Dongtang Ma

Maximizing the Sum-Rate of Amplify-and-Forward Two-Way Relaying Networks

This letter addresses the problem of beamforming design for an amplify-and-forward (AF) based two-way relaying network (TWRN) which consists of two terminal nodes and several relay nodes. Considering a two-time-slot relaying scheme, we design the optimal beamforming coefficients to maximize the sum-rate of AF-based TWRN under total relay power constraint (TRPC). Although the optimization problem is neither convex nor concave, we show that the global optimal solution can be obtained by the branch-and-bound algorithm. To address the computational complexity concern, we also propose a low-complexity suboptimal solution which is obtained by optimizing a cost function over one real variable only. Simulation results show that the proposed optimal solution outperforms existing schemes significantly. Moreover, we show that the suboptimal solution only suffers small sum-rate losses compared to the optimal solution.

Destination-Aided Cooperative Jamming for Dual-Hop Amplify-and-Forward MIMO Untrusted Relay Systems

In this paper, we consider a dual-hop amplify-and-forward (AF) multiple-input-multiple-output (MIMO) relay network, where the source, relay, and destination are each equipped with multiple antennas. The relay is untrusted if it is willing to forward the signal to the destination and, at the same time, acts as a potential eavesdropper to interpret the message from the source. Since there exists no direct link between the source and the destination, a positive secrecy rate cannot be obtained. Addressing this issue, we propose a joint destination-aided cooperative jamming and precoding at both the source and the relay scheme: joint source, relay, and destination precoding (JP). We target at maximizing the secrecy rate by jointly designing the source, relay, and destination precoding matrices and propose an alternating iterative optimization algorithm to tackle the nonconvex problem. Then, a comprehensive study on the asymptotic performance is conducted in a high signal-to-noise ratio (SNR) regime. In particular, we present simple closed-form expressions for the two key performance parameters in the asymptotic secrecy rate, i.e., the high-SNR slope and the high-SNR power offset. Finally, numerical results are conducted to demonstrate the validity of the proposed secure scheme and its performance analysis.

Evaluating the impact of network density, hidden nodes and capture effect for throughput guarantee in multi-hop wireless networks

To optimize the performance of wireless networks, one needs to consider the impact of key factors such as interference from hidden nodes, the capture effect, the network density and network conditions (saturated versus non-saturated). In this research, our goal is to quantify the impact of these factors and to propose effective mechanisms and algorithms for throughput guarantees in multi-hop wireless networks. For this purpose, we have developed a model that takes into account all these key factors, based on which an admission control algorithm and an end-to-end available bandwidth estimation algorithm are proposed. Given the necessary network information and traffic demands as inputs, these algorithms are able to provide predictive control via an iterative approach. Evaluations using analytical comparison with simulations as well as existing research show that the proposed model and algorithms are accurate and effective.

On Ergodic Secrecy Rate for MISO Wiretap Broadcast Channels with Opportunistic Scheduling

In this letter, we study on-off opportunistic beamforming for the multiuser downlink channel with a passive eavesdropper. Two opportunistic scheduling schemes exploiting multiuser diversity are investigated which require limited feedback of the effective signal-to-noise ratio (SNR) from the legitimate users. For the two scheduling schemes, we derive new closed-form expressions for the ergodic secrecy rate with on-off beamforming over Rayleigh fading channels. Numerical results are provided to verify our analytical results and illustrate the impact of multiuser diversity on the secrecy performance.

Robust Artificial Noise Aided Transmit Design for MISO Wiretap Channels with Channel Uncertainty

In this letter, we study the robust artificial noise (AN) aided transmit design for a multiple-input single-output (MISO) wiretap channel with a single-antenna eavesdropper. We consider two uncertainty models for the imperfect channel state information (CSI) on the main and eavesdroppers channels at the transmitter. For the deterministic uncertainty model, we solve the worst-case secrecy rate maximization (WC-SRM) problem via semidefinite program (SDP). For the stochastic uncertainty model, we propose a suboptimal solution to the outage probability constrained secrecy rate maximization (OP-SRM) problem based on the robust design for the WC-SRM problem. The simulation results demonstrate performance improvement of the proposed worst case robust design as compared to that based on the worst case method without usage of AN.

Secrecy Performance Analysis for TAS-MRC System With Imperfect Feedback

In this paper, we investigate the secrecy performance for a multiple-input multiple-output (MIMO) wiretap channel in the presence of a multiantenna eavesdropper. In particular, the legitimate transmitter uses transmit antenna selection (TAS) to transmit on a single antenna with the largest signal-to-noise ratio (SNR) while both the legitimate receiver and the eavesdropper adopt maximal ratio combining (MRC) for reception. We derive exact closed-form expressions for the probabilities of achieving positive secrecy rate and secrecy outage in the case of imperfect feedback due to feedback delay and/or feedback error. Furthermore, we derive the asymptotic secrecy outage probability at high SNR, which accurately reveals the secrecy diversity loss due to imperfect feedback. Simulation results are provided to verify our analytical results and illustrate the impact of imperfect feedback on the secrecy performance of such a wiretap system.

