Uplink Signal Detection via Look-Up Table-Based AMP for Massive MIMO Systems
Uplink Signal Detection via Look-Up Table-Based AMP for Massive MIMO Systems
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DOI：
10.1109/access.2023.3242610
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发表时间：
2023
期刊：
影响因子：
3.9
通讯作者：
Atsunori Shimamura;Takumi Takahashi;S. Ibi;S. Sampei
中科院分区：
文献类型：
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作者：
Atsunori Shimamura;Takumi Takahashi;S. Ibi;S. Sampei
针对大规模多用户多输入多输出（MU-MIMO）系统中的上行链路信号检测问题，提出了一种基于查找表（LUT）的多用户检测（MUD）算法。当AMP采用双精度算法实现时，随着系统规模的扩大，功耗和处理延迟的急剧增加成为实际应用的主要障碍。为了规避这个问题，我们设计了一种新的参考AMP检测器组成的许多小LUT级联层次，其中只有信息的整数值的消息交换的因子图（FG）。我们的方法根据多层结构跟踪LUT输出的离散分布，并使用无监督学习方法连续确定LUT的非均匀量化阈值。具体地，在层级的每个级别处的阈值，即，层，通过聚类与k-means++方法给出的初始值，以最小化量化误差引起的性能下降的最大算法进行优化。数值模拟结果表明，该方法在各种信道模型下的误码率（BER）性能均优于最新的检测器（SotA），验证了该方法的有效性。结果还表明，参考AMP对无线信道的变化具有鲁棒性，并从算法结构上阐明了原因。
We propose a novel look-up table (LUT)-based multi-user detection (MUD) algorithm to imitate approximate message passing (AMP) for uplink signal detection in massive multi-user multi-input multi-output (MU-MIMO) systems. When AMP is implemented with double-precision arithmetic, the dramatic increase in power consumption and process latency becomes a major barrier to practical application, as the system scale expands. To circumvent this issue, we design a novel referential AMP detector composed of many small LUTs cascaded hierarchically, where only informative integer-valued messages are exchanged on a factor graph (FG). Our method tracks the discrete distribution of the LUT outputs according to the multi-layer structure, and successively determines non-uniform quantization thresholds of the LUTs, using an unsupervised learning approach. Specifically, the thresholds at each level of the hierarchy, i.e., layer, are optimized by clustering with the Lloyd-Max algorithm with initial values given by the k-means++ method, in order to minimize the performance degradation caused by quantization errors. The efficacy of the proposed referential AMP detector is confirmed by numerical simulations, which show that the proposed method significantly outperforms the state-of-the-art (SotA) in terms of the bit error rate (BER) performance in various channel models. The results also indicate the referential AMP is robust to changes in wireless channels, and then clarify the reason in terms of the algorithmic structure.