Multiple Secondary Transmitters Research Articles

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.

Throughput Fairness for Wireless Powered Cognitive Hybrid Active-Passive Communications

In this paper, we consider a backscatter communication (BackCom)-based cognitive network that consists of one primary transmitter, one primary receiver, multiple secondary transmitters (STs), and one secondary receiver (SR). Each ST operates in the BackCom or energy harvesting model. Our goal is to jointly optimize the energy harvesting and backscatter time, the transmit power of the primary transmitter, and the power reflection coefficient of each ST to maximize the sum throughput of all the STs under a nonlinear energy harvesting model while satisfying multiple constraints, i.e., the energy causality of each ST, the quality of service of the primary transmitter, etc. The formulated problem is nonconvex due to the coupled variables and is hard to solve. In order to address this problem, we decouple partially coupled variables by using the properties of the objective function and constructing auxiliary variables, and the remaining coupled variables are decoupled via successive convex approximation (SCA). On this basis, a SCA-based iterative algorithm is developed to solve the formulated problem. Simulation results are provided to support our work.

Sum-Throughput Maximization in Backscatter Communication-Based Cognitive Networks

In this paper, we consider a backscatter communication (BackCom) based cognitive network that consists of one primary transmitter, one primary receiver, multiple secondary transmitters (STs), and one secondary receiver (SR). Each ST operates in the BackCom or energy harvesting model. Our goal is to jointly optimize the energy harvesting and backscatter time, the transmit power of the primary transmitter, and the power reflection coefficient of each ST to maximize the sum throughput of all the STs under a nonlinear energy harvesting model while satisfying multiple constraints, i.e., the energy causality of each ST, the Quality of Service of the primary transmitter, etc. The formulated problem is nonconvex due to the coupled variables and hard to solve. In order to address this problem, we decouple partial coupled variables by using the properties of the objective function and constructing auxiliary variables, and the remaining coupled variables are decoupled via successive convex approximation (SCA). On this basis, a SCA based iterative algorithm is developed to solve the formulated problem. Simulation results are provided to support our work.

Performance analysis of Cognitive Vehicular Networks under Unreliable Backhaul

This paper presents a comprehensive model including a wireless backhaul as a cost-effective backhaul alternative to wired backhaul for vehicular networks, a heterogeneous underlay cognitive vehicular network with multiple mobile secondary transmitters acting as mobile small cells, a mob

Bargaining Game Based Time Scheduling Scheme for Ambient Backscatter Communications

Backscatter communications have been acknowledged as an essential key technology in the Internet of Things (IoT) applications. Considering the fact that it needs the coordination from network agents, cooperative bargaining theory is an effective method to strike an appropriate system performance. In this paper, we investigate time scheduling algorithms for a backscatter-aided radio-frequency (RF) powered cognitive radio (CR) network, where multiple secondary transmitters can switch among the backscatter, the energy harvest, and active data transmission modes. Our objective is to maximize the RF-CR system performance while exploring the mutual benefits to leverage a reciprocal consensus between different control issues. According to the ideas of two different bargaining solutions - modified Nash bargaining solution and equitable Nash bargaining solution, we design a new dual bargaining game model to effectively share the limited time resources. The main novelty of our proposed approach is its adaptability, flexibility and responsiveness to current RF-CR system conditions. At last, numerical simulations are carried out to evaluate the performance of the proposed scheme, and we demonstrate the benefits of our dual bargaining game approach.

Achieving Covert Communication in Overlay Cognitive Radio Networks

In this paper, we investigate the covert communications in an overlay cognitive radio (CR) network, where multiple secondary transmitters (STs) opportunistically send confidential information to a secondary receiver (SR). In contrast to current studies with ensuring security of information transmitted, we are motivated to protect communication behavior in CR network, which is considered as a higher-level security. To address covert rate and fairness performance, three joint user-jammer scheduling schemes are proposed, namely, rate-oriented secondary user scheduling (R-SUS), link-oriented secondary user scheduling (L-SUS), and fairness oriented secondary user scheduling (F-SUS). Numerical results show that the minimal detection error probability at eavesdropper (Eve) can be effectively impacted by creating channel uncertainty with the jamming signal. Further, it can be seen that under the same covert constraint, the R-SUS scheme achieves the best covert rate performance, full diversity can be obtained by the L-SUS scheme, while the F-SUS scheme exploits an advantage of better fairness.

