for the secrecy outage probability is derived. Then, the asymptotic secrecy outage closed-form expression is obtained at the high signal-to-noise ratio (SNR) values. Based on the obtained asymptotic analysis, an optimization problem for power allocation is formulated and solved to improve the secrecy performance of the system concerning minimizing the asymptotic secrecy outage probability. Numerical and simulation results are obtained to justify the obtained analysis.

In this paper, the impact of radio frequency (RF) co-channel interference (CCI) on the performance of multiuser (MU) mixed RF/free space optical (FSO) relay network with opportunistic user scheduling is studied. In the considered system, a user is opportunistically selected to communicate with a single destination through an amplify-and-forward (AF) relay in the presence of a single passive eavesdropper. The RF/FSO channel models are assumed to follow Rayleigh/Gamma-Gamma fading models, respectively with pointing errors and identical RF CCI signals. Exact closed-form expression for the system outage probability is derived. Then, an asymptotic expression for the outage probability is obtained at the high signal-to-interference-plus-noise ratio (SINR) regime. The asymptotic results are used to formulate a power allocation problem to obtain optimal RF transmission power. Then, the secrecy performance is studied in the presence of CCI at both the authorized relay and eavesdropper by obtaining exact and asymptotic closed-form expressions for the intercept probability. The derived analytical formulas herein are supported by numerical and simulation results to clarify the main contributions of the work.

In this paper, we study the performance of multiuser (MU) single-input-multiple-output (SIMO) mixed radio frequency (RF)/free space optical (FSO) relay network with transmit opportunistic scheduling. The considered system includes multiple users, one amplify-and-froward (AF) relay, one destination and a multiple-antenna eavesdropper. The users are connected with a multi-antenna relay through RF link and the relay is connected with the destination through an FSO link. Maximal ratio combining (MRC) scheme is used at the relay node to combine the received signals at its different antennas. In the analysis, the first hop channels are assumed to follow Nakagami-m fading model and the second hop channel is assumed to follow Gamma-Gamma fading model with considering the effect of pointing errors. Closed-form expressions are derived for the outage probability, average symbol error probability (ASEP) and ergodic channel capacity. Furthermore, the system performance is studied at high signal-to-noise ratio (SNR) regime where the diversity order and coding gain are derived and analyzed. Using the asymptotic results, the power of the selected best user is determined to minimize the system outage probability under the dominant RF or FSO link. Then, the considered system secrecy performance is investigated and an exact closed-form expression for the intercept probability is derived. Monte-Carlo simulations are provided to validate the achieved exact and asymptotic results.

In this work, a new cooperative cognitive two-way amplify-and-forward (AF) relaying scheme is proposed. In this model, a primary user (PU) network consisting of two PU sources communicate with each other via a single AF relay. In addition, a secondary user (SU) source transmits its data to a SU destination via the same PU relay node via decode-and-forward protocol. In order to mitigate SU interference caused to the PU network, the PU network considers the SU network pairs (i.e., source and destination) as two additional relay nodes helping the original PU relay node in improving the PU network performance. As a reward for its cooperation, the PU network allows the SU network to communicate simultaneously via the PU relay node using the decode-and-forward (DF) protocol. Two power allocation optimization problems are formulated; the first problem minimizes the weighted sum of the average symbol error probability (SEP) of both PU and SU systems, whereas the second problem maximizes the total achievable sum rate of the PU and SU networks. Results show that the error performance of the proposed model outperforms the conventional two-way relaying networks with amplify-and-forward protocol. Moreover, the total achievable sum rate of the proposed model is higher than the total achievable rate of the conventional ones.

In this paper, we study the performance of multiuser single-input multiple-output mixed radio frequency (RF)/free space optical (FSO) relay network with opportunistic user scheduling. The considered system includes multiple users, one amplify-and-forward relay, one destination, and a multipleantenna eavesdropper. The users are connected with the relay node through RF links and the relay is connected with the destination through an FSO link. Both maximum ratio combining and selection combining schemes are used at the multipleantenna relay to combine the signal received from the best user on different antennas. The RF/FSO channels models are assumed to follow Nakagami-m/gamma-gamma fading models with pointing errors. Closed-form expressions are derived for the outage probability, average symbol error probability, and ergodic channel capacity. Then, the power of the selected best user is determined to minimize the system asymptotic outage probability under the dominant RF or FSO link. Then, the considered system secrecy performance is investigated, where the closedform expressions for the intercept probability are derived. Finally, we propose a new cooperative jamming model in which the worst user is selected by the authorized system to jam the existing eavesdropper. Monte-Carlo simulations are provided to validate the achieved exact and asymptotic results.

Abstract In this paper, we examine the impact of antenna correlation on transmit antenna selection with receive maximal ratio combining (TAS/MRC) in multiple‐input multiple‐output multiuser underlay cognitive radio network (MIMO‐MCN) over a Nakagami‐m fading environment. The secondary network under consideration consists of a single source and M destinations equipped with multiple correlated antennas at each node. The primary network composed of L primary users, each of which is equipped with multiple correlated antennas. For the considered underlay spectrum sharing paradigm, the transmission power of the proposed secondary system is limited by the peak interference limit on the primary network and the maximum transmission power at the secondary network. In particular, we derive exact closed‐form expressions for the outage probability and average symbol error rate of the proposed secondary system. To gain further insights, simple asymptotic closed‐form expressions for the outage probability and symbol error rate are provided to obtain the achievable diversity order and coding gain of the system. In addition, the impact of antenna correlation on the secondary user ergodic capacity has been investigated by deriving closed‐form expressions for the secondary user capacity. The derived analytical formulas herein are supported by numerical and simulation results to clarify the main contributions. Copyright © 2016 John Wiley & Sons, Ltd.

