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A novel adaptive code block group hybrid automatic repeat request scheme for low earth orbit satellite networks
International Journal of Satellite Communications and Networking ( IF 1.7 ) Pub Date : 2021-05-06 , DOI: 10.1002/sat.1402
Zhongliang Deng 1 , Hao Liu 1 , Ke Wang 2 , Wenliang Lin 1 , Xiaoyi Yu 1 , Shixuan Zheng 1
Affiliation  

Low earth orbit (LEO) satellite networks provide important support to expand 5G-and-beyond networks to realize global coverage. Hybrid automatic repeat requests (HARQs) can greatly improve the reliability of transmission through dynamic satellite channels. Due to the large propagation delay in LEO satellite channels, the biggest challenges of HARQ in satellite networks are the delayed channel state information (CSI) and overflow of receiver memory. In this paper, we propose a novel adaptive code block group HARQ (ACBG-HARQ) scheme that achieves lower retransmission rates with reliable data receiving. First, we build a new channel state model (CSM) to describe the relationship between the packet error rate (PER) and global channel degradation. Three states of receiver memory allocation for HARQ are designed with respect to the channel state and memory occupation: idle state, non-full state, and full state. Then, we propose an optimal HARQ scheme for LEO satellite networks with the Markov decision process (MDP) based on the fuzzy Q-learning (FQL) algorithm to improve the accuracy of ACBG-HARQ state transfer, which contributes to adaptive selection of the HARQ code block group size. Simulation results show that the ACBG-HARQ scheme can achieve a maximum spectrum efficiency gain of 10% and that the probability of receiver memory overflow is reduced by 1%∼6%.

中文翻译:

一种新的低地球轨道卫星网络自适应码块组混合自动重发请求方案

低地球轨道(LEO)卫星网络为扩展5G及以后网络实现全球覆盖提供重要支撑。混合自动重传请求 (HARQ) 可以大大提高通过动态卫星信道传输的可靠性。由于 LEO 卫星信道的传播延迟很大,卫星网络中 HARQ 的最大挑战是延迟的信道状态信息 (CSI) 和接收机内存溢出。在本文中,我们提出了一种新颖的自适应码块组 HARQ (ACBG-HARQ) 方案,该方案通过可靠的数据接收实现了较低的重传率。首先,我们建立了一个新的信道状态模型(CSM)来描述误包率(PER)和全局信道退化之间的关系。针对信道状态和内存占用设计了 HARQ 接收器内存分配的三种状态:空闲状态、非满状态和满状态。然后,我们提出了一种基于模糊 Q 学习 (FQL) 算法的马尔可夫决策过程 (MDP) 的 LEO 卫星网络最优 HARQ 方案,以提高 ACBG-HARQ 状态转移的准确性,这有助于 HARQ 的自适应选择代码块组大小。仿真结果表明,ACBG-HARQ 方案可以实现10%的最大频谱效率增益,并且接收器内存溢出的概率降低了1%∼6%。我们提出了一种基于模糊 Q 学习 (FQL) 算法的马尔可夫决策过程 (MDP) 的 LEO 卫星网络最优 HARQ 方案,以提高 ACBG-HARQ 状态转移的准确性,这有助于 HARQ 代码块的自适应选择组大小。仿真结果表明,ACBG-HARQ 方案可以实现10%的最大频谱效率增益,并且接收器内存溢出的概率降低了1%∼6%。我们提出了一种基于模糊 Q 学习 (FQL) 算法的马尔可夫决策过程 (MDP) 的 LEO 卫星网络最优 HARQ 方案,以提高 ACBG-HARQ 状态转移的准确性,这有助于 HARQ 代码块的自适应选择组大小。仿真结果表明,ACBG-HARQ 方案可以实现10%的最大频谱效率增益,并且接收器内存溢出的概率降低了1%∼6%。
更新日期:2021-05-06
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