Wireless-powered Cognitive Radio Networks Research Articles

Wireless Powered Cognitive Radio Networks with Multiple Antenna Sources and Hardware Impairments

Wireless Powered Cognitive Radio Networks with Multiple Antenna Sources and Hardware Impairments

Security-aware spectrum sharing for NOMA in cognitive radio networks with discrete-time energy harvesting

In this paper, we propose a security-aware spectrum sharing scheme for wireless-powered cognitive radio networks (CRNs) with non-orthogonal multiple access (NOMA). In this system, a primary transmitter (PT) intends to send confidential signal to a primary receiver (PR) by assisting of a secondary transmitter (ST), while there is a potential eavesdropper (PE) within the scope of PR. It is assume that ST has no fixed energy supply but the NOMA cognitive transmission can be performed after harvesting sufficient radio frequency (RF) energy. To ensure that PT’s confidential signal is safety, PR will be equipped with two antennas and operating in full-duplex mode, so that while ST is performing cognitive transmission, one of the antennas sends artificial noise (AN) from PR to interfere the signal receiving of PE. According to whether the accumulated energy of ST is sufficient and whether ST can correctly decode the PT’s signal, the system can operate in three modes. Since ST needs to accumulate enough energy through several continuous transmission slots, the charging and discharging processes of the battery in the ST can be simulated as a discrete-time Markov chain. Based on these, we derive exact expressions of outage probabilities of the primary and secondary systems, then an approximate formula of secrecy outage probability (SOP) of primary system is also derived. In addition, in order to further improve the transmission performance of the system, optimal power allocation factor and power level of AN are obtained by maximizing the secrecy rate of the primary system, while guaranteeing the system energy efficiency. Compared with zero-forcing (ZF) technique, the proposed secure spectrum sharing scheme has a slight disadvantage in secrecy energy efficiency, but it is simple to deploy, low cost, and achieves a better secrecy rate, which can be applied for a variety of application scenarios.

Energy-Efficient Secure Communications for Wireless-Powered Cognitive Radio Networks.

In this study, we investigate energy-efficient secure communications for wireless-powered cognitive ratio networks, in which multiple secondary users (SUs) share the same frequency band with primary users (PUs) and energy harvesting (EH) nodes harvest energy from the transmitted signals, even though information decoding is not permitted. To maximize the average secrecy energy efficiency (SEE) of SUs while ensuring acceptable interference on PUs and the required amount of energy for the EH nodes, we propose an energy-efficient transmit power control algorithm using dual decomposition, wherein suboptimal transmit powers are determined in an iterative manner with low complexity. Through extensive simulations in various scenarios, we verify that the proposed scheme has a higher average SEE than conventional schemes and a considerably shorter computation time than the optimal scheme.

Low-Complexity Transmit Power Control for Secure Communications in Wireless-Powered Cognitive Radio Networks.

In this study, wireless-powered cognitive radio networks (WPCRNs) are considered, in which N sets of transmitters, receivers and energy-harvesting (EH) nodes in secondary networks share the same spectrum with primary users (PUs) and none of the EH nodes is allowed to decode information but can harvest energy from the signals. Given that the EH nodes are untrusted nodes from the point of view of information transfer, the eavesdropping of secret information can occur if they decide to eavesdrop on information instead of harvesting energy from the signals transmitted by secondary users (SUs). For secure communications in WPCRNs, we aim to find the optimal transmit powers of SUs that maximize the average secrecy rate of SUs while maintaining the interference to PUs below an allowable level, while guaranteeing the minimum EH requirement for each EH node. First, we derive an analytical expression for the transmit power via dual decomposition and propose a suboptimal transmit power control algorithm, which is implemented in an iterative manner with low complexity. The simulation results confirm that the proposed scheme outperforms the conventional distributed schemes by more than 10% in terms of the average secrecy rate and outage probability and can also considerably reduce the computation time compared with the optimal scheme.

Outage Performance Analysis of NOMA in Wireless Powered Cognitive Radio Networks with AF and DF Relaying Techniques.

Improving spectral efficiency under a certain energy limitation is an important design metric for future wireless communications as a response to the growing transmission demand of wireless devices. In order to improve spectral efficiency for communication systems without increasing energy consumption, this paper considers a non-orthogonal multiple access (NOMA)–based cognitive radio network, with the assistance of a wireless-powered relay station (RS), and then analyzes the system outage performance under amplified-and-forward (AF) and decoded-and-forward (DF) cooperative transmission modes. Specifically, the base station (BS) has the opportunity to cooperate by transmitting information through the RS, depending on whether the RS can harvest sufficient RF energy for cooperative transmission. That is to say, when the energy stored by the RS is sufficient for cooperative transmission, the RS will assist the BS to forward information; otherwise, the BS will send information through direct links, while the RS converts the radio frequency (RF) signals sent by the BS into energy for future transmission. Moreover, the transmission power required by the RS for cooperative transmission is usually relatively large, while the amount of harvested energy by the RS in a transmission slot is usually low, so it takes several consecutive time slots to accumulate enough transmission energy. To this end, we utilize a discrete-time Markov chain to describe the processes of charging and discharging of the RS. Subsequently, we derive the closed-form outage probabilities of both the primary and secondary systems for the considered system in AF and DF modes through mathematical analysis, and verify the accuracy of the analyses through Monte Carlo simulation. The simulation results show that the two proposed cooperative transmission schemes with AF and DF relaying techniques outperform both direct transmission and other similar schemes in both the primary and secondary system, while the DF scheme can provide better performance than the AF scheme within the range of setting values.