In this paper, the impact of co-channel interference (CCI) on the secrecy performance of the dual-hop decode-and-forward relaying network is investigated. First, the security-reliability trade-off (SRT) analysis is studied for conventional single-hop networks under a single passive eavesdropper attack. Then, the SRT analysis is investigated to the opportunistic relay selection (ORS) model in the presence of independent and identically distributed (i.i.d.) interfering signals. Moreover, the proposed work enhances physical layer (PHY) security performance of ORS model using cooperative jamming techniques (CJ-ORS). For this purpose, new closed-form expressions are derived for intercept probability and outage probability of CJ-ORS model in the presence of interference over Rayleigh fading channels. A power allocation optimization problem is formulated and solved for enhancing the system security. The derived analytical formulas herein are supported by numerical and simulation results to clarify the main contributions of the paper.

In this paper, we investigate the secrecy performance achieved by a new cooperative cognitive radio (CR) model which employs the two- path amplify-and-forward (AF) relaying protocol. In this model, the secondary user (SU) network pairs (i.e., transmitter and receiver) serve as relaying nodes for the primary user (PU) network. The SU network employs the inter-relay- interference (IRI) between the two relay nodes to transmit its data while relays PU data. In this work, the improvement in PU network physical layer security against multiple passive eavesdroppers is studied in two different scenarios. Optimization problems are formulated to find the optimal power allocation approach that maximizes PU secrecy rate in terms of SU transmission power, amplifying factors. The Lagrangian multipliers method is used to obtain the optimal solutions. Numerical results and simulations are provided to prove that the new cooperative CR model can achieve a non-zero secrecy rate even if the wiretap channel is better than the main channel.

In this work, a new cooperative two-way relaying (TWR) model with amplify-and-forward (AF) protocol is proposed in which a primary user (PU) network consisting of two PU sources communicate with each other via a single relay. In addition, a secondary user (SU) source transmits its data to its SU destination via the same PU relay node. In order to mitigate SU interference caused to the PU network, the PU network considers the SU network pairs (i.e., source and destination) as two additional relay nodes helping the original PU relay node in improving the PU network performance via orthogonal space-time block code (OSTBC) technique. As a reward, the PU network allows the SU network to communicate simultaneously via the PU relay node using the decode-and-forward (DF) protocol. A power allocation optimization problem is formulated to minimize the weighted sum of the average symbol error probability of both PU and SU systems. Results show that the error performance of the proposed model outperforms the conventional TWR-AF model.

In this paper, we examine the impact of antenna correlation on transmit antenna selection with maximal ratio combining (TAS/MRC)in multiple-input-multiple-output multiuser cognitive relay networks (MIMO-MCRNs). A single secondary user (SU) source communicates with M SU destinations via SU decode-and-forward (DF) relay over Rayleigh fading channels and in the presence of L PU destinations. Each node in the considered SU network is equipped with multiple correlated antennas as well as the L PU destinations. The SU network employs underlay spectrum sharing paradigm in which the SU transmission power is limited by peak interference temperature limit on the PU network and the maximum allowable transmission power at each node of the SU network. As a measure of performance, we derived an exact expression for the outage probability of the proposed SU network. To gain further insights, a simple asymptotic expression for the outage probability is provided to obtain the achievable diversity order and coding gain.

In this paper, we investigate the impact of multiple correlated antennas on the performance of transmit antenna selection with receive maximal ratio combining (TAS/MRC) model. Multiple correlated antennas are considered at the primary and secondary users in dual-hop underlay cognitive radio system. The transmit power condition of our proposed spectrum-sharing system is governed by interference temperature limit on the primary networks and the maximum transmission power at the secondary network. An exact expression for the outage probability of the proposed system is derived. To gain further insights, simple asymptotic expression for the outage probability is provided to obtain the achievable diversity order and coding gain of the system. All derived analytical results are corroborated by simulation results to show the correctness of our derived results.

In this paper, we examine the impact of antenna correlation on transmit antenna selection with receive maximal ratio combining (TAS/MRC) in multiple-input multiple-output multiuser network (MUN-MIMO) with single source, M destinations with underlay spectrum sharing over Nakagami-m fading environment. The secondary network under consideration is equipped with multiple correlated antennas at each node. The primary networks composed of L primary users (PUs) equipped with multiple correlated antennas. For the underlay spectrum sharing transmission, the transmit power condition of the proposed MU spectrum-sharing system is limited by peak interference temperature limit on the primary networks and the maximum transmission power at the secondary network. In particular, we derive an exact expression for the outage probability and SER of the proposed system. To gain further insights, simple asymptotic expression for the outage probability and SER are provided to obtain the achievable diversity order and coding gain of the system.