Wirelee Resource Scheduling Algorithm In TD-LTE System

In order to maintain the competition in the wireless communication field, meet the challenge of the wideband access techniques and the new services,3GPP started the standardization of Long Term Evolution (LTE) in 2004. LTE can support both the FDD and TDD modes. In our country, TD-LTE is adopted as the long term evolution of TD-SCDMA.The features of TD-LTE system, such as using time and frequency as resource blocks for allocation, and flexible configuration of the uplink and downlink timeslots, make its resource scheduling rather different from that of the traditional wireless communication system. Especially when MIMO (Multiple-Input Multiple-Out-put) technique was introduced to increase the peak rate (uplink 50Mb/s and downlink 100Mb/s), the concept of Resources Pool has been expanded, so resource scheduling becomes more complicated with joint processing of the time, frequency and space domain.Firstly, we introduce the characteristics of TD-LTE system, classic resource scheduling algorithms and also the basic principles, functions and modules of the TD-LTE System level simulation platform.Then we discuss the CQI feedback model and MCS selection procedure in the TD-LTE downlink system with single-antenna configuration. For the restriction on resource scheduling with single antenna configuration, we proposes a Common MCS selection algorithm——3-steps MCS selection algorithm. Simulation results show that the 3-steps MCS selection procedure can effectively solve the restriction on MCS selection, and the best-M reporting scheme can make a good tradeoff between the uplink overhead and downlink throughput. And also we find that Best M schemeⅡcan make better performance in high speed scenar(?)o.Finally, we introduce the multi-antenna model and analyze the performance of the resource scheduling algorithm for the multi-antenna based downlink TD-LTE system. Simulation results show that multi-antenna technique can effectively improve the system spectrum efficiency, and the rank adaptive algorithm can improve the throughput of edge users at the indoor hotspot and the macro scenarios while maintaining the performance of the whole system.