Radio Resource and Interference Management in Uplink MU-MIMO Systems with ZF Post-processing
This dissertation investigates cross-layer designs in spatial division multiplexing (SDM) for multiuser multiple-input multiple-output (MU-MIMO) transmissions on the uplink. The MU systems which allow simultaneous transmissions on the downlink offer various improvements, such as an increase in total system throughput, and have already been standardized in IEEE 802.11ac wireless local area networks (WLANs) and cellular networks. However, the implementation of MU-MIMO SDM on the uplink is still considered to be an open problem. The challenges include radio resource management and low complexity decoding designs. Motivated by these considerations, this dissertation presents four main contributions. First, this research focuses on the physical layer MU-MIMO issues by proposing an uplink approach that employs a design with low complexity, while maintaining an acceptable sum rate performance. This is done by utilizing zero forcing (ZF) cancellation, and by assuming that channel state information (CSI) is required only at the base station (BS). In addition, spatial coordination is applied to improve the total system performance by giving medium access to a limited number of transmitters. Secondly, two resource management algorithms are developed with the objective of maximizing the total system sum rate by considering the impact of multiple access noise enhancement on the spatial stream capacity. An additional scheme is then proposed to maximize the weighted sum capacity of all admitted users, where the weights are chosen based on the state of user buffers. The proposed resource allocation and scheduling algorithms operate in a reduced search space for sub-optimum configurations targeting lower overall complexity. Thirdly, two-layer decoding is proposed in a multi-cell environment for MU-MIMO systems. The first layer of decoding handles multiple access interference (MAI) by applying the ZF approach, where this process is executed at the BS level. The second layer utilizes a diversity combining technique on a selected number of mobile stations (MS), with the aim of reducing inter-cell interference (ICI). Finally, an interference-aware joint scheduling algorithm is presented for the multi-cell MU-MIMO system. This algorithm focuses on selecting users/antennas, and utilizes power allocation to improve the total system performance. Spatial coordination is executed in a distributive manner with full independence from the power allocation, in order to reduce the search time. Moreover, Newton's method of optimization is included to find the optimum power level for all transmitting users. This dissertation advances MU-MIMO system designs for the uplink by contributing to the development of interference and radio resource management algorithms. The motivation of this work is to propose a low complexity design that reduces the level of interference while providing good overall system performance as measured by the total sum rate. The results presented in this work are applicable to wireless networks such as WLANs that can operate with a single autonomous access point (AP) as well as coordinated APs that are managed by centralized controllers.