Auction-Based Time Scheduling for Backscatter-Aided RF-Powered Cognitive Radio Networks

This paper investigates the time scheduling for a backscatter-aided radio-frequency-powered cognitive radio network, where multiple secondary transmitters transmit data to the same secondary gateway in the backscatter mode and the harvest-then-transmit mode. With many secondary transmitters connected to the network, the total transmission demand of the secondary transmitters may frequently exceed the transmission capacity of the secondary network. As such, the secondary gateway is more likely to assign the time resource, i.e., the backscattering time in the backscatter mode and the transmission time in the harvest-then-transmit mode, to the secondary transmitters with higher transmission valuations. Therefore, according to a variety of demand requirements from secondary transmitters, we design two auction-based time scheduling mechanisms for the time resource assignment. In the auctions, the secondary gateway acts as the seller as well as the auctioneer, and the secondary transmitters act as the buyers to bid for the time resource. We design the winner determination, the time scheduling, and the pricing schemes for both the proposed auction-based mechanisms. Furthermore, the economic properties, such as individual rationality and truthfulness, and the computational efficiency of our proposed mechanisms are analytically evaluated. The simulation results demonstrate the effectiveness of our proposed mechanisms.

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.

Cognitive Heterogeneous Networks With Multiple Primary Users and Unreliable Backhaul Connections

Wireless backhaul has emerged as a suitable and flexible alternative to wired backhaul; however, it is not as reliable as its wired counterpart. This paper presents, for the first time, a comprehensive model including a heterogeneous underlay cognitive network with small cells also acting as multiple secondary users, multiple primary users, and unreliable wireless backhaul. In this system, a macro-base station connects to multiple secondary transmitters via wireless backhaul links. In addition, multiple secondary transmitters send information to a secondary receiver by sharing the same spectrum with multiple primary users. A Bernoulli process is adopted to model the backhaul reliability. A selection combining protocol is used at the secondary receiver side to maximize the received signal-to-noise ratio. We investigate the impact of the number of secondary transmitters, the number of primary users, as well as the backhaul reliability on the system performance in Rayleigh fading channels. Two key constraints are considered on the system performance: 1) maximum transmit power at the secondary transmitters and 2) peak interference power at the primary users caused by secondary transmitters. Closed-form expressions for outage probability, ergodic capacity, and symbol error rate and the asymptotic expressions for outage probability and symbol error rate are derived. Moreover, closed-form expressions are also applicable to non-cooperative scenarios.

Relay Cooperation and Outage Analysis in Cognitive Radio Networks With Energy Harvesting

Cooperative cognitive radio (CCR) is a novel paradigm to improve both radio spectrum efficiency and communication quality. In this paper, we consider a CCR network (CCRN) with energy harvesting in which multiple secondary transmitters (STs) are able to harvest energy from the received signals to serve their own receivers and primary transmitters (PTs). Besides, not only PT's transmitting signal but also interferers, i.e., RF signals in ambient environment received at STs can be used for energy harvesting. Moreover, we aim to analyze the outage probability (OP) for two relay cooperation schemes including single-relay cooperation (SC) and multirelay cooperation (MC) in CCRNs while considering energy harvesting. In addition, we consider Nakagami- $m$ fading rather than Rayleigh fading channels as it is more practical and general for characterizing the fading effect over wireless channels. Most importantly, we compare the outage performance of SC and MC with that of direct transmission and investigate the tradeoff between the primary and secondary users’ performance. Simulation results are presented to validate our analysis, which show the exact performance for different parameter settings.

Decentralized SINR Balancing in Cognitive Radio Networks

This paper considers the downlink of a cognitive radio (CR) network formed by multiple primary and secondary transmitters, where each multiantenna transmitter serves a preknown set of single-antenna users. This paper assumes that the secondary and primary transmitters can simultaneously transmit their data over the same frequency bands to achieve high system spectrum efficiency. This paper considers the downlink balancing problem of maximizing the minimum signal-to-interference-plus-noise ratio (SINR) of the secondary transmitters subject to both the total power constraint of the secondary transmitters and the maximum interference constraint at each primary user due to secondary transmissions. This paper proposes solving the problem using the alternating direction method of multipliers, which leads to a distributed implementation through limited information exchange across the coupled secondary transmitters. This paper additionally proposes a solution that guarantees feasibility at each iteration. Simulation results demonstrate that the proposed solution converges to the centralized solution in a reasonable number of iterations.

