On Transmission Techniques For Multiuser Downlink MIMO Systems

In recent years, with the growing of internet and multimedia applications inwireless networks, the booming demand for wideband high data rates communicationservices is growing quikly. The next generation of mobile communications shouldprovide users with higher data transfer rates and better quality of service. Multiple inputmultiple output (MIMO) techniques make such requirements possible. MIMO systemuses multiple antennas at the transmitter and receiver to obtain spatial diversity andmultiplexing gains. MIMO technology can increase the system capacity, enhance thetransmission link reliability, and improve the spectrum efficiency. Currently, the point topoint single-user MIMO system research has matured, and multiuser MIMO system hasbeen one of the most widely explored topics in wireless communications over the pastfew years. Multiuser MIMO system has many advantages: the multi-antenna diversitygain can improve bit error rate performance, the multi-antenna multiplexing gain canincrease the system throughput, and the multi-directional antenna gain can distinguishdifferent located users, thereby eliminating interference between users.Therefore, thisthesis investigates the precoding design, user scheduling and antenna selection formultiuser MIMO downlink systems. Specifically, the main contributions of this thesisare summarized as follows:1. In the research of the precoding design for multiuser MIMO downlink systems,I) According to the analysis of the typical precoding methods for multiuser MIMOdownlink systems, a multiuser iterative precoding algorithm is proposed, whichis based on matching weighted signal-to-leakage-and-noise ratio (MSLNR)criterion. In the proposed algorithm, the effective channel gain of each user isselected as the matching weighted factor, and the leakage power received byeach user is weighted by the factor. An exact closed form solution for theprecoding vector is obtained by maximizing the WSLNR, and then optimized byusing an iterative optimization approach. The proposed precoding design schemedoes not impose a restriction on the available system antennas configuration,and simulation results show that the proposed scheme can improve the sumcapacity of the system.II) For cognitive radio (CR) multiuser MIMO downlink systems, according to thejoint block diagonalization (BD) algorithm and the MSLNR based algorithm, theCR-BD-MSLNR precoding scheme is proposed. The CR-BD-MSLNRprecoding scheme uses a two-level precoding scheme on the basis of the different priorities when the primary user (PU) and cognitive users (CU) occupyauthorized spectrum. In the first level precoding, for guaranting the PU’scommunication quality, the BD algorithm is adopted to force PU’s precodingmatrix to lie in the null space of interference channel matrix. Thus theco-channel interference from the cognitive user base station (CBS) to the PUcould be removed completely. In the second level precoding, the MSLNR basedalgorithm is adopted to mitigate interference between CUs and improve capacityfor CUs. Simulation results show that the proposed scheme can eliminate theco-channel interference from the CBS to the PU completely and achieve highsum capacity for CUs.2. In the research of the user scheduling for multiuser MIMO downlink systems,I) We propose a low complexity and suboptimal user scheduling algorithm basedon block diagonalization scheme. The proposed user scheduling algorithm uses astrong tight upper bound of sum capacity as selection metric, and thepreliminary selected user set is obtained according to greedy search method.Then a one-for-one substitution operation is employed to modify the preliminaryselected user set, which can mitigate the effect of the local optimum problem toa certain extent. Computer simulations show that the proposed algorithm bothmaintains the low-complexity feature of the capacity upper bound basedalgorithm and obtains higher sum capacity than the capacity based algorithm.That is to say, the proposed algorithm achieves a good trade-off between sumcapacity performance and computational complexity.II) By building the energy-efficient user scheduling model for multiuser MIMOdownlink systems, an low complexity energy-efficient user scheduling scheme isproposed. The proposed user scheduling scheme aims to maximize the largestaggregate channel matrix volume on the basis of greedy search method. In eachuser selection step, the scheme chooses the user that provides the the largestaggregate channel matrix volume with the already selected users. Then theenergy efficiency is maximized by optimizing the transmit power. Furthermore,by taking into account the problem of maintaining fairness among users, asimplified proportional fair scheduling algorithm is also proposed.3. In the research of the antenna selection for massive MIMO systems, an energyefficient antenna selection scheme is proposed. We first derive a goodapproximation of the expression for the sum capacity in the antenna selectionsystem. By building the energy-efficient antenna selection model for massive MIMO systems, we analyze the relationship between energy efficiency andselected antenna number in detail, and determine the optimum antenna number.Then the antenna selection strategy is presented. All the analytical results areverified through computer simulations.