Secondary Receiver Research Articles

On secrecy performance of RIS-assisted CRNs leveraging discrete phase control

In this paper, we investigate the physical layer security (PLS) of a cognitive radio network (CRN) assisted by a reconfigurable intelligent surface (RIS) based on discrete phase control. Specifically, the phase shifts of the RIS are designed to maximize the received signal-to-noise ratio (SNR) at the secondary receiver. In the presence of passive eavesdropping, we address the secrecy outage performances for the considered system under two different scenarios whether the direct link exists or not. To characterize the performance, novel exact expressions of secrecy outage probability (SOP) are derived leveraging the Gaussian–Chebyshev quadrature. We also conduct the asymptotic analysis to study the influence of the main parameters such as the number of reflect elements of RIS and the number of quantization bits on the secrecy performance of our proposed system. Finally, our analytical results are verified through performing Monte Carlo simulations. Simulation results show that significant security enhancement can be achieved in CRN by employing the RIS.

Resource allocation for relaying cognitive network with energy harvesting

This paper investigates a relay-based cognitive wireless-powered communication network with multiple secondary receivers and a secondary relaying network. In the secondary network, a relay adopts an energy model to harvest energy from radio frequency signals of the primary and secondary sources and subsequently utilizes the harvested energy to cooperate with the source for information transmission to multiple Internet-of-things users over time-division multiple access. The research group formulated a novel optimization problem that jointly optimizes the power and time fraction for energy and information transmission to maximize the sum throughput of the secondary network. The authors first converted the non-convex problem to a more computationally tractable problem and then proposed an iterative algorithm in which closed-form solutions are obtained at each iteration. Thus, simulation results verify and demonstrate the effectiveness of the proposed approach.

AoI minimization of ambient backscatter-assisted EH-CRN with cooperative spectrum sensing

To evaluate the timeliness and freshness of information from energy-constrained devices, we minimize the weighted average age of information (AoI) of the ambient backscatter-assisted energy harvesting cognitive radio network (AB-EH-CRN), where secondary transmitters (STs) follow the non-orthogonal multiple access (NOMA) strategy to transmit status updates. The secondary receiver (SR) schedules the selected actions for STs to perform spectrum access, and receives status updates from them. We formulate the AoI minimization problem where the action selection and transmission power of STs are considered as variables. To exploit spectrum resources in the AB-EH-CRN with unknown signal-to-noise ratios (SNRs) at the STs, we propose the deep neural network (DNN)-based cooperative spectrum sensing (CSS), and adopt an energy threshold approach for STs to determine the energy allocation between spectrum sensing (SS) and packet transmission. Moreover, we address the AoI minimization problem by the proposed hybrid action and energy penalty deep deterministic policy gradient (HAEP-DDPG) algorithm, which adapts to the hybrid continuous and discrete action spaces. Simulation results validate the advantage of the proposed HAEP-DDPG algorithm compared with comparison schemes in terms of AoI.

Performance analysis of transmit antenna selection and maximum‐ratio combining in overlay networks powered by harvested energy

AbstractWe aim to improve both the energy harvesting efficiency and communication reliability of overlay networks powered by harvested energy. To this end, multiple antennas are considered to collect energy efficiently and perform reliable decoding by selecting the transmitting antenna and applying maximum‐ratio combining. To further improve communication reliability, nonorthogonal multiple access (NOMA)‐relied decoding is applied to the secondary receiver. For performance evaluation, exact formulas for the secondary/primary outage probability are derived in a closed form. The evaluation results show that the proposed method substantially outperforms a baseline without the NOMA‐relied decoding in all the system settings. The performance of the proposed method is determined by multiple specifications and optimized by allocating the times for energy harvesting and information processing.

On the performance of outage probability in cognitive NOMA random networks with hardware impairments

ABSTRACT The performance of the cognitive non-orthogonal multiple access (NOMA) systems with random locations is examined in the present paper. More precisely, the positions of the secondary receivers (SRs) are randomly distributed inside a disk with the centre at the secondary transmitter (ST). The primary networks (PNs), on the other hand, are not necessarily inside the transmission range of the ST. Two user selection schemes namely, path-loss-based and channel-gain-based approaches, are adopted to serve two SRs according to the power domain NOMA technique. Additionally, the impact of the imperfect hardware impairments (HIs) on both transmitters and receivers is also taken into consideration. Furthermore, a recently proposed transmit power allocation at the ST is employed to concurrently maximize the system performance of the secondary networks (SNs) and to strictly protect the quality-of-service (QoS) of the PNs. The correctness of the developed mathematical frameworks is corroborated by simulation results based on the Monte Carlo method. Finally, we unveil that there is no scheme that always outperforms another. Thus, an adaptive scheme can be proposed to optimize the networks' performance. Our findings also reveal that the outage probability (OP) under the harmful effect of HI can be effectively mitigated by increasing the transmit power of the ST. Additionally, increasing the transmit power of the PT is also beneficial for the SNs with the adopted transmit power allocation at the ST.

