Research On The User Scheduling Strategies In Multi-cell Multi-user System

In order to satisfy all kinds of service need, resource allocation techniques are designed to allocate limited resource to users intelligently. Compared to static allocation, the dynamic approach based on channel state information (CSI) has better system performance.In this dissertation, we study user scheduling techniques in the multi-cell multi-user context from two perspectives. The first one is distributed Power Matched Scheduling policy, which can be utilized for the service requiring a few signaling overhead in fast fading environment. This scheme, with limited degrees of freedom, is used to allocate system resource to the most efficient users. So it can maximize the network capacity in an interference-limited setting, giving consideration of both resource fairness and multi-user diversity gain. The theoretical derivation and simulation results prove that it can approach the theoretical maximum value of system capacity. The second one is a coordinated scheduling algorithm, which can be used to provide non-instantaneous service with a large amount of data. In order to alleviate Co-Channel Interference (CCI) and maximize the system capacity, this scheduling strategy can be considered as an optimization problem. Particle Swarm Optimization (PSO) can easily solve the problem. This paper proposes a scheduling strategy by means of PSO. With the current CSI of every user in the cell cluster, Zero-Forcing (ZF) precoding algorithm is employed to cancel CCI. PSO is used to select the users group, so as to achieve multi-user diversity gain and maximize the system capacity. The simulation results show that in terms of system capacity, the performance of scheduling strategy based on PSO which has much lower complexity, is almost as good as the optimal exhaustive search (ES). Key words: multi-cell multi-user, coordinated scheduling, Power Matched Scheduling (PMS), Particle Swarm Optimization (PSO), network capacity...