Joint Collaborative Beamforming Design For Relay Networks

In the past decades, The multiple-input multiple-output (MIMO) system at-tracts much attention due to the demand for developing affordable bandwidth-efficient technologies to cater to the explosive growth of applications in the wireless communications field. The use of multiple antennas can fully exploit the space di-versity, and improve the system capacity and reliability. However, the limited size and the battery lifetime of the mobile devices challenge the design of such MIMO system.In cooperative communication, users can act as distributed relay nodes to form multiple paths from the source node to the destination node and these distributed nodes actually form a virtual MIMO system. Cooperative communications can also achieve the diversity and multiplexing gain, and to overcome the drawbacks of tra-ditional MIMO system. However, the assignment of each node weighting coefficient is a critical issue. In practical applications, we need to improve system performance and reduce the computational complexity in order to meet the needs of real-time communications.Various cooperative communication schemes have been presented. Amplify-and-forward (AF), decode-and-forward (DF) and compress-and-forward (CF) are three common fixed relaying schemes. Among all these schemes, AF protocol which just amplifies the received noisy signal and forwards it to other relay nodes or des-tinations, is the most attractive strategy due to its low complexity. These schemes have been well studied under different availability of CSI.Existing relay cooperative communication network, such as multi-source multi-relay cooperative networks, multi-hop multi-relay cooperative networks, etc. These network model contains more than one beamforming weight vectors. Their beam-forming optimization problems are multi-variable optimization problems that diffi-cult to be directly solved. Previous researchers used several suboptimal solution, the computational complexity of these methods is high and the performance is not superior enough. In this paper, we focus on two types of network model, and present a variety of better performance beamforming design method to solve the joint opti-mization of multivariable problems. The main contributions of our research can be summarized as follows:we consider a three-hop multi-relay network, which consists of a transmitter, a receiver and two clusters of relay nodes under the assumption of perfect CSI known both at the relay nodes and the receiver. The two clusters of relay nodes form a virtual MIMO system under AF protocol. In this work, we propose two different distributed beamforming approaches. In what follows, we show that, both the ob-tained optimization problems are non-linear nor convex about the two relay weights, and therefore it is very difficult to perform optimization on the two beamforming vectors jointly. To tackle that, we propose two iterative based convex optimal algo-rithms which can be used to obtain the relay weights efficiently. Simulation results revealed that, both our proposed approaches outperform the exsiting solutions with improved energy efficiency and better QoS in term of higher received SNR.We consider the uplink multi-source multi-relay cooperative networks, beam-forming optimization problems of this model contains two optimization variables: the relay weight vector and the basestation equalizer vector. We find that, for fixed relay weight vectors, there is a corresponding basestation beamforming equalizer vector that achieves the optimal performance. So the remaining main task is to find the optimal relay weight vectors, where the GA can be used as an optimizer. It can effectively avoid local optimal phenomenon. Simulation results show signif-icant improvement achieved by the proposed approaches, but the computational cost is somewhat increased, which is difficult to meet the requirements of real-time communication.Also for the multi-source multi-relay network model, we depth to explore the mathematical relationship between the two weight vectors. We find that the bases-tation equalizer vectors can be expressed in closed form solution using the relay weight vector, then we derive the optimal linear receivers and use schur complement to translate the original joint optimization problems of two weight vectors into the standard semi-definite programming problems which only involve one weight vector. Then the optimization problem can be optimally solved by using the interior-point method, and as such, it can avoid using iteration algorithm. Since the interior-point method has been very mature, the computational complexity is greatly reduced com-pared with GA, and this method can reach the global optimum. On this basis, this paper attempts to propose an improved beamforming design method which achieves improvement in computational complexity to meet the requirements of real-time wireless communications.