发表机构
Communications and Information Theory Chair, Faculty of Electrical Engineering and Computer Science, Technische Universität Berlin（柏林工业大学电气与计算机科学学院通信与信息论讲席）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对无小区用户中心网络，提出基于位置相关码本的随机接入方案，结合ZC序列与GLRT或AMP检测，并利用近最大似然方法实现用户定位，仿真验证了AMP检测性能更优且定位精度相当。
AI 中文摘要
在无线网络中，初始/随机接入机制（RACH）允许空闲或新用户加入网络，并（可能）请求为后续流量分配传输资源。基于我们之前的工作，针对无小区用户中心网络，我们考虑与位置相关的随机接入码本，使得特定地理区域（位置）内的用户使用相应的随机接入前导码（码字）集合。我们在两个方面扩展了之前的工作：（1）我们考虑在给定半径内具有视距（LoS）传播的多径信道；（2）我们考虑两种不同的方法。第一种方法利用Zadoff-Chu（ZC）序列和GLRT检测来应对未知时延，其在概念上类似于3GPP两步RACH规范（此处扩展到无小区场景）。第二种方法基于我们之前关于多源近似消息传递（AMP）的工作。对于这两种方案，我们还考虑了一种新颖的近最大似然方法，直接从检测到的RACH前导码中对随机接入用户进行定位，隐式利用嵌入在LoS分量中的到达角和到达时间差信息。仿真结果表明，AMP方法在随机接入用户检测方面通常取得更好的性能，而两种方法在定位能力上相似，但频域方案略有优势。
英文摘要
In a wireless network, the initial/random access mechanism (RACH) allows idle/new users to join the network and (possibly) request allocated transmission resources for subsequent traffic. Building on our own previous work, for cell-free user-centric networks, we consider location-dependent random access codebooks such that users in a certain geographic area (location) make use of the corresponding set of random access preambles (codewords). We expand our previous work in two ways: (1) we consider multipath channels with line-of-sight (LoS) propagation within a given radius; (2) we consider two different approaches. The first makes use of Zadoff-Chu (ZC) sequences and GLRT detection to cope with the unknown delay, and it is conceptually similar to the 3GPP 2-step RACH specification (here extended to the cell-free case). The second builds on our previous work on multisource approximate message passing (AMP). For both schemes, we also consider a novel near Maximum-Likelihood approach for localization of the random access users directly from the detected RACH preambles, implicitly using angle of arrival and time difference of arrival information embedded into the LoS components. Simulation results show that the AMP approach achieves generally better performance for random access user detection, while both approaches have similar localization capability with a slight superiority for the frequency-domain scheme.
