Precoding Techniques For Multiuser Multicell Downlink MIMO Systems

AMultiple input multiple output(MIMO) is a signal processing technology which both the sender and the receiver configure multiple antennas. MIMO technology is the most effective means in improving the spectral efficiency of physical layer for wireless communication systems. Due to the terminal size, power consumption and other restrictions, the terminal generally configures a little of antennas, This leads that MIMO technology is limited in point to point MIMO systems. Multiuser MIMO technology is proposed to effectively solve the above problems. In addition, in order to improve the spectral efficiency, MIMO systems usually regard inter-cell frequency reuse factor as 1, which leads to serious interference to the user, including inter-cell interference and intra-cell interference. Precoding technique is a effective method to elminates the interference for multiuser multicell MIMO systems.On the other hand, the base station(BS) need to get perfect channel state information(CSI) if we want to completely eliminate the interference which user received in multiuser multicell MIMO systems.This paper focuses on the relationship between the imperfect CSI and precoding performances, we mainly do the following:① We have studied the robust beamforming problem in multiuser MIMO downlink system under imperfect CSI. Firstly, we proposed a robust beamforming algorithm based on minimum mean square error(MMSE) in downlink centralized multiuser MIMO systems. Then we proposed a robust beamforming algorithm based on MMSE of signal leakage with distributed characteristics for downlink multiuser MIMO systems. The proposed two beamforming algorithms consider the impact of estimation, quantization and delay error existed in the channel state information. Numerical analysis shows that compared to the traditional MMSE algorithm, the proposed two downlink MU-MIMO beamforming algorithms can achieve better robustness.② We have studied the precoding problem based on block diagonalization(BD) in multicell cooperative downlink MIMO system. Firstly we introduced the BD-based precoding algorithm in network MIMO and multicell cooperative downlink MIMO systems. And then we proposed a BD-based algorithm in multicell partially cooperative downlink MIMO systems. In this paper, the BS just shared CSI of the edge users, so that we can reduce the amounts of CSI backhaul. We also analyzes the rate of loss because of the limited feedback CSI.③ We have studied the robust precoding problem in multicell partially cooperative downlink MIMO systems. In view of the rate lass under imperfect CSI with the proposed algorithm presented in Chapter 4, we proposed a robust double layer precoding algorithm for multicell partially cooperative downlink MIMO systems. The inner layer precoding algorithm trys to eliminate inter-cell interference of the cell edge user received by using zero forceing, it belongs to multicell partially cooperative areas; the outer layer precoding algorithm using the robust signal to leakage and interference ratio(SLNR) algorithm to eliminate intra-cell interference of the all user received.Compared to the proposed algorithm presented in Chapter 4, the proposed algorithm not only retains the advantages of fewer CSI needs, but also reduces the rate of loss, and enhances greatly user’s BER and the Channel capacity.④ We have studied the robust beamforming design based on quality of service(Qo S) in multicell MIMO downlink systems. We minimize a linear combination of characterizing each BS sum of transmitted power and its resulting sum of interference power inflicted, subject to maintaining a set of desired Qo S levels,and then use uplink-downlink duality, we obtain a low complex iterative algorithm. Simulation results show that compared to traditional multicell cooperative downlink beamforming algorithm, the proposed algorithm only requires less transmit power in the same target signal to interference noise ratio(SINR) constraints.