Retransmission Aware Adaptive Modulation and Coding Toward Deterministic Delay Performance

被引:0
作者
Jin, Yuze [1 ]
Wang, Wei [1 ]
Wang, Yitu [2 ]
Yin, Rui [3 ]
Zheng, Ziwei [1 ]
Zhang, Zhaoyang [1 ]
机构
[1] Zhejiang Univ, Coll Informat Sci & Elect Engn, Hangzhou 310027, Peoples R China
[2] North Minzu Univ, Sch Elect & Informat Engn, Yinchuan 750030, Peoples R China
[3] Hangzhou City Univ, Coll Informat & Elect Engn, Hangzhou 310015, Peoples R China
基金
中国国家自然科学基金;
关键词
Delays; Optimization; Ultra reliable low latency communication; Throughput; Modulation; Couplings; Signal to noise ratio; URLLC; deterministic delay constraint; adaptive modulation and coding; data retransmission; WIRELESS; SYSTEMS; DESIGN;
D O I
10.1109/TWC.2024.3456188
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Ultra-reliable low-latency communication (URLLC) is an indispensable element towards supporting various latency-sensitive and reliability-critical applications. To optimize the average delay while satisfying the deterministic delay constraint, initial transmission and retransmission should be handled with different priorities due to the differentiated urgency, which creates complex interdependency and brings new technical challenges to delay-oriented optimization. In this paper, we propose a retransmission-aware adaptive modulation and coding (RAMC) scheme to improve the delay performance in URLLC scenarios. Specifically, we first establish a cascaded queue system, including an initial transmission queue and a retransmission queue. The deterministic delay constraint is satisfied through Lyapunov optimization, where we transform the Lyapunov drift-plus-penalty problem into an infinite horizon Markov decision process (MDP) by constructing a renewal system with sampling to overcome the challenge brought by queue coupling. Next, we propose the delay-optimal RAMC scheme by solving the associated Bellman equation by improved reinforcement learning, which is proved to be asymptotically optimal. Finally, the superiority of the proposed RAMC scheme is verified through simulations.
引用
收藏
页码:17683 / 17697
页数:15
相关论文
共 41 条
[1]   Learning algorithms or Markov decision processes with average cost [J].
Abounadi, J ;
Bertsekas, D ;
Borkar, VS .
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2001, 40 (03) :681-698
[2]  
Adhicandra I, 2010, Arxiv, DOI arXiv:1005.5125
[3]   Hybrid Automatic Repeat Request (HARQ) in Wireless Communications Systems and Standards: A Contemporary Survey [J].
Ahmed, Ashfaq ;
Al-Dweik, Arafat ;
Iraqi, Youssef ;
Mukhtar, Husameldin ;
Naeem, Muhammad ;
Hossain, Ekram .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2021, 23 (04) :2711-2752
[4]   HARQ in Full-Duplex Relay-Assisted Transmissions for URLLC [J].
Airod F.E. ;
Chafnaji H. ;
Yanikomeroglu H. .
IEEE Open Journal of the Communications Society, 2021, 2 :409-422
[5]   A New Adaptive Rate IR-HARQ Combining with AMC [J].
Alkhoder, A. ;
Assimi, A. ;
Alhariri, M. .
JOURNAL OF COMMUNICATIONS SOFTWARE AND SYSTEMS, 2018, 14 (04) :340-349
[6]   Enabling early HARQ feedback in 5G networks [J].
Berardinelli, Gilberto ;
Khosravirad, Saeed R. ;
Pedersen, Klaus I. ;
Frederiksen, Frank ;
Mogensen, Preben .
2016 IEEE 83RD VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), 2016,
[7]  
Bertsekas D., 2012, Dynamic Programming and Optimal Control, V2
[8]  
Billingsley P., 1999, Convergence of probability measures, Wiley series in probability and statistics. Probability and statistics section, V2nd
[9]   Network Slicing Enabled Resource Management for Service-Oriented Ultra-Reliable and Low-Latency Vehicular Networks [J].
Chen, Yuanbin ;
Wang, Ying ;
Liu, Man ;
Zhang, Jiayi ;
Jiao, Lei .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (07) :7847-7862
[10]   A Survey on Delay-Aware Resource Control for Wireless Systems-Large Deviation Theory, Stochastic Lyapunov Drift, and Distributed Stochastic Learning [J].
Cui, Ying ;
Lau, Vincent K. N. ;
Wang, Rui ;
Huang, Huang ;
Zhang, Shunqing .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2012, 58 (03) :1677-1701