Interference Suppression Based On Base Station Coordination In Cellular System

To solve the growing conflicts between limited resources and increasing business requirements, MIMO technique which can significantly improve system capacity, has been widely concerned in recent years. However, in multi-antenna cellular systems, ICI seriously affects system performance improved by MIMO. BSC as key technology of 3GPP LTE and important branch of cooperative communication, can effectively suppress ICI, and improve spectral efficiency, under complex wireless communication environment. However, it is still facing many problems and challenges on its standardization and implementation. Therefore, the design of BSC system with lower complexity and higher performance, and researching fair and effective interference suppression technology are important topics.BSC usually has geographically separated antennas. Compared with convertional MIMO, it has many potential advantages, but also a lot of obstacles for its realization. First is how to select base statios to optimize system performance with lower complexity. Furthermore, in order to suppress ICI, large amount of information is exchanged between BSs, which brings serious burden to backhaul. In addition, there are inherent complexity problems or spatial freedom constrains for uplink and downlink interference suppression techniques. These issues are studied in this paper. We start from BSC capacity and its potential advantages, and focuses on coordinated clustering algorithms, uplink detection and downlink transimssion algorithms. These algorithms can effectively suppress ICI, improve spectral efficiency, while have positive significance for improving user fairness, reducing system complexity and backhaul cost. This paper mainly studies the following questions:Firstly, ICI and BSC model are studied. ICI model, mathematical solving of interference matrix, and performance of interference limited MIMO are given in a multi-cell environment. ICI can not be simply approximated as Gaussian white noise, and it has serious impact on the improvements of MIMO performance. Existing interference suppression algorithms are difficult to make new progress, so we can combine them with network-based coordinated algorithms. Then, Wyner model of BSC is researched, and its information theory performance is given, resulting in a theoretical capacity limit. Finally, advantages of BSC compared with conventional MIMO are discussed in terms of power gain, spatial correlation, channel rank and singular value distribution, and reasons of capacity gains caused by BSC are analyzed. These efforts contribute to deep understanding of principles of BSC, and have a certain significance and reference value for later research in this paper.Secondly, the choice of BS and clustering algorithm are studied. If all BS are involved in coordination, the overhead will be unbearable. Therefore, appropriate BSs should be selected to coordinate with each other. Base on advantages and disadvantages of static and dynamic clustering strategies, an improved static clustering strategy is proposed. Take uplink as an example, base on static clustering, users are divided into intra and inter cluster groups, according to inter-cluster coordinated distance. Zero forcing is applied to intra-cluster users to suppress multi-user interference. Combination of expanding zero forcing and successive interference cancellation is adopted to inter-cluster users to suppress inter-cluster interference. Compared with static clustering, improved strategy improves performance of cluster edge users, system spectral efficiency, and user fairness. Compared with dynamic clustering, performance is almost same, but it doesn't need greedy algorithm, so complexity can be significantly reduced.Thirdly, uplink coordinated detection is studied. In order to reduce feedback overhead caused by information exchang between BS and complexity of central processing unit, distributive coordinated detection is studied. To further reduce the cost, distributive detection based on user grouping is proposed. Users are divided into two groups, according to a threshold set by the ratio of local user channel gain and sum channel gain of all the users. Single cell processing is used to users above threshold, and interference from them is reconfigured. After eliminating interference from strong signals, LCD-DSD is used to users under threshold. Effective interference suppression can be achieved by separating strong and weak signals. Simulations show that when Th≈0.9, performance of only half number of users being coordinated detected is almost same with all users being coordinated detected, so backhaul burden and processing complexity can be greatly reduced.Fourthly, downlink coordinated transmission is studied. Several coordinated precoding is verified. JT-BD is excellent, and can effectively suppress ICI. But linear precoding has constraint of transmit antenna numbers, so two low complexity sub-optimal joint user and antenna selection algorithms are proposed base on BSC JT-BD. When system has less users, such as satifying precoding constraint, only antenna selection is used to remove antennas contribute less to capacity, while reduce interference to other users, which can improve system capacity. When the number of users is large, joint selection is adopted. While selecting users with less interference to maximize system capacity, mobile hardware complexity can be reduced, without large performance decreasing. Moreover, compared with users having equal receiving antennas without antenna selection, good performance gains still can be achieved.