Secure Information Transmissions in Wireless-Powered Cognitive Radio Networks for Internet of Medical Things

In this paper, we consider the issue of the secure transmissions for the cognitive radio-based Internet of Medical Things (IoMT) with wireless energy harvesting. In these systems, a primary transmitter (PT) will transmit its sensitive medical information to a primary receiver (PR) by a multi-antenna-based secondary transmitter (ST), where we consider that a potential eavesdropper may listen to the PT’s sensitive information. Meanwhile, the ST also transmits its own information concurrently by utilizing spectrum sharing. We aim to propose a novel scheme for jointly designing the optimal parameters, i.e., energy harvesting (EH) time ratio and secure beamforming vectors, for maximizing the primary secrecy transmission rate while guaranteeing secondary transmission requirement. For solving the nonconvex optimization problem, we transfer the problem into convex optimization form by adopting the semidefinite relaxation (SDR) method and Charnes–Cooper transformation technique. Then, the optimal secure beamforming vectors and energy harvesting duration can be obtained easily by utilizing the CVX tools. According to the simulation results of secrecy transmission rate, i.e., secrecy capacity, we can observe that the proposed protocol for the considered system model can effectively promote the primary secrecy transmission rate when compared with traditional zero-forcing (ZF) scheme, while ensuring the transmission rate of the secondary system.

Performance analysis of wireless-powered cognitive radio networks with ambient backscatter

Ambient backscatter is a promising wireless communication technique where low-power users communicate with each other without any dedicated power source. These communicating users transmit their information by reflecting ambient radio-frequency (RF) signals. In this paper, we propose an ambient backscatter communications-assisted wireless-powered underlay cognitive radio network (CRN). The proposed CRN consists of a single primary transmitter (PT) and multiple primary receivers (PRs), secondary transmitters (STs), and secondary receivers (SRs). For efficient utilization of radio resources, the STs in the proposed scheme dynamically adopt either harvest-then-transmit mode or backscatter mode. Furthermore, PRs cooperate with STs to select an appropriate mode for their communication with SRs. To evaluate the performance of our proposed scheme, we conduct system-level simulations. Numerical results show that the performance of the secondary system can be improved in terms of throughput with minimum effect on the communication of primary users.

Secure beamforming for cognitive cyber-physical systems based on cognitive radio with wireless energy harvesting

Cognitive cyber-physical systems (CPS) have been extensively applied in many fields from intellectual traffic control system to autonomous robot for face-detection and face-recognition. In wireless-powered cognitive radio networks (WP-CRN), it is necessary to provide secure and effective real-time feedback for CPS users. In this paper, we consider secure transmission issues in WP-CRN for CPS users, where a primary system works in conjunction with a wireless-powered secondary system in the presence of multiple potential eavesdroppers. Furthermore, a novel spectrum sharing scheme is proposed, which multiplexes the secondary transmissions during both the primary and cognitive transmissions. We aim to maximize the secondary data rate while guaranteeing the secure rate requirement of the primary system by jointly optimizing the energy harvesting duration and the beamforming vectors of the primary and secondary systems. In order to solve the non-convex optimization problem, the semi-definite relaxation (SDR) with Charnes–Cooper transformation is adopted to transfer the non-convex problem into convex optimization problem, which can be easily solved by CVX tools. Moreover, we can prove that the SDR is tight since there always exists a rank-one optimal solution. Simulation results illustrate that the proposed scheme can significantly improve the secondary transmission rate while can achieve higher security rates of the primary system compared with zero-forcing (ZF) beamforming scheme.

Traffic-Aware Optimal Spectral Access in Wireless Powered Cognitive Radio Networks

Traffic patterns associated with different primary users (PUs) might provide different spectral access and energy harvesting opportunities to secondary users (SUs) in wireless powered cognitive radio networks (WP-CRNs). Since the traffic applications have their own distinctive patterns, spectral access and energy harvesting opportunities are also expected to be distinctive. In this paper, we propose a novel approach to identify the PU traffic patterns and estimate the energy harvested from each traffic pattern so that SU can maximize its capacity accordingly. More specifically, we propose a theoretical framework based on a variational inference algorithm to cluster various traffic patterns and design a threshold-based SU transmission strategy by taking into account the spectral access and energy harvesting opportunities for each traffic pattern, so as to optimize SU transmission. Through simulations, we demonstrate the effectiveness of the proposed scheme in terms of throughput gains and show the transmission thresholds under various traffic applications (patterns). Further, we illustrate the effects of different collision costs on throughput for different traffic applications using real wireless traces.

