Robust Signal Detections For Multiusers MIMO Systems

MIMO signal detection, a key technique in MIMO system, has been extensively studied and many detection algorithms have been proposed by scholars. However, most of the current detection algorithms are based on completely accurate CSI and the performances of these algorithms would be down sharply when the CSI is not perfect. It’s almost impossible to obtain the perfect CSI due to finite number of pilot squences and rapidly time-varying channel parameters. The CSI of non-collaborative users from other communications cells and jamming signals is difficult to obtain for multiuser MIMO systems specially. Therefore, achieving well performance under the condition of imperfect and partial CSI is an urgent problem for the MIMO signal detection algorithms. This thesis focuses on this problem.The thesis proposes a robust signal detection algorithm for uplink multiuser MIOM system. The algorithm can obtain the well performance in both cases that imperfect and partial CSI. The major contents and innovation points of the paper are as follows:(1) This thesis proposes a multiuser MIMO detection model based on joint space-time information. Using space-time process, the multiuser MIMO detection model can be posed as ill-conditioned linear equations.(2) Truncated singular value decomposition is used to solve the problem of signal detection for multiuser MIMO system. Regularization methods are efficent ways to solve ill-conditioned linear equations. The truncated singular value decomposition, a regularization method, is applied to the field of MIMO detection and then three stratagies are proposed to choose the regularization factor based on three communication scene in this paper.(3) The problem of signal detection for multiuser MIMO system is solved by using Landweber iteration. Landweber iteration is widely applied to the field of image reconstruction. This method is employed to resovle the problem of MIMO detectection. And two stratagies are proposed to determine the regularization factor corresponding to two commnuication scenes.At last, the proposed algorithms are simulated. The results show that the proposed methods can achieve well performance much better than that of ZF and MMSE when CSI is imperfect, expecially under strong near-far effect.