Research On Joint Relay And Antenna Selection And Link Adaptation In MIMO Cooperative Communications

In the future, the applications of a great amount of wireless intelligent equipments will need faster intercommunication, which fetches stringent challenges to the current wireless communication systems. This is due to the fact that most of the equipments today are only equipped with one antenna. As a way, the future equipments will tend to equip more than one antenna. Many outputs have been available on relay selection and link adaptation areas for single antenna cooperative scenario, while people rarely concentrate on multiple antenna scenarios. This thesis introduced genetic search and fuzzy control techniques into the study of the relay and antenna joint selection and link adaptive algorithms in MIMO (Multiple Input Multiple Output) cooperative communication systems, providing meaningful considerations for the design of the next generation mobile communication. The main contributions of this thesis including:Firstly, we classified cooperative relay nodes into four categories and thereafter analyzed their features and cooperative capabilities. By taking source, relay, destination node’s antenna selection and relay selection as a whole, we proposed Joint Relay and Antenna Selection Algorithm (JRAS) with the help of the genetic search method. Simulating results shows that the proposed JRAS algorithm is close to the complete exhaust search algorithm in ergodic capacity and outage capacity, and better performed than JTRAS algorithm.Secondly, to exploit the advantages of fuzzy control methods in resolving multiple variable problems, we proposed a link adaptive algorithm based on fuzzy controls in MIMO cooperative communication systems. Such systems are able to select proper coding and modulation strategies according to the channel conditions. Simulating results show that the proposed algorithm achieved good trade-offs between the communication robustness and efficiency.