Research On Multi-user Detection Technology In MIMO-OFDM System

When the future wireless communication achieves high-speed data transmission and provides multimedia services it faces two major challenges: multipath fading and bandwidth utilization. The Orthogonal Frequency Division Multiplexing (OFDM) technology decomposes the channel into multiple orthogonal sub-channels and transforms frequency selective multi-path fading channel to flat fading channel, it effectively reduces the affect of multipath fading. The Multiple-Input Multiple-Output (MIMO) technology produces multiple independent parallel channels in space and transmits data simultaneously, so it can increase times of the capacity of communicate system and spectrum efficiency without any additional bandwidth.MIMO-OFDM system which is combined by MIMO technology and OFDM technology is a great breakthrough of antenna technology in wireless telecommunication. It can significantly improve the channel capacity and transmission speed, effectively resistant to multipath fading and inhibited of interference and noise in wireless communication system. So it is considered to be the key technology in the next-generation wireless communication. Multi-user detection (MUD) is a new method of resisting MAI at the receiver. It can not only eliminate MAI, but also can resist near-far problem and interference of multipath so as to improve the performance of the system.The main works of this paper can be summarized as follows:1. Introduce the basic principle of MIMO and OFDM technology and analysis the model and features of MIMO-OFDM system.2. Discuss the MUD technique and introduce the basic idea, system model, performance indicators, and the classification of algorithm then compare the different algorithms in simulation.3. Research signal detection techniques in MIMO-OFDM system, mainly analyze the maximum likelihood detection (ML), zero forcing detection algorithm (ZF), minimum mean square error detection algorithm (MMSE) and MMSE-based parallel interference cancellation detection algorithm (MMSE-PIC), then simulate and compare the performance of ZF, MMSE and ML algorithm.4. At last, present an iterative receiver for MIMO-OFDM system. The receiver performs channel estimation and multi-user detection, with soft information iteratively provided by the single-user decoders. Simulation results show that the performance of system is improved through iteration.