Adaptive And Cooperative Beamforming For Wireless Communication System

Wireless communication is one of the most vibrant areas in the technical field today. The third Generation wireless communication system has been widely applied in commercial environment, but its performance is still not satisfied to the increasing requirement. The fact that the radio resourse is more and more precious imperatively demands the advanced technologies in wireless communictions. So the next generation wireless communication systems should provide higher capacity and spectral efficiency to meet the needs of providing various data sevice at mobile ends. Multiple-Input Multiple-Out systems can exploit spatial multiplex gain with multiple antennas being equipped both at the transmitter and receiver. The significant improvement of data transmission rate and spectral efficiency can be achieved in MIMO systems without any extra requirement of frequency band and transmit power. However, the potential benefits can not be utilized since it is difficult to implement multiple antennas at mobile terminal in practical due to the limited size, complexity and power conservation of mobile unit, cooperative schemes among users are proposed as an alternative technology, which is often called cooperative communication. In such schemes, users are allowed to carry not only its own information transmission but also other user's transmission. In this dissertation, we aim to design beamforming schemes for MIMO systems and cooperative communication systems, such as adaptive beamforming in MIMO systems, adaptive downlink beamforming in multiuser MISO systems, cooperative beamforming in multi-hop multi-relay networks and robust cooperative beamforming in multi-source multi-relay networks.In chapter 1, we give an overview of the development of wirless communication technology, and introduce the application of beamforming in wireless systems. Some conventional beamforming algorithms are described in chapter 2. The main work in this dissertation focus on adaptive and cooperative beamforming, which are detailed discussed as follows: 1. An adaptive eigen-beamforming method for MIMO systems is proposed. The traditional eigen-beamforming method requires the computation of eigenvalue or singularvalue decomposition of channel response matrix, which has high computational complexity. The proposed method obtains the transmit and receive beamforming vectors based on subspace tracking, which updates singular values and the corresponding left and right singular vectors of channel response matrix using a given random vector. Then, the performance is further improved by combining with a subchannel selection algorithm. The proposed method can obtain required beamforming vectors without the computation of matrix decomposition, which resulting in a lower complexity. Simulation results verify the effectiveness and advantage of the proposed method.2. We consider adaptive downlink beamforming stratergy for multiuser MISO systems. In our proposed method, the singular value and singular matrices of the selected user's channel matrix, which is obtained using SUS, are estimated using power iteration method. Then the optimal downlink beamforming matrix can be derived using such matrices. The new adaptive beamforming algorithm has lower computational complexity due to only containing multiplication and addition of matrix in its iterative formulations. Simulation results verify the effectiveness of the proposed method.3. The cooperative beamforming solutions for the multi-hop multi-relay wireless networks are investigated. In such networks, the communication between source and destination is accomplished by a three-hop channel with aid of two relay clusters under amply-and-forward (AF) protocol. Our objective is to optimize the complex amplify-and forward weights of the relaying terminals if the channel state information is exploited. In this part, three appropriate method are given. First, we illustrate the near optimal coolaborative relay beamforming weights can be found from solving an unconstrained multi-variant minimization problem. Second, using the concept of subspace averaging, a low-complexity sub-optimal closed-form solution is then proposed. Third, a suboptimal solution can be obtained by semidefinite programming (SDP). An improved method is also proposed in combination with bisection search. Finally, the effectiveness of proposed methods is verified through computer simulations.4. In multi-source multi-destination relaying networks, we develop a robust cooperate-ve beamforming in the presence of a bounded uncertain CSI. Our aim is to optimize the complex weights of the relays such that the SINRs at all destinations are above pre-defined threshold. To obtain this, we minimize the total transmit power at relays using optimization of worst-case SINR performance. It is shown that the original problem can be formulated by a convex SDP problem with SDR. Simulation results illustrate the proposed solution can guarantee the user's QoS in terms of SINR with a little bit more extra transmit power.In the last part, we give the prospect of adaptive and cooperative beamforming in wireless communication systems and point out the direction of future research work.