Research About Uplink And Downlink Algorithms In Large-Scale Distributed-MIMO Systems

The increasing demands of people surfing on the Internet, future mobile wireless communication system provides network service including real-time stream business, high-rate multi-media and high-speed multi-media business. And this will be affected and limited by the system's power, bandwidth and algorithm complexity. Thus, high-rate and high-throughput communication technique will be the key of the future's wireless communications.Among which, Distributed MIMO will be one of the key technique of 5G wireless communication. Many Radio access ports are widely distributed in an area around a base station. There are hundreds of antennas in the base station and there are also many antennas configured in the radio access port for aid of transmitting and receiving signal. Distributed MIMO combines the advantage of point-to-point MIMO and distributed antennas.It can greatly increase the speed of data transmission and improve the Spectrum efficiency, and at the same time taking advantage of distributed antennas thus getting the macro-diversity gains and complexity gains.This article did a series of research about Distributed MIMO on the communication link between the central base station and the wireless radio ports.Firstly, we reviewed some classical transmitting and receiving technique in MIMO system.Secondly, we discussed about the performance via k fading channel in the Distributed MIMO System. Specifically, we used the analytical capacity and proposed the ergodic capacity when the antennas of the base station grow infinitely. Taking advantage of the results above, we studied about the energy efficiency. Simulations show the joint-search algorithm could get the same energy efficiency with exhaustive searching however the complexity of the algorithm is much better. Based on the principal of energy efficiency maximization, we could get the system configuration such as the count of antennas, the corresponding energy efficiency and spectrum efficiency.Thirdly, we proposed a low-complexity QR decomposition self-adapted pre-coding algorithm based on RBD. When one or more user's channel change, it will re-compute the QR decomposition or not according to the relation between the antennas in base station and wireless radio ports.Using the stored QR matrix, it can reduce the complexity. This algorithm could reduce the complexity of pre-coding without affecting system capacity and byte error rate.Finally, we conclude this article's future development and process,and propose future study according to current shortcuts.