The Key Techniques Research Of The Multi-User MIMO Systems

In recent years, burst of booming demands for wide-band high data rates communication services and necessity of integrating internet with multimedia applications have aroused new challenges for next generation wireless communication systems. Clearly, both information reliability and high data rates must be taken into account. In order to meet the requirements, such as wide band spectrum, higher data rates, wider cell coverage etc., brought by next generation wireless communication systems mentioned above, OFDM and MIMO techniques are always considered key technologies of the physical layer. MIMO technology can significantly increase the transmission rate and link reliability of the communication systems without widening system bandwidth. As core branches of MIMO technique, precoding, detection and multi-user MIMO techniques have drawn considerable attention due to excellent performances.In this dissertation, MIMO system models, channel capacity of single-user MIMO and multi-user MIMO are introduced at first. Then key techniques related to single-user MIMO precoding and detection techniques, linear precoding techniques for the downlink of Multi-user MIMO system are studied. Detailed researches and major contributions of this dissertation are presented as follows:Considering precoding and detection techniques in single-user MIMO system, a new linear precoding scheme based on LQ decomposition is proposed, which can decode the transmit signal simplily by successive interference cancellation(SIC) at the receiver. The proposed precoding methods are given based on both ZF and MMSE criterion, adding the sorting operation to further improve system performance.For the problem of the QR decomposition detection algorithm which can not usually acquire perfect detection sequence at the receiver of the V-BLAST system(Vertical Bell Labs layered Space-Time), we derive the precoding matrix through the QR decomposition of the conjugate transpose of the channel matrix at the transmitter. The proposed scheme not only can explicitly get a perfect detection sequence when the SIC decoder is used at the receiver but aslo have been proven much more convenient to mitigate the error propagation. Compared to conventional decoder algorithms, the new scheme turns out to achieve better bit error rate (BER) performance with lower computational complexity.Due to high computational complexity for conventional linear precoding algorithms, it's not practical for downlink of Multi-user MIMO system. Therefore, three improved linear precoding algorithms are proposed, which can reduce the computational complexity effectively without notable performance loss. In addition, other two improved linear precoding algorithms are proposed in order to enhance the system performance effectively.Algorithm 1 (QR-BD) is a block digonolization precoding method which make use of QR decomposition to get the nullspace. The conventional BD algorithm has high computational complexity by using SVD decomposition to obtain the nullspace. The proposed algorithm utilizes the QR decomposition to get the nullspace instead of SVD, which get the same system perfomance with much lower computational complexity.Algorithm 1 (QR-BD) is a block digonolization precoding method which make use of the QR decomposition to get the nullspace. The conventional BD algorithm has a high computational complexity for using SVD to obtain the nullspace. The proposed algorithm utilizes the QR decomposition to get the nullspace instead of the SVD, which get the same system perfomance with much lower computational complexity.Both algorithm 2 and algorithm 3 are improved precoding methods by reducing the complexity of RBD algorithm (Regularized Block Digonolization). First, we obtain a useful conclusion via deriving the process of optimal solution from original RBD. The idea of channel extension which is regularly used in singleuser MIMO detection is spread to Multi-user MIMO system to contruct the precoding matrices in algorithm 2. A novel channel extension method is proposed including noise and the interference channel information from other users. Algorithm 2 utilizes QR decomposition to attain the space which minimizes the interference leakage and noise, referred to as QR-RBD algorithm. Furthermore, we prove that algorithm 2 is mathematically equivalent to original RBD but with considerably lower complexity. Algorithm 3 utilizes the cholesky factorization arithmetic to attain the space which minimizes the interference leakage and noise, referred to as CL-RBD algorithm. Algorithm 2 is also mathematically equivalent to original RBD, and its complexity is approximately equal to algorithm 2.Conventional channel inversion precoding algorithms only adapt to single receiver antenna scenarios. Hereby an improved channel inversion precoding algorithm based on MMSE criteria is presented which adds cooperation among multiple antennas on lower dimensions of uers' channel matrices to further suppress interference leakage and noise. Algorithm 4 imporves MMSE-CI algorithm so that it's suitable for scenarios with users possessing multiple receiver antennas. Theoretical analysis and simulation results show that the proposed algorithm achieves better system performance than original MMSE-CI algorithm with slight increment for complexity. Algorithm 5 is an iterative optimization precoding algorithm for Multi-user MIMO system. This Algorithm exploits unused subspaces of the already known users to boost space gain of other users. Porposed algorithm can greatly improve the system performance via optimal iterative method, whereas no impact on detection algorithm at the receiver and no increment for overhead are appended. In additio, the comparatively faster convergence ratio of proposed algorithm make it quite applicable to practical applications.