Utility-oriented optimization for video streaming in UAV-aided MEC network: a DRL approach

Miao, J, Bai, S, Mumtaz, S ORCID: https://orcid.org/0000-0001-6364-6149, Zhang, Q and Mu, J, 2024. Utility-oriented optimization for video streaming in UAV-aided MEC network: a DRL approach. IEEE Transactions on Green Communications and Networking. ISSN 2473-2400

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Abstract

The integration of unmanned aerial vehicles (UAVs) in future communication networks has received great attention, and it plays an essential role in many applications, such as military reconnaissance, fire monitoring, etc. In this paper, we consider a UAV-aided video transmission system based on mobile edge computing (MEC). Considering the short latency requirements, the UAV acts as a MEC server to transcode the videos and as a relay to forward the transcoded videos to the ground base station. Subject to constraints on discrete variables and short latency, we aim to maximize the cumulative utility by jointly optimizing the power allocation, video transcoding policy, computational resources allocation, and UAV flight trajectory. The above non-convex optimization problem is modeled as a Markov decision process (MDP) and solved by a deep deterministic policy gradient (DDPG) algorithm to realize continuous action control by policy iteration. Simulation results show that the DDPG algorithm performs better than deep Q-learning network algorithm (DQN) and actor-critic (AC) algorithm.

Item Type:	Journal article
Publication Title:	IEEE Transactions on Green Communications and Networking
Creators:	Miao, J., Bai, S., Mumtaz, S., Zhang, Q. and Mu, J.
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Date:	10 January 2024
ISSN:	2473-2400
Identifiers:	Number Type 10.1109/tgcn.2024.3352173 DOI 1852262 Other
Rights:	© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Ward
Date Added:	18 Jan 2024 10:17
Last Modified:	18 Jan 2024 10:17
URI:	https://irep.ntu.ac.uk/id/eprint/50707

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