Research On Coordinated Interference Processing In Downlink MIMO Transmission

The burgeoning growth of internet data tsunami is mostly caused by the popularization of diversified mobile equipment, deployment of the internet of things, multimedia application on the mobile internet, and mo-bile wireless broadband access. Therefore, wireless communication sys-tem in the future should be capable of achieving the reliable communica-tion, as well as high transmission rate, short transmission delay, and wide network coverage across large geographic field. It is in great urgency of increasing the spectrum efficiency through research in terms of network architecture, resource allocation and distributive signal processing.The trend in wireless network development renders the interference a fundamental bottleneck of performance improvement, and base station cooperation is considered to be one of the most promising technologies to solve this issue. Consequently, interference processing based on base sta-tion cooperation is of high theoretical value and broad application pro-spects.From the viewpoints of resource allocation and network architecture, we investigate the adaptive interference coordination through beamform-ing, power control and base station clustering in this dissertation. Four research outcomes are concluded as follows.Firstly, effectively managing the leakage power is investigated in the beamforming design through maximizing the signal to leakage plus noise ratio (SLNR). A weighted SLNR is proposed and power control algorithm is developed to guarantee the fairness among all users. In the classical beamforming design based on the SLNR maximization, the leakage pow-er may cause more damage to the user whose channel quality is relatively poorer. Through introducing the weight coefficients into the SLNR ex-pression, the leakage power is effectively and fairly distributed among other users. Moreover, we take the ambiguity of channel state infor-mations (CSI) into consideration to improve the robustness of proposed algorithm. Finally, a power control algorithm is proposed based on the weighted SLNR with information about the unideal CSI.Secondly, under the constraint of backhaul capacity and overhead signal, we investigate the beamforming design and power control based on the local CSI. After building the sum capacity maximization problem with the constraint of per-base peak transmission power, the domain of transmission power is discretized to restrict the searching space. Thereaf-ter, a beamforming design is proposed based on the local CSI and power control algorithm is developed according to the greedy criterion. Simula-tion results demonstrate that the proposed scheme can achieve high spec-trum efficiency at the cost of low computation complexity while guaran-teeing the fairness among all users. This proposed scheme provides a reasonable framework to handle the interference by beamforming and power control.Thirdly, base station clustering is studied in the limitedly coordinat-ed network. We propose a new dynamic clustering algorithm based on the predefined connectivity graph and heuristic utility function. The sum ca-pacity maximization problem is firstly formulated under the constraints of per-base transmission power and base station clustering. By mapping the base station and the cooperation relationship to the vertices and edges in the graph, the set of searching path for clustering algorithm is reduced. A heuristic function based on the sum of statistical interference channel gain is proposed to weight those edges representing the possibility of base sta-tion cooperation. Simulation results illustrate that the proposed scheme can achieve a relative good performance at low computation-al-complexity while characterizing the robustness against the imperfect CSI.Finally, interference processing is completed by joint design of base station clustering and beamforming vector. We propose a unified inter-ference coordination framework on the basis of leakage power. After in- troducing the concept of leakage channel station information, the mathe-matical meaning for the sum of leakage power is analyzed from the view of several base stations acting as the whole cluster. Subsequently, most of the inter-cell interference is transformed into the intra-cluster interference by the criterion of maximizing the sum of leakage power from different base stations. This intra-cluster interference is then suppressed by the clustered beamforming vector designed through SLNR maximization. Simulation results show that the proposed scheme compromises its com-putational-complexity and the performance in terms of average user ca-pacity and cell edge user capacity. Moreover, the proposed method pro-vides a better predefined outage probability than the optimal base clus-tering algorithm.