Optimized Payload Length and Power Allocation for Generalized Superimposed Pilot in URLLC Transmissions

• Published in: IEEE transactions on communications Vol. 72; no. 10; pp. 6073 - 6086
• Main Authors: Zhou, Xingguang, Zhu, Yongxu, Xia, Wenchao, Zhang, Jun, Wong, Kai-Kit
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Channel estimation; Closed form solutions; Exact solutions; finite blocklength; Iterative algorithms; Lower bounds; massive MIMO; Network latency; Optimization; Reliability; Resource management; superimposed pilot; Symmetric matrices; Transmission rate (communications); Ultra reliable low latency communication; Uplink; URLLC; Vectors; Wireless networks
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2024.3392806

Ultra-reliable and low-latency communication (URLLC) is recognized as the most challenging use case for the next generation of wireless networks. Existing research on URLLC is based on the regular pilot (RP) scheme, which is tough to ensure a high transmission rate with stringent latency and reliability requirements due to the impact of finite blocklength, especially in massive connectivity scenarios. In this paper, we propose to use generalized superimposed pilot (GSP) scheme for URLLC transmission in massive multi-input multi-output (mMIMO) systems. Distinguishing from the conventional superimposed pilot (SP) scheme, the GSP scheme eliminates mutual interference between the pilot and data, where the data length is optimized, and the data symbols are precoded to spread over the whole transmission block. With the GSP scheme, we first formulate a weighted sum rate maximization problem by jointly optimizing the data length, pilot power, and data power and then derive closed-form results, including suboptimal data length and achievable rate lower bounds with maximum-ratio combining (MRC) and zero-forcing (ZF) detectors, respectively. Based on the closed-form results, we provide the corresponding iterative algorithms for the MRC and ZF cases where the problems are transformed into geometry program format by using log-function and successive convex approximation methods. Finally, the performance of the RP, SP, and GSP schemes are compared through simulation results, which reflect the superiority and robustness of the GSP scheme in URLLC scenarios.