MIMO System Equalization Technology Based On Sphere Decoding Algorithm

Recently,due to the rapid development of modern wireless communication and users'increasing needs of data rate and better services, high broadband wireless communication system has been promoted . MIMO (multiple-input- multiple-output) technique transmits multiple data streams in spatial parallel sub-channels by multiple antennas in both transmitter and receiver, thus greatly increasing the system throughout and spectrum efficiency without additional bandwidth and power requirements. MIMO system can resist channel fading and improve wireless communication reliability through achieving space diversity gain using space-time coding and beam forming. Owing to the above advantages, MIMO technique has become one of the key technologies in high broadband wireless communication system.However, with the transmitted data from different transmitted antennas and multipath effects causing interfering with each other, it is a great challenge to eliminate inter-symbol interference and achieve low-complexity ML (maximum- -Likelihood) signal detection at the MIMO receiver side, which hinders the development and widely application of MIMO technique. To solve the problems mentioned above, in this paper, we focus on MIMO system equalization and signal detecting techniques based on SDA (sphere decoding algorithm).The content of this paper are listed as follows:1. Analyzing the fading characteristics of wireless mobile channel, modeling the MIMO channel using several channel modeling methods, and deducing mathematical expression of MIMO channel under flatting fading and frequency selective fading channel circumstances respectively .2. Deep research on linear equalizer and decision feedback equalizer in Single-Input-Single-Output system. Analyzing of equalizer performance based on ZF and MSE criteria and some factors which influence the performance are also given in this paper.3. Researches on the design method of MIMO time domain equalizer and MIMO frequency domain equalizing principles. SDA is clearly explained, some derivations and optimizations are made for using in MIMO signal detection.4. With MATLAB software, system simulations of MIMO flat fading channel and frequency selective fading channel have been accomplished. Analysis and discussion of performance in equalization and detection are also included.Simulation results show that MIMO DFE is superior to MIMO linear equalizer in equalization performance. Furthermore, to close to the quality of ML detection, the modified algorithm based on SDA is computationally efficient, it can achieve a preferred balance between computation and detection properties, and thus the detection efficiency is improved.