Xiaoye Shi

Performance analysis and power allocation for a two-way amplify-and-forward relay with channel estimation errors

This study deals with the performance analysis and power allocation of a two-way amplify-and-forward relay system with channel estimation errors. Exact closed-form expressions for outage probability and average symbol error rate (SER) are first presented. To provide more insights, their closed-form asymptotic expressions are then obtained. It is shown that the presence of channel estimation error causes outage probability and average SER maintain a fixed level even when a noiseless channel is adopted. These results are applied further to study the optimal power allocation problem for each node. From the perspective of service quality, rather than minimise the outage probability as much as possible, the goal is to use the minimum energy consumed to satisfy the traffic requirements and thereby conserve the energy resource. Furthermore, based on the optimal solutions to power allocation, the optimal relay location is investigated, which indicates that the system has higher energy efficiency with the relay located around the middle point of the two end nodes for any asymmetric traffic requirement. The simulation results verify that the derived outage probability and average SER expressions are accurate and highlight the effect of power allocation under various traffic requirements and channel estimation errors.

A Leakage-Based Precoding Scheme for Cognitive Multiuser MIMO Systems

In this paper, we develop linear precoding schemes for cognitive radio (CR) multiuser multiple-input multiple-output (MU-MIMO) downlink systems. A secondary user base station (SBS) with multiple secondary users (SUs) sharing the primary user (PU) spectrum is considered. In the proposed scheme, the block diagonalization (BD) algorithm is adopted to remove the co-channel interference from the SBS to the PU completely, and the matching weighted signal-to-leakage-and-noise ratio (SLNR) maximization algorithm is proposed to mitigate interference between SUs. The proposed scheme does not require a strict restriction on the number of transmit and receive antennas. Simulation results show that the proposed scheme can achieve high sum rate throughput with affordable complexity.

Power Allocation for Cognitive Two-Way AF Relay Networks with Asymmetric Traffic Requirements

In this paper, we study the power allocation for two-way amplify-and-forward relay networks with asymmetric traffic requirements in cognitive radio. The proposed power allocation scheme is achieved by minimizing the weaker link’s individual outage probability under the sum-power constraint and interference power threshold (IPT) constraints of the primary user (PU). Particularly, for the purpose of accomplishing the power allocation more realistically, the interference to each other between PU and secondary user (SU) and relay is taken into consideration. And the closed-form solution is derived for the optimum power allocation scheme of each case. Numerical results confirm that the proposed scheme improves the system performance compared with the equal power allocation scheme under various traffic requirements. The outage probability of SU communication is limited by the IPT constraints of PU and is affected significantly by the IPT level of PU. Furthermore, regardless of the symmetric or asymmetric traffic requirements, the proposed power allocation scheme is more suitable for cognitive two-way relaying networks.

Optimal power allocation for asymmetric analogue network coding in cognitive radio

In this study, the optimal power allocation (OPA) problem is studied for the two-way relay channel employing the analogue network coding protocol with the asymmetric traffic requirements in a cognitive radio network. The OPA scheme is proposed by maximising the sum-rate of the success delivery bit from the secondary user (SU) perspective subject to the sum-power constraint and the interference power threshold (IPT) constraints to the primary user (PU). In particular, for the purpose of accomplishing the power allocation more realistically, the interference to each other between the PU and the SU and the relay is taken into consideration and by solving the optimisation problem composed for each case, the closed form expressions of each node power are obtained. All the simulation results have demonstrated that the system with the proposed scheme outperforms the equal power allocation (EPA) scheme irrespective of the IPT. When the IPT constraint is introduced, the sum-rate of the success delivery bit of the SU communication converges to a certain level with the increasing total power. Meanwhile, the proposed strategy is superior to the conventional EPA scheme for any relay location, which is more remarkable when the relay is located on either end node regardless of the traffic symmetry or the asymmetry.

Linear precoding design for cognitive multiuser MIMO systems using a leakage-based approach

In this paper, we develop linear precoding schemes for cognitive radio (CR) multiuser multiple-input multiple-output (MU-MIMO) downlink systems. A secondary user base station (SBS) with multiple secondary users (SUs) sharing the primary user (PU) spectrum is considered. In the proposed scheme, the block diagonalisation (BD) algorithm is adopted to remove the co-channel interference from the SBS to the PU completely, and the matching weighted signal-to-leakage-and-noise ratio (SLNR) maximisation algorithm is proposed to mitigate interference between SUs. We also discuss the cases where the SBS has only partial channel information and the channel estimation with errors, respectively. The proposed scheme does not require a strict restriction on the number of transmit and receive antennas. Simulation results show that the proposed scheme can achieve high sum rate throughput with affordable complexity.

