Research On Limited Feedback-based Precoding And Antenna Combining Techniques In MIMO Systems

The demand of wireless services have been continually growing in recent years. In order to efficiently utilize spectrum resources, signal transmission techniques based on multiple-input multiple-out(MIMO) structure have attracted lots of attentions. It has been theoretically proved that MIMO techniques can exponentially increase spectrum effectiveness compared with single-input sigle-output(SISO) systems. Therefore, MIMO is considered as one of the key techniques in future wireless communication systems. This dissertation presents the research of the procoding and antenna combining techniques of MIMO systems. Considering that the uplink rate of practical wireless communiation systems is limited, the transmission techniques proposed in this dissertation are based on limited feedback. The full text summary is described as follows:In Chapter 2, a simplified codeword searching algorithm is proposed in order to reduce the channel quantization complexity at receivers. The operations of channel quantization contain two parts, the first part is the calculation of the quantization error of each codeword, and the second part is the searching strategy among all codewords. The codeword searching strategy depends on the codebook structure, while the widely used strategy is the ergodic search. The codeword searching algorithm proposed in this chapter aims at simplifying the calculation of quantization error of each codeword, and this algorithm can be adapted to any type of codebook.The existing linear procoding algorithms require considerable feedback overhead in order to achieve the full multiplex gain. An efficient approach of reducing the feedback overhead is designing specific feedback and precoding strategies for specific scenarios. In practical multiuser MIMO systems, it is a commen scenario where one base station simultaneously transmitting signals to two users. In chapter 3, we propose a linear precoding algorithm for this scenario, and the proposed algorithm can achieve higher performance compared with the exiting linear procoding algorithms.As the representative strategy of opportunistic commucations, per user unitary rate control(PU2RC) is widely used in practical wireless systems. In chapter 4, we propose a multimode transmission(MMT) strategy and the corresponding codebook design algorithm for PU2 RC systems in order to overcome its inherent shortcomings. In the proposed MMT strategy, each user report two parameters in order to allow the transmitter to design the optimum user scheduling strategy. The proposed MMT strategy can enhance the system’s roubustness without requiring additional feedback overhead. In this chapter, we also derive the probability distribution function(pdf) of each user’s pre-scheduling signal interference noise ratio(SINR) for PU2 RC system. This result is quite useful in the design of MMT and feedback strategies for PU2 RC system, and an dimension-reducing algorithm derived in the derivation process is quite useful in the performance analysis and beamforming stategy design of MIMO procoding systems.Antenna combining techniques is an important signal detection strategy in limited feedback-based multiuser MIMO systems. The existing optimal antenna algorithm is derived conditioning on user scheduling, however, the latest research shows that the optimum strategy of feedback resource distribution is to allocate the feedback overhead to small number of users. In chapter 5, we proposed the optimal antenna algorithm for this feedback resource distribution strategy and present the lower bound of the proposed combiner’s performance. The analysis method utilized in this chapter can be easily extended to other types of MIMO systems.In the last chapter, the summary of the dissertation is presented, and the future work is introduced.