Research On Precoding For Cooperative Multi-cell MIMO Channels

In a wireless network of high density, the interference problem is akey factor restricting thesystem capacity. Inter-cell interference (ICI) is treated as noise in single-cell techniques. However,cooperative multi-cell technology can use ICI to improve system performance by cooperationamong base stations. Distributed precoding method is a more practical solution to solve thisproblem without sharing the global CSI and the users’ data. Distributed MIMO precoding includestwo basic strategies: received interference-aware precoding (RIAP), generated interference-awareprecoding (GIAP).Firstly, some interference mitigating methods anddownlink capacity performance incooperative multi-cell MIMO system are analyzed. The capacity performance of MCP system andSCP system using different frequency reuse factorsare compared. The simulation result shows thatcooperative processing canimprove the system capacity performance.Secondly, RIAP and GIAP schemes are analyzed in detail. The standard expressions, thehybrid precoding scheme, and a switching scheme of RIAP and GIAP are explained through theintroduction of some effective channel matrices. The performance of both RIAP and GIAP areanalyzedand simulated in a multi-cell scenario. The simulation results show that the switchingscheme in this chapter is effective and efficient.Finally, a distributed virtual SINR framework based on the uplink and downlink duality theoryis analyzed to design DVSINR precoding scheme and aoptimal power allocation scheme is used toenhance DVSINR precoding performance. DVSINR precodingis proved able to obtain optimalmultiplexing gain. Numerical simulations under a variety of scenarios show that DVSINRprecoding scheme has a superior performance than distributed MRT and ZFprecoding at all SNRconditions. So it can be concluded that DVSINR precoding scheme is more practical and effectivethan other precoding schemes.