A Game-Theoretic Approach to Achieve Covert Communication in Cognitive Radio Systems

In this paper, we investigate a covert cooperative cognitive radio (CCCR) system, where multiple primary transmitters (PTs) transmit information with the aid of multiple secondary transmitters (STs) in order to conserve power consumption. In return, by opportunistically accessing PT's spectrum, STs send confidential information to a secondary receiver (SR) in the presence of external eavesdropper (Eve). Aiming to maximize covert rate, we model our CCCR framework as an evolutionary game in which each PT and ST make decisions based on their utility histories. By introducing the evolutionary game, we propose a game-oriented secondary user scheduling (G-SUS) scheme to find when multiple STs determine to access PTs' spectrum. Moreover, we analyze covert performance of the proposed scheme and obtain a closed-form expression for Eve's detection error probability. Numerical results show that, the minimal detection error probability at Eve can be effectively impacted by creating channel uncertainty and noise uncertainty. Furthermore, the results also demonstrate the proposed scheme can converge quickly, which stimulates its practical implementation.

Deep learning based relay selection and precoders design for IoT cognitive relay networks

This paper focuses on designing a multiple-input multiple-output (MIMO) Internet-of-Things (IoT) oriented cognitive multi relay network (CMRN), where the secondary system (SS) consists of IoT nodes. Randomly placed multiple IoT nodes help in data transmission between two IoT users, i.e., a secondary transmitter (ST) and a secondary receiver (SR). Specifically, the problem of designing energy-efficient precoders at ST and SR is considered. The problem is addressed in two steps, first, a closed-form solution for the precoders is derived. Secondly, optimal precoders weight are used to select the best relay that assists the transmission between ST and SR nodes, ensuring maximum end-to-end energy efficiency (E2E-EE) at the SS. However, as the number of relays increases, the computational complexity of the solution also increases. Therefore, achieving a balance between the number of relays and computational feasibility is essential for optimal performance. To ensure fast communication system, deep learning (DL) based framework is employed for precoder design and relay selection, which offers solution with high precision and fast execution time. This approach effectively minimizes power consumption in the IoT nodes while maintaining the Quality of Service (QoS) of the primary and secondary systems. Numerical results demonstrate the impact of relay selection and precoder design on the achievable E2E-EE at SS. The DL scheme achieves comparable performance and much lower complexity than the conventional method while demonstrating lower runtime, particularly when the number of relays is large.

Physical Layer Security Performance Analysis of IRS-Aided Cognitive Radio Networks

Cognitive radio (CR) acts as a significant player in enhancing the spectral efficiency (SE) of wireless telecommunications; simultaneously, the intelligent reflecting surface (IRS) technique is a valid technique for increasing the confidentiality properties of wireless telecommunications systems through the modulation of the amplitude and phase shift of the channel. Therefore, we take into consideration an IRS-assisted multiple-input single-output (MISO) CR system to raise the confidentiality rate, which is composed of a primary network with a primary receiver (PR) and an eavesdropping link, as well as a secondary network with a secondary receiver (SR) and SR transmitter (SR-TX). In particular, we minimize the SR’s transmit power under the interference temperature (IT) and confidentiality capacity constraints via the joint optimization of the beamforming vector and artificial noise (AN) constraint matrix at SR-TX together with the phase shift matrix of IRS. Numerical outcomes indicate that various transmit antenna values and the IRS element numbers at SR-TX can greatly reduce transmit power while assuring secure communication.

