UAV-enabled integrated sensing and communication in maritime emergency networks
UAV-enabled integrated sensing and communication in maritime emergency networks
With line-of-sight mode deployment and fast response, unmanned aerial vehicle (UAV), equipped with the cutting-edge integrated sensing and communication (ISAC) technique, is poised to deliver high-quality communication and sensing services in maritime emergency scenarios. In practice, however, the real-time transmission of ISAC signals at the UAV side cannot be realized unless the reliable wireless fronthaul link between the terrestrial base station and UAV are available. This paper proposes a multicarrier-division duplex based joint fronthaulaccess scheme, where mutually orthogonal subcarrier sets are leveraged to simultaneously support four types of fronthaul/access transmissions. In order to maximize the end-to-end communication rate while maintaining an adequate sensing quality-of-service (QoS) in such a complex scheme, the UAV trajectory, subcarrier assignment and power allocation are jointly optimized. The overall optimization process is designed in two stages. As the emergency area is usually far away from the coast, the optimal initial operating position for the UAV is first found. Once the UAV passes the initial operating position, the UAV’s trajectory and resource allocation are optimized during the mission period to maximize the end-to-end communication rate under the constraint of minimum sensing QoS. Simulation results demonstrate the effectiveness of the proposed scheme in dealing with the joint fronthaul-access optimization problem in maritime ISAC networks, offering the advantages over benchmark schemes.
Li, Bohan
4a33b982-c099-4731-b21d-1cafad070df2
Liu, Jiahao
a71cd1bc-4ee2-4c7b-a638-dd5b249a2b08
Mu, Junsheng
049991c3-b49c-4c39-b559-46cc8ccd955f
Xiao, Pei
4fe33422-75e3-44d1-a2d2-8feb12f28d66
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Li, Bohan
4a33b982-c099-4731-b21d-1cafad070df2
Liu, Jiahao
a71cd1bc-4ee2-4c7b-a638-dd5b249a2b08
Mu, Junsheng
049991c3-b49c-4c39-b559-46cc8ccd955f
Xiao, Pei
4fe33422-75e3-44d1-a2d2-8feb12f28d66
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Li, Bohan, Liu, Jiahao, Mu, Junsheng, Xiao, Pei and Chen, Sheng
(2025)
UAV-enabled integrated sensing and communication in maritime emergency networks.
IEEE Internet of Things Journal.
(In Press)
Abstract
With line-of-sight mode deployment and fast response, unmanned aerial vehicle (UAV), equipped with the cutting-edge integrated sensing and communication (ISAC) technique, is poised to deliver high-quality communication and sensing services in maritime emergency scenarios. In practice, however, the real-time transmission of ISAC signals at the UAV side cannot be realized unless the reliable wireless fronthaul link between the terrestrial base station and UAV are available. This paper proposes a multicarrier-division duplex based joint fronthaulaccess scheme, where mutually orthogonal subcarrier sets are leveraged to simultaneously support four types of fronthaul/access transmissions. In order to maximize the end-to-end communication rate while maintaining an adequate sensing quality-of-service (QoS) in such a complex scheme, the UAV trajectory, subcarrier assignment and power allocation are jointly optimized. The overall optimization process is designed in two stages. As the emergency area is usually far away from the coast, the optimal initial operating position for the UAV is first found. Once the UAV passes the initial operating position, the UAV’s trajectory and resource allocation are optimized during the mission period to maximize the end-to-end communication rate under the constraint of minimum sensing QoS. Simulation results demonstrate the effectiveness of the proposed scheme in dealing with the joint fronthaul-access optimization problem in maritime ISAC networks, offering the advantages over benchmark schemes.
Text
IoTJ2025-accep
- Accepted Manuscript
More information
Accepted/In Press date: 6 October 2025
Identifiers
Local EPrints ID: 506626
URI: http://eprints.soton.ac.uk/id/eprint/506626
ISSN: 2327-4662
PURE UUID: 3786c99e-366c-4ccd-821c-ebeef9cc5d27
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Date deposited: 12 Nov 2025 17:44
Last modified: 12 Nov 2025 17:44
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Contributors
Author:
Bohan Li
Author:
Jiahao Liu
Author:
Junsheng Mu
Author:
Pei Xiao
Author:
Sheng Chen
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