The Study On Antenna Selection Based Channel Capacity In MIMO Syetem

The development of wireless mobile communication technology leads to thetraffic trend to video，multimedia traffics in communication technology from thetraditional voice communication, so that larger bandwidth and greater capacity onthe wireless network are required. Multi-input multi-output (MIMO), as a majorbreakthrough in wireless mobile communication technologies, can greatly improvesystem capacity and spectrum utilization, and it has been paid more and moreattention. However, the setting of multi-antenna in MIMO communication systemsneed more radio links, which not only virtually increases the system’s hardwarecosts, but also increases the complexity of the system. The antenna selection shouldbe accomplished by using less radio links to comply more antennas and less systemperformance loss, the hardware cost of the system and system complexity can alsobe effectively reduced, for the antenna selection technique is studied in this paper.Firstly, in this paper, the background, current status, several different loss andexisting problems in wireless MMO technology are discussed in detail, theperformance of antenna selection MIMO system, the system bit error rate andchannel capacity in-depth concerning on antenna selection are analyzed. Then, aMIMO system model was built based on antenna selection in MIMO and MIMOchannel capacity formula is derived.Secondly, in practical wireless communication systems, the transmitting andreceiving antenna selection algorithm is so complicated that it is particularlyimportant to reduce the complexity of the algorithm. The antenna selectionalgorithms in the MIMO system were analyzed and summarized from the pointbased on the achieved maximum of channel capacity and the less complexity ofsystem calculation at the same time. Compared with several common algorithmsbased on the domestic and foreign researchers on antenna selection algorithm, anew antenna selection algorithm was proposed and compared with the originalalgorithm. When the algorithm starts, the receiving antenna set is setted empty, andwhen the iteration begins, the receiving antenna with the largest contribution to thechannel capacity will be selected and added to the collection. At the receiving end,the largest M lines of the channel capacity of the H channel matrix are selectedgradually and added to the antenna subset. A fast iterative update formula is used in the new proposed algorithm, which has lower computational complexity than theDS algorithm, and can be completed with almost the same channel capacity and biterror rate performance compared with the optimal antenna selection algorithms.Especially in the quasi-static Rail fading channel, the algorithm is superior to theNBS algorithm, the CBS algorithm and random antenna selection algorithm.Finally, simulation results show that the new algorithm is able to achieve theperformance on channel capacity and bit error rate close to the optimal algorithmwith a lower computational complexity, and could meet the requirements of thereal-time signal transmission.