Study On Joint Transmit And Receive Antenna Selection Algorithm Based On Capacity In MIMO Systems

MIMO not only can effectively utilize the multi-path propagation, but also effectively improve the capacity and spectrum efficiency. Although MIMO have the potential of multiple the channel capacity and improve quality of service for communication, the cost and complexity of MIMO system is high. Antenna selection is using less RF links to match more antennas. It will reduce the cost and complexity and at the same time maintain most of the advantages of MIMO systems. We will study the technology of antenna selection in MIMO system in my master’s degree thesis. The main research works included as follows.1 The channel model of MIMO system is studied and the capacity of MIMO system is analyzed in ergodic capacity and outage capacity. By analyzing the outage capacity, diversity and multiplexing trade off is given. Some classical antenna selection algorithms are presented. The performance and defects of optimal joint transmit and receive antenna selection(JTRAS) algorithm, norm JTRAS algorithm, increasing JTRAS algorithm are obtained.2 The decreasing joint transmit and receive antenna selection algorithm is investigated, based on the analysis of the channel capacity, the equation about the decrease of the channel capacity is obtained when one more pair of transmit and receive antennas are removed. The decreasing joint transmit and receive antenna selection algorithm is proposed, which is suitable for the number of selected antennas is nearly the number of total antennas. According to proportion of the number of selected antennas and the total number of antennas, a fast adaptive antenna selection algorithm is proposed, which is suitable for any number of selected antennas.3 The application of the binary particle swarm optimization(BPSO) algorithm in wireless communication is studied. The theoretical model of BPSO joint transmit and receive antenna selection in MIMO system is presented. Based on the convergence of BPSO, an improved BPSO JTRAS is investigated. The results show that the improved BPSO JTRAS algorithm almost has the same performance of optimal JTRAS, while, the computational complexity of the BPSO JTRAS is smaller than the optimal JTRAS algorithm.