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Resource Allocation in Drone-Assisted Emergency Communication Systems

Chen, Tianqi (2023) Resource Allocation in Drone-Assisted Emergency Communication Systems. Doctor of Philosophy (PhD) thesis, University of Kent,. (doi:10.22024/UniKent/01.02.102163) (KAR id:102163)

Abstract

Due to low cost and high mobility, drones are considered important in emergency communications. In this thesis, we consider a unique drone assisted emergency communication system used in disaster scenarios, where the drone with limited power acts as a relay to improve the downlink sum rate through rational resource allocation. The wireless channel model between drones and ground users in emergency communications is different from conventional relay networks, while drones have their coverage area and data rate limits. Considering these specific characteristics, we formulate a joint power and subcarrier allocation problem to maximize data rate of users, which is limited by the transmit power budget per drone and the number of users on each subcarrier in emergency communications.

However, resource allocation in a unique drone assisted emergency communication system is a nondeterministic polynomial time (NP)-hard problem requiring brute force search, which has prohibitive computational complexity. Instead, efficient algorithms that provide a good trade-off between system performance and implementation practicality are needed.

The contributions of this thesis are proposing two different resource allocation schemes. Both schemes divide users into high-priority(HP) users and low-priority(LP) users and both guarantee minimum guaranteed rate for HP users.

The first scheme is an adaptive algorithm with low complexity. In this scheme, a suboptimal solution is proposed by dividing users into two priority groups: HP users (rescuers) and LP users (affected people). This procedure achieves quasi-linear complexity in terms of the number of users. Finally, the data of the brute force search method and this method were collected through simulation experiments. The data shows that the data rate of the proposed scheme was very close to the optimal data rate when there was a lack of resources.

The second scheme is an adaptive algorithm. In the proposed scheme, we formulate a joint power and subcarrier allocation problem to maximize data rate of users, which is limited by the transmit power budget per drone and the number of users on each subcarrier in emergency communications. Due to the intractability of the formulated problem, it is decomposed into two sub-problems: power allocation optimisation and subcarrier allocation optimization. Then a joint resource allocation algorithm is proposed. The simulation results show that the performance of the proposed method is close to that of the optimal solution but with much lower complexity.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Wang, Jiangzhou
Thesis advisor: Zhu, Huiling
DOI/Identification number: 10.22024/UniKent/01.02.102163
Uncontrolled keywords: Resource management, Drones, Optimization, Communication networks, Complexity theory, Downlink
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Funders: University of Kent (https://ror.org/00xkeyj56)
SWORD Depositor: System Moodle
Depositing User: System Moodle
Date Deposited: 21 Jul 2023 09:10 UTC
Last Modified: 25 Jul 2023 07:44 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/102163 (The current URI for this page, for reference purposes)

University of Kent Author Information

Chen, Tianqi.

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