Multiple carrier frequency offsets tracking in co-operative space-frequency block-coded orthogonal frequency division multiplexing systems

This study addresses the problem of carrier frequency offset (CFO) tracking in co-operative space-frequency block-coded orthogonal frequency division multiplexing (OFDM) systems with multiple CFOs. Considering that the inserted pilot tones are decayed by data subcarriers in the presence of multiple CFOs, a novel recursive residual CFO tracking (R-RCFOTr) algorithm is proposed. This method first removes CFO-induced inter-carrier interference from data subcarriers, and then updates the residual CFO (RCFO) estimation of each OFDM block recursively. When used in conjunction with a multiple CFOs estimator, the proposed R-RCFOTr can effectively mitigate the impacts from the multiple RCFOs with affordable complexity. Finally, simulation results are provided to validate the effectiveness of our proposed R-RCFOTr algorithm, which has performance close to that of perfect CFO estimation at moderate and high signal-to-noise ratio, and significantly outperforms conventional CFO tracking algorithm for large CFOs.

Distributed interference-aware relay selection for IEEE 802.11 based cooperative networks

Cooperative communication has been recently proposed as a way to mitigate fading in wireless networks. Analytical results indicate that network performance improvement by cooperative communication heavily depends on selecting suitable relay nodes. Previous work on relay selection fails to consider the impact of inter-node interference among transmissions, which potentially results in a degradation of network performance. In this study, it is shown how the use of relay nodes may degrade rather than improve network performance (e.g. throughput) in scenarios where inter-node interference is not accounted for. In this approach, inter-node interference is embedded into our relay selection strategy through a newly proposed distributed interference-aware relay selection (DIRS) algorithm for IEEE 802.11-based wireless networks with multiple source–destination pairs. Under DIRS algorithm, each source–destination pair will select an optimal relay based on both the channel quality and the interference information, which can be obtained locally without the knowledge of topology information. The simulation results demonstrate the effectiveness of our proposal and show that inter-node interference can be mitigated by optimising relay selection.

Low-Complexity Data-Detection Algorithm in Cooperative SFBC-OFDM Systems With Multiple Frequency Offsets

This paper addresses the problem of data detection in cooperative space-frequency block-coding (SFBC) orthogonal frequency-division multiplexing (OFDM) systems in the presence of multiple carrier frequency offsets (CFOs). A new ordered-successive parallel interference cancellation (OSPIC) detector is proposed. This method consists of first carrying out coarse ordered interference cancellation detection, where the interference components are successively eliminated, and then performing fine interference cancellation detection using parallel interference reduction. Simulation results show that the proposed detector significantly outperforms existing detectors and performs close to that of CFO-free systems for practical signal-to-noise ratios (SNRs). To further reduce the computational complexity, a minimum mean-square error (MMSE)-based reduced-complexity OSPIC (RC-OSPIC) detector is proposed. Compared with the MMSE detector, which requires a full-size complex matrix inversion, the proposed RC-OSPIC detector performs better and is computationally much more effective.

Robust Masked Beamforming for MISO Cognitive Radio Networks With Unknown Eavesdroppers

This paper studies a cognitive radio network (CRN), in which a multiple-input single-output (MISO) secondary transmitter (SU-Tx) aims to send confidential messages to its receiver (SU-Rx) in the presence of unknown eavesdroppers, while having to control its generated interference to the primary users (PUs) under a given threshold. Because the eavesdroppers are unknown, this paper considers the artificial noise (AN) approach or masked beamforming to provide the information secrecy. The objective of this paper is to maximize the power of AN in order to degrade the eavesdroppers, subject to the signal-to-interference-plus-noise ratio (SINR) constraint at the SU-Rx, as well as the interference temperature limits (ITLs) for the PUs. In the case of perfect channel state information (CSI), we reveal that the optimal strategy for the information-bearing signal is beamforming. Imperfect CSI cases of bounded and stochastic uncertainties are investigated. In the case of ellipsoid-bounded errors, we derive the equivalent forms for the SINR and ITL constraints and then transform the optimization problem into a form of semidefinite programming (SDP). For the case of probabilistic CSI uncertainties, we propose an outage-constrained robust formulation where the CSI errors are Gaussian distributed. With the aid of two kinds of Bernstein-type inequalities, we reexpress the probabilistic constraints into deterministic forms, which results in a safe approximate solution.