下一代大规模设备的URLLC：源和非源随机接入的统一半盲检测框架
Next-Generation URLLC with Massive Devices: A Unified Semi-Blind Detection Framework for Sourced and Unsourced Random Access
摘要：
本文提出了一个统一的半盲检测框架的源和无源随机接入（RA），使下一代超可靠的低延迟通信（URLLC）的大规模设备。具体地，有源设备以免授权方式发送其上行接入信号，以实现超低接入时延。同时，基站的目标是在严重的设备间干扰下实现超可靠的数据检测，而不利用显式信道状态信息（CSI）。我们首先提出了一种高效的发射机设计，其中将少量参考信息（RI）嵌入到接入信号中，以解决未知CSI引起的固有模糊性。在接收端，我们进一步开发了一种基于连续干扰消除的半盲检测方案，其中双线性广义近似消息传递算法用于联合信道和信号估计（JCSE），而嵌入式RI用于消除模糊。特别地，秩选择方法和RI辅助的初始化策略被纳入，以降低算法的计算复杂性和提高JCSE的可靠性，分别。此外，四个使能技术的集成，以满足严格的延迟和可靠性要求的大规模URLLC。数值结果表明，所提出的半盲检测框架提供了一个更好的可扩展性-延迟-可靠性权衡比国家的最先进的检测方案专用于源或无源RA。
英文摘要：
This paper proposes a unified semi-blind detection framework for sourced and unsourced random access (RA), which enables next-generation ultra-reliable low-latency communications (URLLC) with massive devices. Specifically, the active devices transmit their uplink access signals in a grant-free manner to realize ultra-low access latency. Meanwhile, the base station aims to achieve ultra-reliable data detection under severe inter-device interference without exploiting explicit channel state information (CSI). We first propose an efficient transmitter design, where a small amount of reference information (RI) is embedded in the access signal to resolve the inherent ambiguities incurred by the unknown CSI. At the receiver, we further develop a successive interference cancellation-based semi-blind detection scheme, where a bilinear generalized approximate message passing algorithm is utilized for joint channel and signal estimation (JCSE), while the embedded RI is exploited for ambiguity elimination. Particularly, a rank selection approach and a RI-aided initialization strategy are incorporated to reduce the algorithmic computational complexity and to enhance the JCSE reliability, respectively. Besides, four enabling techniques are integrated to satisfy the stringent latency and reliability requirements of massive URLLC. Numerical results demonstrate that the proposed semi-blind detection framework offers a better scalability-latency-reliability tradeoff than the state-of-the-art detection schemes dedicated to sourced or unsourced RA.
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。
