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Resource allocation in millimeter-wave multicarrier-division duplex systems with hybrid beamforming

Resource allocation in millimeter-wave multicarrier-division duplex systems with hybrid beamforming
Resource allocation in millimeter-wave multicarrier-division duplex systems with hybrid beamforming

In-band full-duplex (IBFD) systems require promising resource allocation (RA) strategies to fully exploit the available time-frequency resources. Furthermore, the acquisition of channel state information and signal reception in IBFD systems are significantly impacted by insufficient self-interference cancellation (SIC), impeding the applications of IBFD in practical wireless systems. Multicarrier-division duplex (MDD), which benefits low-budget SI mitigation in digital domain and flexible subcarrier assignment, is expected to be a promising transitional technique from half-duplex (HD) to IBFD. To demonstrate the advantages of MDD over HD, this paper first compares the upper-bound performance of MDD and HD by applying unfair greedy RA. Then, considering the millimeter-wave (mmWave) with hybrid beamforming, we propose the RA optimization with the quality-of-service constraints on both downlink (DL) and uplink (UL) mobile-stations (MSs). To solve this non-convex RA problem, we divide it into a suboptimal subcarrier allocation problem solved by the proposed improved fair greedy (IFG) algorithm, and a convex power allocation problem. Furthermore, we design two general hybrid precoder based on matrix factorization and direct approach, and a combiner having high SIC capability. Our results show that the proposed RA algorithm can achieve the performance near the upper-bound achieved by the unfair greedy algorithm, while guaranteeing the proportional fairness among all DL/UL MSs. The performance of the two precoding schemes is depended on the number of radio frequency chains supported. Finally, the proposed SIC algorithm is able to provide sufficient SI mitigation, which can be implemented without impacting the RA operation.

MIMO, Multicarrier-division duplex, full duplex, hybrid beamforming, mmWave, resource allocation, selfinterference cancellation
0018-9545
7921 - 7935
Li, Bohan
79b7a5a4-0966-4611-805b-621d4ff9abb5
Yang, Lie-Liang
ae425648-d9a3-4b7d-8abd-b3cfea375bc7
Maunder, Robert
76099323-7d58-4732-a98f-22a662ccba6c
Sun, SongLin
34982047-9db3-4c99-b6ac-22d8bf8a40ca
Li, Bohan
79b7a5a4-0966-4611-805b-621d4ff9abb5
Yang, Lie-Liang
ae425648-d9a3-4b7d-8abd-b3cfea375bc7
Maunder, Robert
76099323-7d58-4732-a98f-22a662ccba6c
Sun, SongLin
34982047-9db3-4c99-b6ac-22d8bf8a40ca

Li, Bohan, Yang, Lie-Liang, Maunder, Robert and Sun, SongLin (2021) Resource allocation in millimeter-wave multicarrier-division duplex systems with hybrid beamforming. IEEE Transactions on Vehicular Technology, 70 (8), 7921 - 7935, [9477180]. (doi:10.1109/TVT.2021.3095226).

Record type: Article

Abstract

In-band full-duplex (IBFD) systems require promising resource allocation (RA) strategies to fully exploit the available time-frequency resources. Furthermore, the acquisition of channel state information and signal reception in IBFD systems are significantly impacted by insufficient self-interference cancellation (SIC), impeding the applications of IBFD in practical wireless systems. Multicarrier-division duplex (MDD), which benefits low-budget SI mitigation in digital domain and flexible subcarrier assignment, is expected to be a promising transitional technique from half-duplex (HD) to IBFD. To demonstrate the advantages of MDD over HD, this paper first compares the upper-bound performance of MDD and HD by applying unfair greedy RA. Then, considering the millimeter-wave (mmWave) with hybrid beamforming, we propose the RA optimization with the quality-of-service constraints on both downlink (DL) and uplink (UL) mobile-stations (MSs). To solve this non-convex RA problem, we divide it into a suboptimal subcarrier allocation problem solved by the proposed improved fair greedy (IFG) algorithm, and a convex power allocation problem. Furthermore, we design two general hybrid precoder based on matrix factorization and direct approach, and a combiner having high SIC capability. Our results show that the proposed RA algorithm can achieve the performance near the upper-bound achieved by the unfair greedy algorithm, while guaranteeing the proportional fairness among all DL/UL MSs. The performance of the two precoding schemes is depended on the number of radio frequency chains supported. Finally, the proposed SIC algorithm is able to provide sufficient SI mitigation, which can be implemented without impacting the RA operation.

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MDD_RA_Final - Accepted Manuscript
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e-pub ahead of print date: 7 July 2021
Published date: 7 August 2021
Additional Information: Funding Information: Manuscript received November 30, 2020; revised March 14, 2021 and May 23, 2021; accepted July 2, 2021. Date of publication July 7, 2021; date of current version August 13, 2021. This work was supported through the Project EP/P034284/1 by EPSRC, U.K. The review of this article was coordinated by Dr. B. Shim. (Corresponding author: Lie-Liang Yang.) Bohan Li, Lie-Liang Yang, and Robert G. Maunder are with the School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, U.K. (e-mail: bl2n18@ecs.soton.ac.uk; lly@ecs.soton.ac.uk; rm@ecs.soton.ac.uk). Publisher Copyright: © 1967-2012 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
Keywords: MIMO, Multicarrier-division duplex, full duplex, hybrid beamforming, mmWave, resource allocation, selfinterference cancellation

Identifiers

Local EPrints ID: 450707
URI: http://eprints.soton.ac.uk/id/eprint/450707
ISSN: 0018-9545
PURE UUID: 93768cc8-7e4f-48e5-9733-e56b8103d434
ORCID for Bohan Li: ORCID iD orcid.org/0000-0001-7686-8605
ORCID for Lie-Liang Yang: ORCID iD orcid.org/0000-0002-2032-9327
ORCID for Robert Maunder: ORCID iD orcid.org/0000-0002-7944-2615

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Date deposited: 09 Aug 2021 16:30
Last modified: 28 Apr 2022 02:25

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Contributors

Author: Bohan Li ORCID iD
Author: Lie-Liang Yang ORCID iD
Author: Robert Maunder ORCID iD
Author: SongLin Sun

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