Performance Analysis of NOMA-Based Spectrum Sharing System With Imperfect SIC

This paper presents a non-orthogonal multiple access (NOMA)-based spectrum sharing scheme with imperfect successive interference cancellation (i-SIC), where the secondary user assists the primary to achieve cooperative multiplexing. The proposed scheme allows primary and secondary transmitters to transmit in alternate time slots and, hence, no primary transmitter's (PT) interference at the secondary receiver (SR). However, since the relay node and secondary transmitter (ST) are transmitting simultaneously on the same frequency spectrum, ST causes interference to the primary user. Therefore, the proposed scheme imposes the variable interference threshold constraint (v-ITC) to ST transmit power to improve the performance of both primary and secondary networks. We derive the closed-form expressions for the outage probability and ergodic rate of the proposed system. Furthermore, numerical results are presented to manifest the advantages of the v-ITC scheme on outage performance and the ergodic rate of the secondary network (SN).

Performance Analysis of Full-Duplex Multirelaying Energy Harvesting Scheme in Presence of Multiuser Cognitive Radio Network

This paper investigates the outage performance of secondary receiver with an energy harvesting cognitive radio network employing multiple full-duplex (FD) relaying protocol in presence of multi-user spectrum sharing environment. Under this energy harvesting aided FD relaying network scenario, adaptive transmit power policies for the secondary user (SU) source, secondary FD relays and exact outage probability of the secondary user are derived analytically in presence of multiple primary users and multiple secondary destinations. Impact of self interference at the receive antenna of each FD relay in addition to all the transmitting interference at all receive nodes is being addressed. A comparative study considering all the interference together in an FD relaying protocol with that of conventional half-duplex (HD) relaying protocol is carried out. With the same diversity order, a trade-off between FD multi-relay and multi-destination is shown. Closed form expressions of secondary outage probability for FD energy harvested relay equipped CR network has also been evaluated. Maintaining quality of service (QoS) of multiple primary users (PUs), power allocation strategies at each secondary transmitting node is taken care of. Finally, all the analytical closed form expressions have been validated through Monte-Carlo simulations.

Outage Probability Minimization in Secure NOMA Cognitive Radio Systems With UAV Relay: A Machine Learning Approach

This paper considers a multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) cognitive radio (CR) system with an unmanned aerial vehicle relay (UR). In this system, a secondary transmitter (ST) uses licensed spectrum from the primary network to transmit signals to its secondary receivers (SRs) based on NOMA. The UR is used as a relay to forward the signals from the ST to the SRs. As a result, the system can achieve significant improvements in spectral efficiency and network capacity. However, such a MIMO NOMA CR system faces issues of interference and security, i.e., eavesdropping attacks, due to the shared spectrum use and the UR. Therefore, we aim to minimize the outage probability of the secondary network, subject to constraints on the outage probability of the primary network and the intercept probabilities of eavesdroppers. Then, we attempt to optimize the transmit power of the UR, the coordinates of the UR, and the power allocation factors for NOMA. We further derive closed-form expressions for the outage probabilities of the secondary and primary networks and the intercept probabilities at the eavesdroppers. We propose using a machine learning algorithm based on a constrained continuous genetic algorithm to solve the optimization problem.

Robust Beamformer Design in Active RIS-Assisted Multiuser MIMO Cognitive Radio Networks

In this work, we address the problem of a joint robust transmission, reflection and reception strategy design at an active reconfigurable intelligent surface (RIS)-assisted underlay multiple input multiple output (MIMO) cognitive radio networks in which a secondary transmitter serves multiple secondary receivers simultaneously. As such, we study the impact of imperfection in channel state information (CSI) at the secondary transmitter following a norm-bounded error model. A sum mean squared error (MSE) minimization problem is formulated by jointly optimizing the transmit beamforming matrix (BFM) at the secondary transmitter, the linear reception filters (LRF) at the secondary receivers and the reflection coefficient matrix (RCM) at the RIS subject to the constraints of available transmission power at the secondary transmitter, maximum allowed interference power towards the primary receiver and the permissible amplification range at each RIS element. Due to the coupled nature of the BFM, LRF and RCM variables, the formulated problem is non-convex and, thus, cannot be solved using conventional optimization methods. As a result, we propose an alternating optimization (AO) based iterative algorithm that determines the optimal BFM, LRF and RCM using semidefinite programming and inner approximation methods with guaranteed convergence. We also discuss the impact of the limited power budget at active RIS on the performance of the considered network. We present simulation-based numerical results to validate the efficacy and robustness of the proposed algorithm. Moreover, we also highlight the superiority of the use of the active RIS over passive RIS in the considered communication network.

