Twin-timescale radio resource management for ultra-reliable and low-latency vehicular networks
Twin-timescale radio resource management for ultra-reliable and low-latency vehicular networks
To efficiently support safety-related vehicular applications, the ultra-reliable and low-latency communication (URLLC) concept has become an indispensable component of vehicular networks (VNETs). Due to the high mobility of VNETs, exchanging near-instantaneous channel state information (CSI) and making reliable resource allocation decisions based on such short-term CSI evaluations are not practical. In this paper, we consider the downlink of a vehicle-to-infrastructure (V2I) system conceived for URLLC based on idealized perfect and realistic imperfect CSI. By exploiting the benefits of the massive MIMO concept, a two-stage radio resource allocation problem is formulated based on a novel twin-timescale perspective for avoiding the frequent exchange of near-instantaneous CSI. Specifically, based on the prevalent road-traffic density, Stage 1 is constructed for minimizing the worst-case transmission latency on a long-term timescale. In Stage 2, the base station allocates the total power at a short-term timescale according to the large-scale fading CSI encountered for minimizing the maximum transmission latency across all vehicular users. Then, a primary algorithm and a secondary algorithm are conceived for our V2I URLLC system to find the optimal solution of the twin-timescale resource allocation problem, with special emphasis on the complexity imposed. Finally, our simulation results show that the proposed resource allocation scheme significantly reduces the maximum transmission latency, and it is not sensitive to the fluctuation of road-traffic density.
1023 - 1036
Yang, Haojun
4956d3b5-d3f1-41f5-b4bf-0aff47d6d806
Zheng, Kan
1141004c-e359-4b26-a49b-2a821d76edf0
Zhao, Long
d90dfed2-ac7b-4169-9c1a-851b008545b9
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Yang, Haojun
4956d3b5-d3f1-41f5-b4bf-0aff47d6d806
Zheng, Kan
1141004c-e359-4b26-a49b-2a821d76edf0
Zhao, Long
d90dfed2-ac7b-4169-9c1a-851b008545b9
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Yang, Haojun, Zheng, Kan, Zhao, Long and Hanzo, Lajos
(2019)
Twin-timescale radio resource management for ultra-reliable and low-latency vehicular networks.
IEEE Transactions on Vehicular Technology, .
(doi:10.1109/TVT.2019.2954462).
Abstract
To efficiently support safety-related vehicular applications, the ultra-reliable and low-latency communication (URLLC) concept has become an indispensable component of vehicular networks (VNETs). Due to the high mobility of VNETs, exchanging near-instantaneous channel state information (CSI) and making reliable resource allocation decisions based on such short-term CSI evaluations are not practical. In this paper, we consider the downlink of a vehicle-to-infrastructure (V2I) system conceived for URLLC based on idealized perfect and realistic imperfect CSI. By exploiting the benefits of the massive MIMO concept, a two-stage radio resource allocation problem is formulated based on a novel twin-timescale perspective for avoiding the frequent exchange of near-instantaneous CSI. Specifically, based on the prevalent road-traffic density, Stage 1 is constructed for minimizing the worst-case transmission latency on a long-term timescale. In Stage 2, the base station allocates the total power at a short-term timescale according to the large-scale fading CSI encountered for minimizing the maximum transmission latency across all vehicular users. Then, a primary algorithm and a secondary algorithm are conceived for our V2I URLLC system to find the optimal solution of the twin-timescale resource allocation problem, with special emphasis on the complexity imposed. Finally, our simulation results show that the proposed resource allocation scheme significantly reduces the maximum transmission latency, and it is not sensitive to the fluctuation of road-traffic density.
Text
URLLC_V2I_v12
- Accepted Manuscript
More information
Accepted/In Press date: 17 November 2019
e-pub ahead of print date: 6 December 2019
Identifiers
Local EPrints ID: 447410
URI: http://eprints.soton.ac.uk/id/eprint/447410
ISSN: 0018-9545
PURE UUID: 30cc5997-44b0-4ba0-ab0d-f2993c912ad3
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Date deposited: 10 Mar 2021 17:45
Last modified: 18 Mar 2024 05:14
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Contributors
Author:
Haojun Yang
Author:
Kan Zheng
Author:
Long Zhao
Author:
Lajos Hanzo
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