Impact of primary networks on the performance of energy harvesting cognitive radio networks

In this paper, we investigate the effect of of the primary network on the secondary network when harvesting energy in cognitive radio in the presence of multiple power beacons and multiple secondary transmitters. In particular, the influence of the primary transmitter's transmit power on the energy harvesting secondary network is examined by studying two scenarios of primary transmitter's location, i.e., the primary transmitter's location is near to the secondary network and the primary transmitter's location is far from the secondary network. In the scenario where the primary transmitter locates near to the secondary network, although secondary transmitter can be benefit from the harvested energy from the primary transmitter, the interference caused by the primary transmitter suppresses the secondary network performance. Meanwhile, in both scenarios, despite the fact that the transmit power of the secondary transmitter can be improved by the support of powerful power beacons, the peak interference constraint at the primary receiver limits this advantage. In addition, the deployment of multiple power beacons and multiple secondary transmitters can improve the performance of the secondary network. The analytical expressions of the outage probability of the secondary network in the two scenarios are also provided and verified by numerical simulations.

Guest Editorial

Guest Editorial

Transmit Antenna Selection with Optimum Combining for Aggregate Interference in Cognitive Underlay Radio Network

Transmit antenna selection (TAS) is most popular technique in underlay cognitive radio (CR) networks as they increase the capacity of secondary users with less hardware requirements. In this paper, a new scenario of CR ad-hoc network topology is proposed in which apart from primary users, there are multiple number of secondary users which are assumed to be distributed as homogeneous spatial Poisson point process (PPP) and are trying to use the primary spectrum in underlay mode. These multiple secondary transmitters generate the aggregate interference and can degrade the performance of secondary receiver. Here this aggregate interference is estimated and its impact on performance of secondary receiver under unconstrained mode of operation is presented. Further, to enhance the performance of secondary receivers in this scenario, single TAS technique based on maximizing the received signal to interference noise ratio by using optimum combining (OC) method is proposed. Furthermore, in this work the design of end to end Simulink based environment for secondary trans---receiver system with advancements in channel design and estimation is proposed. The bit error rate (BER) analysis is presented and verified for image data for single TAS-OC technique for unconstrained mode in underlay CR network in Rician fading channel. The BER performance is also presented for different number of secondary interference sources which are located at fixed distance in one case and they are assumed to be distributed as PPP in another case.

Pricing-Based Multiresource Allocation in OFDMA Cognitive Radio Networks: An Energy Efficiency Perspective

Both the orthogonal frequency-division multiple access (OFDMA) and cognitive radio (CR) technologies offer great flexibility and feasibility for future green wireless communications. In this paper, an energy-efficient multiresource-allocation scheme is proposed for OFDMA CR networks (CRNs) with multiple secondary transmitters (STs). To maximize the energy efficiency (EE) and guarantee the primary transmitter's (PT's) quality-of-service (QoS) requirement, a linear pricing technique is employed to handle both the inter-ST coupling (the spectrum competition among STs) and intra-ST coupling (the correlation between the available transmit power and assigned subchannels for each ST). Furthermore, a distributed algorithm is devised to harvest the multiresource and multiuser gains, and the multiresource allocation is transformed to 1-D pricing-factor profile searching. Simulation results demonstrate that the proposed strategy brings higher EE. Additionally, by adjusting the pricing factors, a different performance can be achieved by the STs with different priorities.

A robust beamformer design for underlay cognitive radio networks using worst case optimization

We propose a robust beamforming design for underlay cognitive radio networks where multiple secondary transmitters communicate with corresponding secondary receivers and coexist with a primary network. We consider a scenario where all transmitters have multiple antennas and all primary and secondary receivers are equipped with a single antenna. The main focus is to design the optimal transmit beamforming vectors for secondary transmitters that maximize the minimum of the received signal-to-interference-plus-noise ratios of the cognitive users. The interference powers to the primary receivers are kept below a threshold to guarantee that the performance of the primary network does not degrade due to the secondary network. Imperfect channel state information (CSI) in all relevant channels are considered, and a bounded ellipsoidal uncertainty model is used to model the CSI errors. We recast the problem in the form of semidefinite program and an iterative algorithm based on the bisection method is proposed to achieve the optimal solution. Further, we propose upper and lower bounds for the optimal value of the considered problem, which provides better initialization for the algorithm. Numerical simulations are conducted to show the effectiveness of the proposed method against the non-robust design.

