Adaptive Modulation and Coding for URLLC Retransmission
For ultra-reliable low-latency communication (URLLC), retransmission data should be scheduled with different priorities due to the urgency, which brings new challenges in delay-oriented optimization, especially with deterministic delay constraint. In this paper, we propose an adaptive modulation and...
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| Published in: | IEEE Wireless Communications and Networking Conference : [proceedings] : WCNC pp. 1 - 6 |
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| Format: | Conference Proceeding |
| Language: | English |
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21.04.2024
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| ISSN: | 1558-2612 |
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| Abstract | For ultra-reliable low-latency communication (URLLC), retransmission data should be scheduled with different priorities due to the urgency, which brings new challenges in delay-oriented optimization, especially with deterministic delay constraint. In this paper, we propose an adaptive modulation and coding (AMC) scheme for both initial transmissions and retransmissions in separate data queues. Different from most of the existing works focusing on average delay, we jointly consider delay performance and deterministic delay requirement by combining the Markov decision process (MDP) with Lyapunov optimization technique. To overcome the coupling in the objective and the deterministic constraint, we transform this problem into an infinite horizon MDP by constructing a renewal system with sampling. Based on this, we propose a delay-optimal modulation and coding scheme (MCS) selection policy using reinforcement learning. Simulation results show that the proposed scheme achieves better delay performance than the conventional AMC schemes. |
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| AbstractList | For ultra-reliable low-latency communication (URLLC), retransmission data should be scheduled with different priorities due to the urgency, which brings new challenges in delay-oriented optimization, especially with deterministic delay constraint. In this paper, we propose an adaptive modulation and coding (AMC) scheme for both initial transmissions and retransmissions in separate data queues. Different from most of the existing works focusing on average delay, we jointly consider delay performance and deterministic delay requirement by combining the Markov decision process (MDP) with Lyapunov optimization technique. To overcome the coupling in the objective and the deterministic constraint, we transform this problem into an infinite horizon MDP by constructing a renewal system with sampling. Based on this, we propose a delay-optimal modulation and coding scheme (MCS) selection policy using reinforcement learning. Simulation results show that the proposed scheme achieves better delay performance than the conventional AMC schemes. |
| Author | Wang, Yitu Zhang, Zhaoyang Jin, Yuze Zheng, Ziwei Wang, Wei |
| Author_xml | – sequence: 1 givenname: Yuze surname: Jin fullname: Jin, Yuze organization: College of Information Science and Electronic Engineering, Zhejiang University,Hangzhou,P.R. China – sequence: 2 givenname: Wei surname: Wang fullname: Wang, Wei email: wangw@zju.edu.cn organization: School of Electrical and Information Engineering, North Minzu University,Yinchuan,P.R. China – sequence: 3 givenname: Ziwei surname: Zheng fullname: Zheng, Ziwei organization: College of Information Science and Electronic Engineering, Zhejiang University,Hangzhou,P.R. China – sequence: 4 givenname: Yitu surname: Wang fullname: Wang, Yitu organization: College of Information Science and Electronic Engineering, Zhejiang University,Hangzhou,P.R. China – sequence: 5 givenname: Zhaoyang surname: Zhang fullname: Zhang, Zhaoyang organization: School of Electrical and Information Engineering, North Minzu University,Yinchuan,P.R. China |
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| Snippet | For ultra-reliable low-latency communication (URLLC), retransmission data should be scheduled with different priorities due to the urgency, which brings new... |
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| SubjectTerms | Encoding Markov decision processes Modulation Reinforcement learning Simulation Transforms Ultra reliable low latency communication |
| Title | Adaptive Modulation and Coding for URLLC Retransmission |
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