Sparse Activity, Timing Detection and Channel Estimation for Grant-Free Uplink Communications
Sparse Activity, Timing Detection and Channel Estimation for Grant-Free Uplink Communications
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DOI：
10.1109/pimrc48278.2020.9217319
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发表时间：
2020-08
期刊：
影响因子：
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通讯作者：
Chu-Tung Liu;Hsuan-Jung Su;Yasuhiro Takano
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文献类型：
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作者：
Chu-Tung Liu;Hsuan-Jung Su;Yasuhiro Takano
本文考虑了一种免授权上行链路的情况下，用户活动（UA），定时偏移（TO），和信道状态信息（CSI）的用户设备（UE）是未知的服务基站（BS）。在这种情况下，潜在UE的数量很大，而只有少数UE是活动的。由于UA的稀疏性，提出了一种使用近似消息传递（AMP）的检测算法，一种压缩感知（CS）算法，以恢复UA，TO和CSI。该算法将异步系统映射到一个虚拟系统上，并将AMP应用于该虚拟系统，在AMP收敛后，为了最小化检测错误概率，推导并利用贝叶斯检验。此外，状态演化（SE）的虚拟系统进行分析，预测所提出的算法的性能。仿真结果表明，当导频符号数足够大时，该算法可以获得与理想同步系统相同的检测错误概率和信道估计误差。分析结果表明，SE能够预测所需的最小数目的导频符号，以达到所需的检测错误概率，并预测性能时，导频符号的数量是大的。
This paper considers a grant-free uplink scenario in which the user activity (UA), the timing offsets (TOs), and the channel state information (CSI) of user equipments (UEs) are unknown to the serving base station (BS). In this scenario, the number of potential UEs is large while only a few UEs are active. Due to the sparse nature of the UA, a detection algorithm using approximate message passing (AMP), a compressed sensing (CS) algorithm, is proposed to recover the UA, TOs, and CSI. The proposed algorithm maps the asynchronous system to a virtual system and applies AMP to it. After AMP converges, to minimize the detection error probability, a Bayes test is derived and utilized. Besides, state evolution (SE) analysis is conducted on the virtual system to predict the performance of the proposed algorithm. Simulation results show that when the number of pilot symbols is large enough, the proposed algorithm can achieve the same detection error probability and channel estimation error as those of an ideal system in which the UEs are synchronized. Analytical results show that SE is able to predict the minimum number of pilot symbols needed to achieve a required detection error probability, and predict the performance when the number of pilot symbols is large.