On the Multi-User Diversity with Fixed Power Transmission in Cognitive Radio Networks

In this letter, we investigate the multi-user diversity (MUD) in an underlay cognitive radio (CR) network where multiple secondary transmitters and primary receivers exist. Many studies on MUD in the underlay CR network have assumed that the secondary transmitters adaptively control their transmit power in order to achieve the {optimal} MUD gain, maintaining the interference at the primary receivers below a pre-determined level. We, however, prove the optimal MUD gain can be also achieved by the fixed power transmission strategy. In contrast to the adaptive power transmission strategy, the fixed power operation in the secondary transmitters relaxes the coordination constraint between the primary and secondary networks, and significantly reduces the signaling and feedback overhead from the secondary transmitters to the secondary receiver.

Adaptive Sensing Period Based Distributed Medium Access Control for Cognitive Radio Networks

In this paper, we propose distributed medium access control (MAC) protocols based on an adaptive sensing period adjustment scheme for low-cost multiple secondary users in interweave-type cognitive radio (CR) networks. The proposed MAC protocols adjust the sensing period of each secondary user based on both primary sensing and secondary data channels in distributed manner. Then, the secondary user with the shortest sensing period accesses the medium using request-to-send (RTS) and clear-to-send (CTS) message exchange. Three components affect the length of each user’s sensing period: sensing channel quality from the primary system, data channel quality to the secondary receiver, and collision probability among multiple secondary transmitters. We propose two sensing period adjustment (SPA) schemes to efficiently improve achievable rate considering the three components, which are logarithmic SPA (LSPA) and exponential SPA (ESPA). We evaluate the performance of the proposed schemes in terms of the achievable rate and other factors affecting it, such as collision probability, false alarm probability, and average sensing period.

Decentralized Beamformer Design with Limited Multi-Cell Cooperation for Interference Channel of Cognitive Radio Networks

In spectrum-sharing-based cognitive radio networks, multiple secondary systems can access a licensed spectrum to better utilize scarce radio resources. When the multiple secondary transmitters are co-located, the weighted sum-rate of the secondary users (SUs) is mainly limited by the inter-cell interference (ICI). With limited cooperation among co-located secondary transmitters, we propose an algorithm for decentralized beamforming with power allocation via dual decomposition. To maximize the weighted sum-rate of the SUs, the proposed decentralized algorithm efficiently mitigates the ICI by the undesired leakage power limitation at each secondary transmitter. Because the channel information is not perfectly known at the transmitter in practical applications, we also develop a decentralized robust beamformer. To efficiently design the robust beamformer, a convex problem is formulated by semi-definite relaxation. Simulation results show that the proposed algorithm with perfect channel state information (P-CSI) efficiently maximizes the weighted sum-rate performance by the undesired leakage power limitation. For an imperfect CSI with a small error bound, the proposed robust beamformer approaches the performance of a P-CSI case, without causing harmful interference to the primary user.

Proportional Fair Power Allocation for Secondary Transmitters in the TV White Space

The key bottleneck for secondary spectrum usage is the aggregate interference to the primary system receivers due to simultaneous secondary transmissions. Existing power allocation algorithms for multiple secondary transmitters in the TV white space either fail to protect the TV service in all cases or they allocate extremely low power levels to some of the transmitters. In this paper, we propose a power allocation algorithm that favors equally the secondary transmitters and it is able to protect the TV service in all cases. When the number of secondary transmitters is high, the computational complexity of the proposed algorithm becomes high too. We show how the algorithm could be modified to reduce its computational complexity at the cost of negligible performance loss. The modified algorithm could permit a spectrum allocation database to allocate near optimal transmit power levels to tens of thousands of secondary transmitters in real time. In addition, we describe how the modified algorithm could be applied to allow decentralized power allocation for mobile secondary transmitters. In that case, the proposed algorithm outperforms the existing algorithms because it allows reducing the communication signalling overhead between mobile secondary transmitters and the spectrum allocation database.