存在移动性和时延扩展时多前导码的低复杂度检测
Low-Complexity Detection of Multiple Preambles in the Presence of Mobility and Delay Spread
AI总结：
本文针对移动性和时延扩展下的多前导码检测问题，基于ZC序列和Zak-OTFS构建前导码，将检测建模为压缩感知问题，提出一种复杂度为O(M²N²)的低复杂度检测算法，适配5G免授权随机接入需求。
摘要：
当前无线基础设施针对支持下行链路应用进行了优化。本文预判了工程重点从下行链路上行链路转移的应用场景的出现。当前在预留的上行链路资源上调度用户的范式无法有效应对不可预测的流量模式。因此，3GPP引入了2步RACH（随机接入信道）作为实现免授权（随机）初始接入的机制。这两个步骤中的第一步是RACH时隙中的前导码检测，本文提出了一种在存在移动性和时延扩展的情况下同时检测多个前导码的低复杂度算法。我们选择ZC序列作为前导码，为该方案纳入标准提供了路径，因为ZC序列已出现在5G标准中。我们通过离散Zak变换将时域（TD）中长度为MN的ZC序列转换为延迟-多普勒（DD）域中的准周期M×N阵列，以此构建前导码。序列中存在MN个准周期狄拉克脉冲，每个脉冲对应一个Zak-OTFS（Zak变换正交时频空）载波波形，而ZC前导码就是这些Zak-OTFS载波波形的对应和。我们通过在DD域的M×N周期网格上对接收信号进行采样，来在存在移动性和时延扩展的情况下检测多个前导码。我们将检测问题建模为压缩感知问题。我们将一个前导码表示为DD域中长度为MN的列向量，并通过时延和多普勒域的离散移位生成压缩感知矩阵中具有O(MN)列的一个块。多个前导码的叠加对应感知矩阵中列的块稀疏和。ZC序列的相关特性使得压缩感知矩阵具有高度结构化的特点，因此可以使用OST（正交匹配追踪类算法，原文为OST，按要求保留）识别组成前导码，其复杂度为O(M³N³)。在本文中，我们提出了一种算法，其相对于单个列的规模的复杂度为O(M²N²)。
英文摘要：
Current wireless infrastructure is optimized to support downlink applications. This paper anticipates the emergence of applications where engineering focus shifts from downlink to uplink. The current paradigm of scheduling users on reserved uplink resources is not able to deal efficiently with unpredictable traffic patterns. As a result, 3GPP introduced the 2-step RACH as a mechanism to enable grant-free (random) initial access. The first of the two steps is preamble detection in a RACH slot, and in this paper we describe a low-complexity algorithm for simultaneous detection of multiple preambles in the presence of mobility and delay spread. We provide a pathway to standards adoption by choosing ZC sequences as preambles, as ZC sequences already appear in 5G standards. We construct preambles by using the discrete Zak transform to pass from a ZC sequence of length MN in the TD to a quasi-periodic MxN array in the DD domain. There are MN quasi-periodic Dirac pulses, each corresponding to a Zak-OTFS carrier waveform, and the ZC preamble is simply the corresponding sum of Zak-OTFS carrier waveforms. We detect multiple preambles in the presence of mobility and delay spread by sampling the received signal on the MxN period grid in the DD domain. We approach detection as a compressed sensing problem. We represent a preamble as a column of length MN in the DD domain and apply discrete shifts in delay and Doppler to produce a block with O(MN) columns in the compressed sensing matrix. The superposition of multiple preambles determines a block sparse sum of columns in the sensing matrix. The correlation properties of ZC sequences result in a highly structured compressed sensing matrix, making it possible to identify constituent preambles using OST, which has complexity O(M^3N^3). In this paper, we describe an algorithm with complexity that is O(M^2N^2) in the size of an individual column.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
