Sphere Decoding Algorithm For MIMO System

Digital communication using multiple-input–multipleoutput (MIMO) has recently emerged as one of the most significant technical breakthroughs in modern communications in the last two decades. The technology figures prominently on the list of recent technical advances with a chance of resolving the bottleneck of traffic capacity in future high speed wireless networks. Perhaps even more surprising is that just a few years after its invention the technology seems poised to penetrate large-scale standards-driven commercial wireless products and networks such as broadband wireless access systems, wireless local area networks (WLAN), third-generation (3G) networks and beyond. The advantage of MIMO system is its potential huge capacity, and the capacity increases linearly with the lesser number of the transmit and receive antennas. The theoretical research and practical application indicate that MIMO system is the important technology to realized the future high speed gigabit wireless communication, so it has high research value. After nearly ten years efforts, great development has been gained for MIMO system and its related technology. However, some disadvantages still exist: (1) The research on the MIMO capacity is not complete. The exist research is generally based on the rayleigh distribution assumption. However, in some case of wireless communications, such as the broadband wireless access system, the proper channeal model is the ricean channel model. How to model this multiple antenna system and what transmit scheme should be adopted is worth studying. (2) The detection problem for MIMO system needs further research. In order to approach the MIMO system capacity, good detection algorithm is needed. However the mimo system brings the huge capacity as well as high complexity of the receive signal detection. Sphere decoding algorithm is a detection algorithm with optimal performance and medium complexity. However, the exist sphere decoding algorithm can not solve the system where there are more transmit antennas then the receive antennas. The generalized sphere decoing algorithm could overcome the shortcomings of the sphere decoding algorithm, but the complexity is very high. (3) Joint the detection and decoding for MIMO system need to be improved. The joint detection and decoding can further improve the system performance. However how to combine the sphere decoding algorithm and Turbo iterative decoding to further improve the system performance need research. The core problem is how to construct a soft sphere decoder. The research focusing on these shortcomings is very important and valuable. Our research obtained support of the support of National Natural Science Foundation (Investigation of Wireless Multimedia Techniques based on Multimedia Transmission Property, No. 60202005). Our research work contains three categories: (1) the modeling and simulation of the ricean channel multiple antennas system adopting transmitted power optimal allotment; (2) the research on the fast generalized sphere decoding algorithm which is suitable for the cases where there are more transmit antennas then the receive antennas; (3) the soft generalized sphere decoder for the joint detection and decoding . The contribution of this thesis contains the following aspects: (1) propose the multiple-antenna system capacity model with ricean distribution, analysis the capacity with optimal transmit power allotment, and compare with the equal transmit power allotment with low complexity The conclusion could be helpful for the wireless communication system design. (2) Propose a new fast generalized sphere decoding algorithm. This algorithm usestwo regular sphere decoding algorithm to solve the cases where there are more transmit antennas then the receive antennas. It is very simple and easy to be implemented. We name this algorithm as double layer sphere decoding algorithm.; (3) Propose an improved double layere sphere decoder. This decoder can adjust its search radius according to the SNR change. Its performance is stable then the previous double layer sphere decoding algorithm; (4) Give a system model using joint sphere decoding algorithm and Turbo iterative decoding algorithm and propose a soft list generalized sphere decoder to be used in this model. This decoder can receive and produce the soft information. The simulation result shows that this system achieves the near-capacity of multiple-antenna system.