Interference Alignment with Complex FDPM-Based Subspace Tracking in MIMO Cognitive Networks

This paper addresses the implementation of interference alignment (IA) in cognitive networks, where the unlicensed secondary transmitter-receiver pairs modeled as a K-user multiple-input and multiple-output (MIMO) interference channel coexist with the licensed multi-antenna primary user. Starting from investigating the constraint conditions of IA scheme in MIMO cognitive networks, a practical IA algorithm is developed based on the minor subspace tracking that utilizes the fast data projection method (FDPM), which requires no channel knowledge of secondary network. In the proposed algorithm, each secondary transmitter first aligns their transmitted signal into the null space of the channel matrix from itself to the primary user without causing any interference to the primary. Then secondary transmitters and receivers alternately design the precoding and post processing matrices through a training period which exploits the complex FDPM-based subspace tracking, thus eliminating interference among secondary users. Simulation results show that the proposed algorithm can achieve a high sum rate performance while requiring low computational complexity.

Network-Coding-Based Hybrid-ARQ for Two-Way Relaying

Network coding is a promising technique to improve the throughput performance of wireless networks. In this paper, we propose a novel network-coding-based hybrid retransmission request protocol for two-way relaying system. The proposed protocol can retransmit more information in a given time interval by introducing network coding in the retransmission process, thus improving the throughput. Furthermore, we derive the frame error rate and delay performance using the L-ary pulse amplitude modulation by solving Markov state transition equations. Applying these results, the closed-form approximate solution of the throughput is acquired. Numerical results have validated our analytical results, and demonstrated that the proposed protocol outperforms the traditional hybrid retransmission request protocol for two-way relaying system by a throughput gain of about 9% when the relay lies close to the midpoint of the two users.

Traffic-knowledge-based relay selection for asymmetric two-way AF relaying networks

A novel relay selection criterion, in which the traffic-knowledge is utilized, is proposed for asymmetric two-way amplify-and-forward (AF) relaying networks. The system outage probability, diversity gain and coding gain are then investigated, and closed-form expressions are presented. Simulation results verify the accuracy of our derived outage probability expressions and highlight the performance of the proposed relay selection policy.

Network-coding-based hybrid-ARQ for bi-directional regenerative relaying

Network coding is a promising technique to improve the throughput performance of wireless networks. In this paper, we propose a novel network-coding-based hybrid retransmission request protocol for two-way relaying system. The proposed protocol can retransmit more information in a given time interval by introducing network coding in the retransmission process, thus improving the throughput. Furthermore, we derive the frame error rate and delay performance using the L-ary pulse amplitude modulation by solving Markov state transition equations. Applying these results, the closed-form approximate solution of the throughput is acquired. Numerical results have validated our analytical results, and demonstrated that the proposed protocol outperforms the traditional hybrid retransmission request protocol for two-way relaying system by a throughput gain of about 9% when the relay lies close to the midpoint of the two users.

Interference alignment for MIMO cognitive networks: a complex FDPM-based subspace tracking approach

Interference alignment (IA) for multiple-input multiple-output (MIMO) cognitive networks is considered by modelling the unlicensed secondary transmitter-receiver pairs which coexist with the licensed multi-antenna primary user as a K-user MIMO interference channel. Starting from investigating the constraint conditions of IA scheme in MIMO cognitive networks, a practical IA algorithm is developed by using a subspace tracking approach based on the complex fast data projection method (FDPM). In the proposed algorithm, first, each secondary transmitter aligns its transmitted signal into the null space of the channel matrix from itself to the primary user without causing any interference to the primary user. Then secondary transmitters and receivers, requiring no channel knowledge of secondary networks, alternately design the precoding and postprocessing matrices through a training period which exploits the complex FDPM-based minor subspace tracking, thus eliminating interference among secondary users. Moreover, the case where secondary transmitters have partial knowledge of channels from themselves to the primary user is also discussed. Simulation results reveal that the proposed algorithm can achieve a high sum rate performance while requiring low computational complexity.