Algorithm Designing And Performance Evaluation For Radio Resource Self-Optimization In TD-LTE-Advanced

The radio resource self-optimization technique through adaptively adjusting the configuration parameters or related resource management strategies of base stations and other network equipment can enhance coverage, improve system capacity, reduced power consumption, optimize handover, etc, so it is widely studied. While in order to improve spectral efficiency, algorithms should be studied in different scenarios, especially in heterogeneous networks. This paper studies the TD-LTE-Advanced system radio resource self-optimization techniques. Based on the existing standard protocols and academic achievements, the algorithms of improvement of radio resource optimization are studied. Then through the dynamic system-level simulation detailed performance analysis and application scenarios are given. The main works are listed below:(1) Proposed joint enhanced inter-cell interference coordination and cell coverage expansion optimization algorithm;This algorithm calculates the resource requirements and channel capacity of macro-eNBs (evolved Node B) and pico-eNBs, and then dynamically adjusts muting ratio and CRE (Cell Range Extension) bias value. For the different distribution of network load, both centralized and distributed algorithms are proposed. Dynamic system-level simulation results show that both algorithms at different load distributions can make the average cell throughput increased by9%or more, up to41.6%; cell edge user throughput increased by10.2%or more, up to144.2%.(2)Proposed MLB (Mobility Load Balance) algorithm;According to real-time changes in the network load, this algorithm can switch the users with poor channel quality from heavy load cell to surrounding light load cell, improving light load cell resource utilization. Dynamic system-level simulation results show that the algorithm can increase the cell edge user throughput16.7%in homogeneous networks and26.1%in heterogeneous networks without cell average throughput decreasing.(3)Proposed MRO (Mobility Robustness Optimization) algorithm;The algorithm can dynamically adjust the time to trigger and other information in order to optimize system performance parameters. Dynamic system-level simulation shows that the algorithm can make the call drop ratio decreased from8.6%to3.5%in homogeneous networks and from17.9%to8.1%in heterogeneous networks.