On Effective Secrecy Throughput of Underlay Spectrum Sharing $\alpha -\mu$/ Málaga Hybrid Model Under Interference-and-Transmit Power Constraints

The underlay cognitive radio-based hybrid radio frequency/free-space optical (RF/FSO) systems have emerged as a promising technology due to their ability to eliminate spectrum scarcity and spectrum under-utilization problems. The physical layer security of such a network with a primary user, a secondary source, a secondary receiver, and an eavesdropper is therefore examined in this work. In this network, secret communication occurs between two reliable secondary peers over the RF and FSO links simultaneously, and the eavesdropper can only overhear the RF link. In particular, the maximum transmits power limitation at the secondary user as well as the permissible interference power restriction at the primary user are also taken into consideration. All the RF and FSO links are modeled with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha$</tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> fading and Málaga turbulence with link blockage and pointing error impairments. At the receiver, the selection combining diversity technique is utilized to select the signal with the best electrical signal-to-ratio (SNR). Furthermore, to examine the secrecy performance taking into account the effects of each system parameter, closed-form expressions for the secrecy outage probability and effective secrecy throughput are derived. The resultant expressions are finally verified by Monte-Carlo simulations.

User Scheduling Design for Covert Communication in Cooperative Cognitive Radio System

In this article, we investigate the covert communication for a cooperative cognitive radio (CCR) system, where the secondary transmitters (STs) help the primary transmitter (PT) to transmit information while covertly transmitting their own information to the secondary receiver (SR) against the warden of PT. In particular, the different ST scheduling schemes are proposed for covert communications, namely, covert rate maximization (CRM), best channel gain (BCG), and fairness oriented (FO). The closed-form expression is derived for the expected detection error probability at the warden PT. Based on that, we, respectively, analyze the covert rate and covert outage probability (COP) of the proposed ST scheduling schemes. The simulation results show that, under the both effects of channel uncertainty and noise uncertainty, the CRM scheme achieves the best covert rate performance, and the BCG and FO schemes ensure the quality of service (QoS) and the STs’ fairness as the cost of covert performance degraded.

Secrecy Rate Maximization for Multicarrier-Based Cognitive Radio Networks With an Energy Harvesting Jammer

Cognitive radio (CR) is becoming an increasingly significant component of Internet-of-Things technologies because it overcomes the challenge of spectrum resource scarcity for wireless communications. For the cooperative CR network (CRN) based on the multicarrier system, this article investigates the physical layer security (PLS) to guarantee information privacy for the secondary network while guaranteeing the quality of service (QoS) of the primary network. First, we propose one communication scheme for this type of CRN. The secondary transmitter (ST) and secondary jammer (SJ) first harvest RF energy from the primary signal transmitted by the primary transmitter (PT). Then, ST transmits confidential information with the spectrum vacated by the primary network to the secondary receiver (SR), and SJ simultaneously generates the jamming signal to interfere with the eavesdropper (ED). Second, for the scenarios with the instantaneous channel state information (CSI) and the statistical CSI of the ED, respectively, we aim to maximize the secrecy rate of the secondary network while guaranteeing the QoS requirement of the primary network by jointly optimizing the time allocation between the two phases and the transmit power allocation for ST and SJ over subcarriers. For each scenario, the secrecy rate maximization is formulated as the nonconvex optimization problem. Finally, we design efficient algorithms for both two nonconvex problems. The optimal time allocation is obtained by the 1-D search method at the outer layer, and the optimal transmit power allocation is obtained by the difference of concave (DC) programming at the inner layer, where the Lagrange duality method is used to solve the convex approximation problem. Simulation results verify that the proposed scheme essentially improves the secrecy rate of the secondary network compared to benchmark schemes.

RIS-Enabled UAV Cognitive Radio Networks: Trajectory Design and Resource Allocation

Due to its flexible deployment and high mobility of unmanned aerial vehicles (UAVs), the UAV-assisted cognitive radio (CR) network has attracted a lot of attention as one of the most promising techniques to address spectrum congestion issues in futuristic networks. However, its performance can be severely affected by the blocked line-of-sight (LoS) channel in its air-to-ground (A2G) links. In this paper, we propose a UAV CR system enabled by a reconfigurable intelligent surface (RIS), which helps to reconstruct reliable links in UAV-assisted cognitive radio (CR) networks. Our goal is to maximize the achievable rate of a secondary receiver (SR) through the proper selection of the UAV trajectory, transmit power, and RIS phase shifts based on a given interference temperature threshold and other practical constraints. In addition, we solve the corresponding non-convex optimization problem using block coordinate descent (BCD) and successive convex approximation (SCA) algorithms. The simulation results will demonstrate the effectiveness of the proposed algorithms.

