Resource Allocation for Multi-User Downlink MISO OFDMA-URLLC Systems

• Published in: IEEE transactions on communications Vol. 68; no. 11; pp. 7184 - 7200
• Main Authors: Ghanem, Walid R., Jamali, Vahid, Sun, Yan, Schober, Robert
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-11-2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation algorithms; Complexity; Computational geometry; Convexity; Delay; Delays; Design optimization; Downlink; Downlinking; Frequency division multiple access; Mathematical programming; MISO (control systems); MISO communication; monotonic optimization; Network latency; orthogonal frequency division multiple access (OFDMA); Orthogonal Frequency Division Multiplexing; Packet transmission; Quality of service; Resource allocation; Resource management; short packet transmission; Ultra reliable low latency communication; ultra-reliable low latency communication (URLLC); Upper bounds
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2020.3017757

This article considers the resource allocation algorithm design for downlink multiple-input single-output (MISO) orthogonal frequency division multiple access (OFDMA) ultra-reliable low latency communication (URLLC) systems. To meet the stringent delay requirements of URLLC, short packet transmission is adopted and taken into account for resource allocation algorithm design. The resource allocation is optimized for maximization of the weighted system sum throughput subject to quality-of-service (QoS) constraints regarding the URLLC users' number of transmitted bits, packet error probability, and delay. Despite the non-convexity of the resulting optimization problem, the optimal solution is found via monotonic optimization. The corresponding optimal resource allocation policy can serve as a performance upper bound for sub-optimal low-complexity solutions. We develop such a low-complexity sub-optimal resource allocation algorithm based on successive convex approximation and difference of convex programming. Our simulation results reveal the importance of using multiple antennas for reducing the latency and improving the reliability of URLLC systems. Moreover, the proposed sub-optimal algorithm is shown to closely approach the performance of the proposed optimal algorithm and outperforms two baseline schemes by a considerable margin, especially when the users have heterogeneous delay requirements. Finally, conventional resource allocation designs based on Shannon's capacity formula are shown to be not applicable in MISO OFDMA-URLLC systems as they are not able to guarantee the users' delay constraints.