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

Authors :
Ghanem, Walid R.
Jamali, Vahid
Sun, Yan
Schober, Robert
Source :
IEEE Transactions on Communications. Nov2020, Vol. 68 Issue 11, p7184-7200. 17p.
Publication Year :
2020

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00906778
Volume :
68
Issue :
11
Database :
Academic Search Index
Journal :
IEEE Transactions on Communications
Publication Type :
Academic Journal
Accession number :
147133746
Full Text :
https://doi.org/10.1109/TCOMM.2020.3017757