Study On Resource Allocation Algorithm In Multiuser MIMO-OFDM System

The next-generation mobile communication systems are required to provide high data-rate, high reliable transmission, and guarantee end-to-end QoS. MIMO, OFDM, and adaptive transmission have been comprehensively considered as the major candidate techniques for future radio communication systems. In frequency selective channels, adaptive MIMO-OFDM systems are able to support high reliable and high spectral efficiency communication with low complexity, while it can adjust various parameters dynamically so that the system resources adapt to the variations of wireless environment. Adaptive subcarrier allocation technique is employed in multiuser OFDM applications, which assigns the subcarriers among users according to their channel conditions. A large amount of researches have shown that adaptive subcarrier allocation can improve the performance or enhance the capacity significantly by exploiting the multiuser diversity resulting from users' random locations.This paper we have proposed two algorithms based on mulituser MIMO-OFDM system :First, MIMO-OFDM system has been turned into virtual OFDM system through singular value decomposition (SVD). At the same time, a particle swarm optimization algorithm based multiuser MIMO-OFDM system has decreased the complexity of the algorithm and improved gains of system.Second, we have improved a fair resource allocation scheme based on cross-layer architecture. This scheme assigns sub-carriers and transmission power among users according to their delay in the queue of data link layer. And it has optimized fairness and throughput.This paper consists of five chapters. The first chapter is introduction, which presents the research background, meaning of resource allocation. In the second chapter, we show the principle of MIMO-OFDM system. We research resource allocation based on PSO algorithm in chapter three. In chapter four, we research resource allocation based on cross-layer structure. The fifth chapter is conclusion, which generalizes the main work of this paper and future work.