Robust Iterative Transceiver Beamforming For Multipair Two-Way Distributed Relay Networks

OAPA In this paper, the transceiver beamforming problem is studied for multipair two-way distributed relay networks, particularly with multi-antenna user nodes and in the presence of channel state errors. With multi-antenna setting on the user nodes, some of the usual signal processing tasks are shifted from the relay nodes to the user nodes with the proposed transceiver beamforming designs. The transmit beamforming vectors, distributed relay coefficients and the receive beamforming vectors are obtained by iteratively solving three sub-problems, each having a closed-form solution. The tasks of maximizing desired signal power, and reducing inter-pair interference (IPI) and noise are thus allocated to different iteration steps. By this arrangement, the transmit and receive beamformers of each user are responsible for improving its own performance and the distributed relay nodes with simple amplify-and-forward protocol aim at creating a comfortable communication environment for all user pairs. With respect to the channel uncertainty, two relay strategies are proposed considering two different requirements from the communication network: sum relay output power and individual relay output power. Our simulation demonstrates that the performance improvement can be very significant through cooperation of the three components, especially when the number of relay nodes is large

Beamforming and Power Splitting Designs for AN-aided Secure Multi-user MIMO SWIPT Systems

In this paper, an energy harvesting scheme for a multi-user multiple-input-multiple-output (MIMO) secrecy channel with artificial noise (AN) transmission is investigated. Joint optimization of the transmit beamforming matrix, the AN covariance matrix, and the power splitting ratio is conducted to minimize the transmit power under the target secrecy rate, the total transmit power, and the harvested energy constraints. The original problem is shown to be non-convex, which is tackled by a two-layer decomposition approach. The inner layer problem is solved through semi-definite relaxation, and the outer problem, on the other hand, is shown to be a single- variable optimization that can be solved by one-dimensional (1- D) line search. To reduce computational complexity, a sequential parametric convex approximation (SPCA) method is proposed to find a near-optimal solution. The work is then extended to the imperfect channel state information case with norm-bounded channel errors. Furthermore, tightness of the relaxation for the proposed schemes are validated by showing that the optimal solution of the relaxed problem is rank-one. Simulation results demonstrate that the proposed SPCA method achieves the same performance as the scheme based on 1-D but with much lower complexity.Comment: 12 pages, 6 figures, submitted for possible publicatio

Adaptive Beamforming for Distributed Relay Networks

Tremendous research work has been put into the realm of distributed relay networks, for its distinct advantages in exploiting spatial diversity, reducing the deployment cost and mitigating the effect of fading in wireless transmission without the multi-antenna requirement on the relay nodes. In typical relay networks, data transmission between a source and a destination is assisted by relay nodes with various relaying protocols. In this thesis, we investigate how to adaptively select the relay weights to meet specific interference suppressing requirements of the network. The thesis makes original contributions by proposing a filter-and-forward (FF) relay scheme in cognitive radio networks and an iterative algorithm based transceiver beamforming scheme for multi-pair relay networks. In the firstly proposed scheme, the relay nodes are adapted to deal with the inter-symbol-interference (ISI) that is introduced in the frequency-selective channel environment and the leakage interference introduced to the primary user. Our proposed scheme uses FF relay beamforming at the relay nodes to combat the frequency selective channel, and our scheme also aims to maximize the received SINR at the secondary destination, while suppressing the interference introduced to the primary user (PU). This scheme is further extended to accommodate a relay nodes output power constraint. Under certain criteria, the extended scheme can be transformed into two sub-schemes with lower computational complexity, where their closed-form solutions are derived. The probability that we can perform these transformations is also tested, which reveals under what circumstances our second scheme can be solved more easily. Then, we propose an iterative transceiver beamforming scheme for the multi-pair distributed relay networks. In our scheme, we consider multi-antenna users in one user group communicating with their partners in the other user group via distributed single-antenna relay nodes. We employ transceiver beamformers at the user nodes, and through our proposed iterative algorithm the relay nodes and user nodes can be coordinatively adapted to suppress the inter-pair-interference (IPI) while maximize the desired signal power. We also divide the rather difficult transceiver beamforming problem into three sub-problems, each of which can be solved with sub-optimal solutions. The transmit beamforming vectors, distributed relay coefficients and the receive beamforming vectors are obtained by iteratively solving these three sub-problems, each having a closed-form solution. The tasks of maximizing desired signal power, and reducing inter-pair interference (IPI) and noise are thus allocated to different iteration steps. By this arrangement, the transmit and receiver beamformers of each user are responsible for improving its own performance and the distributed relay nodes can be employed with simple amplify-and-forward(AF) protocols and only forward the received signal with proper scalar. This iterative relay beamforming scheme is further extended by distributing the computation tasks among each user and relay node, through which high computational efficiency can be ensured while extra overhead of bandwidth is need for sharing beamforming vector updates during the iteration steps. Furthermore, with respect to the channel uncertainty, two more relay strategies are proposed considering two different requirements from the communication network: sum relay output power and individual relay output power. At last, the application of the iterative relay beamforming method in cognitive radio networks is studied, where multiple pairs of users are considered as secondary users (SUs), and the designed transmit beamforming vector, relay beamforming vector and receive beamforming vector together guarantee that the inner interference of their transmissions is well suppressed while the interference introduced by them to the PU is restricted under a predefined threshold

Robust Beamforming for Cognitive and Cooperative Wireless Networks

Ph.DDOCTOR OF PHILOSOPH

Array communications in wireless sensor networks

Imperial Users onl

Efficient Robust Adaptive Beamforming Algorithms for Sensor Arrays

Sensor array processing techniques have been an important research area in recent years. By using a sensor array of a certain configuration, we can improve the parameter estimation accuracy from the observation data in the presence of interference and noise. In this thesis, we focus on sensor array processing techniques that use antenna arrays for beamforming, which is the key task in wireless communications, radar and sonar systems. Firstly, we propose a low-complexity robust adaptive beamforming (RAB) technique which estimates the steering vector using a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) algorithm. The proposed LOCSME algorithm estimates the covariance matrix of the input data and the interference-plus-noise covariance (INC) matrix by using the Oracle Approximating Shrinkage (OAS) method. Secondly, we present cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. The proposed algorithms are based on the exploitation of the cross-correlation between the array observation data and the output of the beamformer. Thirdly, we propose distributed beamforming techniques that are based on wireless relay systems. Algorithms that combine relay selections and SINR maximization or Minimum Mean-Square- Error (MMSE) consensus are developed, assuming the relay systems are under total relay transmit power constraint. Lastly, we look into the research area of robust distributed beamforming (RDB) and develop a novel RDB approach based on the exploitation of the cross-correlation between the received data at the relays and the destination and a subspace projection method to estimate the channel errors, namely, the cross-correlation and subspace projection (CCSP) RDB technique, which efficiently maximizes the output SINR and minimizes the channel errors. Simulation results show that the proposed techniques outperform existing techniques in various performance metrics