Energy-Efficient Transmission Strategy for Delay Tolerable Services in NOMA-Based Downlink With Two Users

With the continuous development of the communication industry, there is a shift in real-time services from 4G networks to Delay Tolerable (DT) services in the context of 5G/B5G networks. Additionally, energy consumption control poses significant challenges in the current communication industry. Ther...

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Vydáno v:	IEEE access Ročník 11; s. 113227 - 113243
Hlavní autoři:	Bai, Mengmeng, Zhu, Rui, Guo, Jianxin, Wang, Feng, Wang, Liping, Zhu, Hangjie, Huang, Lei, Zhang, Yushuai
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	5G mobile communication Algorithms approximate statistical dynamic programming algorithm Approximation algorithms Base stations Communication Communications systems Context Convex analysis Convexity Decision analysis deep deterministic policy gradient Deep learning delay tolerable Delays Downlink Downlinking Dynamic programming Energy consumption Energy efficiency Heuristic algorithms NOMA Nonorthogonal multiple access Optimization proximal policy optimization Real time Resource management Statistical analysis
ISSN:	2169-3536, 2169-3536
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Abstract	With the continuous development of the communication industry, there is a shift in real-time services from 4G networks to Delay Tolerable (DT) services in the context of 5G/B5G networks. Additionally, energy consumption control poses significant challenges in the current communication industry. Therefore, we study algorithms and schemes to improve the Energy Efficiency (EE) of DT services in the context of Non-Orthogonal Multiple Access (NOMA) downlink two-user communication system.First, we transformed the EE enhancement problem into a convex optimization problem based on transmission power by derivation. Secondly, we propose to use Approximate Statistical Dynamic Programming (ASDP) algorithm, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO) to solve the problem that convex optimization cannot be decided in real time. Finally, we perform an interpretability analysis on whether the decision schemes of the agents trained by the DDPG algorithm and the PPO algorithm are reasonable. The simulation results show that the decisions made by the agent trained by the DDPG algorithm perform better compared to the ASDP algorithm and the PPO algorithm.
AbstractList	With the continuous development of the communication industry, there is a shift in real-time services from 4G networks to Delay Tolerable (DT) services in the context of 5G/B5G networks. Additionally, energy consumption control poses significant challenges in the current communication industry. Therefore, we study algorithms and schemes to improve the Energy Efficiency (EE) of DT services in the context of Non-Orthogonal Multiple Access (NOMA) downlink two-user communication system.First, we transformed the EE enhancement problem into a convex optimization problem based on transmission power by derivation. Secondly, we propose to use Approximate Statistical Dynamic Programming (ASDP) algorithm, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO) to solve the problem that convex optimization cannot be decided in real time. Finally, we perform an interpretability analysis on whether the decision schemes of the agents trained by the DDPG algorithm and the PPO algorithm are reasonable. The simulation results show that the decisions made by the agent trained by the DDPG algorithm perform better compared to the ASDP algorithm and the PPO algorithm.
Author	Zhu, Hangjie Guo, Jianxin Wang, Liping Huang, Lei Bai, Mengmeng Zhang, Yushuai Zhu, Rui Wang, Feng
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SubjectTerms	5G mobile communication Algorithms approximate statistical dynamic programming algorithm Approximation algorithms Base stations Communication Communications systems Context Convex analysis Convexity Decision analysis deep deterministic policy gradient Deep learning delay tolerable Delays Downlink Downlinking Dynamic programming Energy consumption Energy efficiency Heuristic algorithms NOMA Nonorthogonal multiple access Optimization proximal policy optimization Real time Resource management Statistical analysis
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Title	Energy-Efficient Transmission Strategy for Delay Tolerable Services in NOMA-Based Downlink With Two Users
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