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Online resource allocation for QoE optimization in CoMP-assisted eMBMS system

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Abstract

Coordinated multi-point (CoMP) transmission allows multiple base stations (BSs) to transmit the same signal to users simultaneously at the same resource block for higher throughput. It can be applied to the evolved Multimedia Broadcast/Multicast Service (eMBMS) framework to provide additional gains for users in the same multicast group. However, optimal resource allocation is required for the system with multiple cells and multicast groups with various quality of experience (QoE) requirements. This paper investigates the online QoE maximization for a CoMP-enhanced eMBMS system by jointly optimizing the BS clustering, sub-channel assignment, and power allocation. Moreover, we propose a hybrid learning framework combining deep reinforcement learning (DRL) and model-based optimization techniques. More specifically, for the DRL scheme, we propose a multi-agent deep Q network (DQN) to find the online BS clustering and sub-channel assignment for each multicast group with fast convergence. For the model-based scheme, we propose a fractional programming-based method to find the optimal power allocation and evaluate the joint action reward in the proposed DRL framework. With the reward obtained by optimal power allocation design, the action space for the DRL algorithm can thus be reduced, and the joint optimization algorithmic framework can be constructed. Numerical results demonstrate the effectiveness of the proposed algorithm, and the performance gain can be improved by increasing the number of BSs and sub-channels.

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Funding

This work was supported in part by the National Natural Science Foundation of China under Grants No. 61972079, 62172084, 62132004, in part by the Major Research Plan of National Natural Science Foundation of China under Grant No. 92167103, in part by the LiaoNing Revitalization Talents Program under Grant No. XLYC2007162, in part by the LiaoNing Key Research and Development Program under Grant No. 2023JH2/101300196, and in part by the Fundamental Research Funds for the Central Universities under Grants No. N2216009, N2216006, N2116004, and 2324004-12.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China

    Jian Chen, Kaili Zhai, Jie Jia, An Du, Yi Xue & Xingwei Wang

  2. Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, 110819, Liaoning, China

    Jian Chen, Jie Jia & Yi Xue

Authors
  1. Jian Chen
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  2. Kaili Zhai
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  3. Jie Jia
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  4. An Du
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  5. Yi Xue
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  6. Xingwei Wang
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Contributions

Jian Chen performed conceptualization and methodology; Kaili Zhai performed validation and original Draft; Jie Jia performed review and editing; An Du performd data curation; Yi Xue provided computing resources; Xingwei Wang performed supervision.

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Correspondence to Jie Jia.

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Chen, J., Zhai, K., Jia, J. et al. Online resource allocation for QoE optimization in CoMP-assisted eMBMS system. Peer-to-Peer Netw. Appl. 16, 2667–2680 (2023). https://doi.org/10.1007/s12083-023-01555-0

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