小小区发现中基于能量变化的时偏估计算法

Timing-Offset Estimation Algorithm based on Energy Variations in Discovery of Small Cells

伴随着智能终端的普及,数据流量呈现爆炸式增长,小小区密集部署成为解决这类问题的潜在方案。但是,这会导致异构网络中小小区区间干扰愈发严重,使得快速有效地发现小小区越来越困难。从发现精度的角度考虑,研究现有PSS自相关时偏估计算法、最小二乘时偏估计算法、能量变化时偏估计算法,提出基于能量变化的时偏估计算法改进方案,搭建了小小区发现仿真平台,仿真验证了该算法能够在低SNR和多径信道下实现很好的估计性能。

With the popularity of the intelligent terminal, data traffic shows the trend of explosive growth, and dense deployment of small cells becomes a potential solution to such problem. The presence of small cell interference in heterogeneous networks is increasingly severe, and thus the efficient and quick discovery of small ceils becomes even more difficult. From the angle of discovery accuracy, the existing time offset estimation algorithms, including PSS autocorrelation, least squares algorithm, energy variation are studied, and the modified scheme based on energy variation is proposed, and the simulation platform for small-cell discovery built up. Simulation results show that the proposed algorithm has good performance under low SNR and multipath conditions.