Minimizing Age-of-Information in HARQ-CC Aided NOMA Systems

In this paper, we investigate the timeliness performance of a downlink wireless communication system with non-orthogonal multiple access (NOMA). The timeliness of the system is characterized by Age of Information (AoI). To efficiently utilize the time-frequency resource and achieve a tradeoff betwee...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2023-02, Vol.22 (2), p.1-1
Main Authors: Wu, Shaohua, Deng, Zhihong, Li, Aimin, Jiao, Jian, Zhang, Ning, Zhang, Qinyu
Format: Article
Language:English
Subjects:
Adaptive systems
Age of Information
Automatic repeat request
Delays
finite blocklength
HARQ-CC
Lyapunov Drift function
Markov processes
MDP
Measurement
NOMA
Nonorthogonal multiple access
Optimization
Packet transmission
power alloction
Reliability
Resource management
Throughput
Wireless communication systems
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Summary:In this paper, we investigate the timeliness performance of a downlink wireless communication system with non-orthogonal multiple access (NOMA). The timeliness of the system is characterized by Age of Information (AoI). To efficiently utilize the time-frequency resource and achieve a tradeoff between timeliness and reliability, we propose an adaptive transmission policy under hybrid automatic repeat request with chase combining (HARQ-CC) aided NOMA systems. In particular, the BS can adaptively adjust the power allocation and decide whether to transmit old or new packets to users in the NOMA system, based on the current AoI status and the positive/negative acknowledgement (ACK/NACK) feedback signal.We first analyze the BLER under such adaptive systems, and then formulate an AoI minimization problem based on the derived BLER. By transforming the objective function to a Markov Decision Process (MDP) problem, an optimal policy is obtained to minimize the average AoI of the system. Considering the high complexity of the MDP, we further divise an alternative near-optimal policy based on Lyapunov Drift function. Furthermore, we consider the fairness of users and propose a greedy policy to minimize the maximal expected AoI of users. Based on extensive simulations, it has been found that NOMA can outperform OMA on both an overall and a user-level basis when operating with adaptive retransmission and power allocation strategies.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2022.3201115