Dynamic threshold-setting for RF-powered cognitive radio networks in non-Gaussian noise

The increasing demand for spectral and energy efficient communication networks has drawn an upsurge of interest in frequency (RF) energy harvesting (EH) cognitive radio networks (CRNs), and the spectrum analyzer is the brain to provide different spectral access and energy harvesting opportunities in wireless-powered cognitive radio networks (WP-CRNs). The performance of detecting the existence of primary signals will be more crucial for the EH node. However, to the best of our knowledge, no dynamic threshold-setting method to achieve target detection performance, particularly in the practical non-Gaussian noise, is reported in the literature. Traditional assumption of additive white Gaussian noise (AWGN) fails to model the behavior of certain types of noise found in practice.In this paper we give a dynamic threshold-setting method to detect the existence of primary signals for the energy harvesting node in non-Gaussian noise background. Combined with the fractional lower order statistics (FLOS), we propose a weighting factor for dynamic threshold-setting to exploit the existence of the PU to harvest RF energy, namely weighting factor based fractional lower order moment (WF-FLOM) detector. Numerical simulation results verify that the proposed method is effective for the EH node, when the signal-to-noise ratio is low or the back ground noise varies.

Energy-Arrival-Aware Detection Threshold in Wireless-Powered Cognitive Radio Networks

Traffic patterns associated with different primary user (PU) channels may provide different spectral access and energy harvesting opportunities in wireless-powered cognitive radio networks (WP-CRNs). Considering this, we propose traffic-specific optimal spectrum sensing policy such that the expected transmission rate of secondary user (SU) is maximized under the energy causality and PU collision constraints in orthogonal frequency-division multiple access (OFDMA)-based WP-CRN. Toward this, we cluster $N$ subcarriers (subchannels) into $K$ clusters (where $K \leq N$ ) and derive an optimal energy detection threshold for the SU under each traffic pattern. Using traffic features, we propose an unsupervised and nonparametric classification technique to determine the number of unique traffic patterns $K$ over all subchannels. Then, the traffic patterns are used to predict the idle/busy period statistics for subchannels, based upon which SU identifies harvest and transmit PU subchannels for energy harvesting and data transmission, respectively. We derive an optimal detection threshold based on the harvested energy such that it maximizes the expected transmission rate of SU while protecting PU from collision. We demonstrate the effectiveness of the proposed scheme in terms of rate gains under design constraints and show the optimal detection threshold under various energy arrival rates.

Wireless Powered Cognitive Radio Networks With Compressive Sensing and Matrix Completion

In this paper, we consider cognitive radio networks in which energy constrained secondary users (SUs) can harvest energy from the randomly deployed power beacons. A new frame structure is proposed for the considered networks. In the considered network, a wireless power transfer model is proposed, and the closed-form expressions for the power outage probability are derived. In addition, in order to reduce the energy consumption at SUs, sub-Nyquist sampling are performed at SUs. Subsequently, compressive sensing and matrix completion techniques are invoked to recover the original signals at the fusion center by utilizing the sparsity property of spectral signals. Throughput optimizations of the secondary networks are formulated into two linear constrained problems, which aim to maximize the throughput of a single SU and the whole cooperative network, respectively. Three methods are provided to obtain the maximal throughput of secondary networks by optimizing the time slots allocation and the transmit power. Simulation results show that the maximum throughput can be improved by implementing compressive spectrum sensing in the proposed frame structure design.

Resource Allocation in Wireless Powered Cognitive Radio Networks Based on a Practical Non-Linear Energy Harvesting Model

Wireless powered techniques have been recognized as promising techniques in future wireless communication systems, especially in cognitive radios (CRs) with energy-limit devices. However, most of the existing works focus on CRs with an ideal linear energy harvesting model. In this paper, a wireless powered wideband CR network is considered, and a practical non-linear energy harvesting model is adopted. To maximize the sum throughput of the secondary users, the energy harvesting time, channel allocation, and transmit power are jointly optimized. The closed-form expressions for the optimal transmit power and channel allocation are given. Simulation results show that there is a tradeoff between the harvesting energy and the sum throughput of the secondary users. It is also shown that the performance achieved under the non-linear energy harvesting model may equal to that achieved under the linear energy harvesting model.

Secure Beamforming in Wireless-Powered Cooperative Cognitive Radio Networks

In wireless-powered cognitive radio networks, secure information transmission is of paramount importance for the primary system. This letter considers cooperation between a primary system and a wireless-powered secondary system. In particular, we focus on secure information transmission for the primary system when the secondary users (SUs) are the potential eavesdroppers. We aim to jointly design power splitting and secure beamforming to maximize the secondary system data rate subject to the secrecy QoS requirement of the primary system and the secondary transmitter (ST) power constraint. To solve this nonconvex problem, we propose a two-stage optimization approach. Simulation results demonstrate that our proposed scheme achieves a significant transmission rate of the secondary system while provides a high secrecy rate for the primary system compared to the scheme without energy harvesting.