摘要
在LTE-A中采用异构网络能提高用户的性能,但是由于小区间使用相同的频谱资源,产生了小区间干扰,影响了用户性能,从而需要采用小区间干扰协调技术来控制小区间干扰(ICI)。虽然现有的小区间干扰协调技术可以降低小区间干扰,但是存在Macro用户性能影响较大的问题。为此,提出了基于Q学习的ETPS算法,在不影响Macro用户性能的前提下,降低小区间干扰。仿真结果表明,QL-ETPS算法较传统固定ABS/RP-ABS子帧配置方案性能更优,可以在尽量不影响Macro基站用户的前提下,提高Pico基站边缘用户的吞吐量。
The heterogeneous network adopted by long-term evolution-advance （LTE-A） system can improve the user perfor- mance. The inter-cell interference （ICI） is generated and the user performance is influenced due to the shared frequency spec- trum among the inter-cells, so it is necessary to adopt the inter-cell interference coordination （IC） technology to control the ICI. Although the existing inter-cell interference coordination technology can reduce the ICI efficiently, but influence the Macro user performance greatly. To solve this problem, a Q-learning based enhance transmission power subframe （QL-ETPS） algorithm is pro- posed, which can reduce the ICI on the premise of ensuring the Macro user performance. The simulation results show that the per- formance of the proposed QL-ETPS algorithm is better than that of the conventional fixed ABS/RP-ABS configuration scheme, and can improve the throughput of the Pico base station edge user while ensuring the performance of Macro base station user.
出处
《现代电子技术》
北大核心
2016年第23期13-16,共4页
Modern Electronics Technique
基金
国家科技重大专项资助项目(2015ZX03004002)
