针对短突发通信系统存在的频偏估计相位模糊问题,本文提出了一种宽范围低复杂度的时域相关频偏估计算法——基于相位解模糊的部分互相关算法.该算法利用自相关算法思想和相关代数知识消除了其复乘运算,再利用基于蒙特卡罗仿真的解相位模糊算法解决了其相位模糊问题,从而适应大频偏下的短突发通信环境.最后仿真结果表明,与经典的M&M、AC和Giugno时域算法相比,在保证了较大估计范围的同时,该算法具有更高的估计精度和更低的复杂度,适用于低时延高可靠的短数据包传输.
Abstract
Considering the phase ambiguity problem of frequency offset estimation existed in the short-burst communication, this paper proposes a wide-range low-complexity time-domain correlation frequency offset estimation algorithm-phase-unwrapping based partial cross-correlation algorithm. This algorithm uses the idea of the autocorrelation algorithm and knowledge of the algebra to eliminate its complex multiplication operation, and then utilizes a Monte-Carlo simulation based phase-unwrapping algorithm to solve the problem of phase ambiguity, thus suitable for the short burst communication environment with large frequency offsets. Simulation results show that when maintaining large estimation range, the proposed algorithm also exhibits both higher accuracy and lower complexity than the classical M&M, AC, and Giugno algorithms, thus suitable for low-latency high-reliability short packet transmission.
关键词
时域相关 /
相位模糊 /
频偏估计 /
蒙特卡洛仿真 /
无人机通信 /
短突发通信
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Key words
time-domain correlation /
phase ambiguity /
frequency offset estimation /
Monte-Carlo simulation /
UAV communication /
short-burst communication
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中图分类号:
TP911.23
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脚注
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基金
国家自然科学基金 (No.61801527,No.61702071); 河南省高等学校重点科研项目 (No.19A510028); 河南省科技厅科技发展计划项目 (No.182102210152,No.182102310867,No.192102210279)
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