Research on Communication Technology of OPGW Line in Distribution Network under Interference Environment

In optical fiber composite overhead ground wire (OPGW) networks, the current monitoring is mainly through installing electronic sensors on the cable and manually monitoring the video on the cable, where the interference plays an important role in the communication and monitoring based systems. In essence, the interference arises from aggressive frequency reuse, especially in the frequency-limited Internet of Things (IoT) networks. The existence of interference causes a negative effect on the system performance of communication systems and IoT networks including the OPGW networks. Hence, this article investigates the communication technology of OPGW line in distribution network under interference environment, where there is one primary link, one secondary link, and one legitimate monitor listening to the secondary link. The secondary user needs to transmit its message to the secondary receiver under the interference power constrained by the primary node. We firstly define the outage probability of legitimate monitoring based on the data rate, and then analyze the system performance by theoretically deriving a closed-form expression of the outage probability for the OPGW communication under interference environment. Simulation results are finally demonstrated to verify the correctness of the closed-form expression for the OPGW communication under interference environment, and show that the interference has a negative impact on the OPGW communication performance.

Secondary Network Throughput Optimization of NOMA Cognitive Radio Networks Under Power and Secure Constraints

Recently, the combination of cognitive radio networks with the nonorthogonal multiple access (NOMA) approach has emerged as a viable option for not only improving spectrum usage but also supporting large numbers of wireless communication connections. However, cognitive NOMA networks are unstable and vulnerable because multiple devices operate on the same frequency band. To overcome this drawback, many techniques have been proposed, such as optimal power allocation and interference cancellation. In this paper, we consider an approach by which the secondary transmitter (STx) is able to find the best licensed channel to send its confidential message to the secondary receivers (SRxs) by using the NOMA technique. To combat eavesdroppers and achieve reasonable performance, a power allocation policy that satisfies both the outage probability (OP) constraint of primary users and the security constraint of secondary users is optimized. The closed-form formulas for the OP at the primary base station and the leakage probability for the eavesdropper are obtained with imperfect channel state information. Furthermore, the throughput of the secondary network is analyzed to evaluate the system performance. Based on that, two algorithms (i.e., the continuous genetic algorithm (CGA) for CR NOMA (CGA-CRN) and particle swarm optimization (PSO) for CR NOMA (PSO-CRN)), are applied to optimize the throughput of the secondary network. These optimization algorithms guarantee not only the performance of the primary users but also the security constraints of the secondary users. Finally, simulations are presented to validate our research results and provide insights into how various factors affect system performance.

Achievable Rate of NOMA-Based Cooperative Spectrum-Sharing CRN over Nakagami-m Channels

Efficient data dissemination is a key challenge for IoT applications. In this paper, we present an ergodic achievable rate analysis of the non-orthogonal multiple access (NOMA)-based cooperative transmission scheme in spectrum-sharing cognitive radio networks (CRNs). The transmission scheme consists of two phases, where the NOMA transmission strategy is employed at the secondary transmitter (ST) in the second phase to serve the primary receiver (PR) and secondary receivers (SRs). This cooperative spectrum-sharing transmission is favourable when the ST-PR link is strong and the ST faces a spectrum scarcity issue. To evaluate the performance of the network over Nakagami-m channels, ergodic achievable rates at PR and SRs are derived in closed forms, which can be used for any integer or non-integer value of fading index m. Finally, we compare the results of the analytical expressions with simulated results for validation.

Broadcasting in Cognitive Radio Networks: A Fountain Codes Approach

The present paper addresses the performance of the broadcasting scheme in cognitive radio networks (CRNs) under a fountain codes (FC) approach. Particularly, closed-form expressions are derived for the cumulative distribution function (CDF) and the expectation of the number of FC clock cycles required for broadcasting packets to all secondary receivers. The energy efficiency (EE) of the secondary networks (SN) is also provided. Moreover, a simple transmit power scheme is proposed to enhance the performance of the SN and guarantee the quality-of-service (QoS) of the primary network (PN). The trends of the introduced closed-form performance metrics are then examined versus important network parameters allowing for the optimization of those parameters. Finally, numerical results are provided to confirm the accuracy of the derived mathematical framework and the superior performance of the introduced FC scheme over uncoded broadcasting protocols.