Energy Efficiency Optimization Algorithm Based On PD-NOMA Under Heterogeneous Cloud Radio Access Networks

Lun TANG; Ziyu LI; Lingjin GUAN; Qianbin CHEN

doi:10.11999/JEIT200327

Volume 43 Issue 6

Jun. 2021

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Lun TANG, Ziyu LI, Lingjin GUAN, Qianbin CHEN. Energy Efficiency Optimization Algorithm Based On PD-NOMA Under Heterogeneous Cloud Radio Access Networks[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1706-1714. doi: 10.11999/JEIT200327

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Lun TANG, Ziyu LI, Lingjin GUAN, Qianbin CHEN. Energy Efficiency Optimization Algorithm Based On PD-NOMA Under Heterogeneous Cloud Radio Access Networks[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1706-1714. doi: 10.11999/JEIT200327

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Energy Efficiency Optimization Algorithm Based On PD-NOMA Under Heterogeneous Cloud Radio Access Networks

doi: 10.11999/JEIT200327

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Key Laboratory of Mobile Communication Technology, Chongqing University of Post and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (62071078), The Science and Technology Research Project of Chongqing Education Commission (KJZD-M201800601), The Major Theme Projects in Chongqing (cstc2019jscxzdztzxX0006)

Received Date: 2020-04-28
Rev Recd Date: 2020-10-05

Available Online: 2020-10-12

Publish Date: 2021-06-18

Abstract

Abstract

In view of the spectrum efficiency and energy efficiency of Heterogeneous Cloud Radio Access Networks (H-CRAN), an energy efficiency optimization algorithm based on Power Domain Non-Orthogonal Multiple Access (PD-NOMA) is proposed. First, the algorithm takes queue stability and forward link capacity as constraints, jointly optimizes user association, power allocation and resource block allocation, and it establishes a joint optimization model of network energy efficiency and user fairness. Secondly, because the state space and action space of the system are both high-dimensional and continuity, the research problem is the NP-hard problem of the continuous domain, and then Trust Region Policy Optimization (TRPO) algorithm is introduced to solve efficiently the continuous domain issue. Finally, the amount of calculations generated by the standard solution for the TRPO algorithm is too large, and Proximal Policy Optimization (PPO) algorithm is used to optimize the solution. The PPO algorithm not only ensures the reliability of the TRPO algorithm, but also reduces effectively the TRPO calculation complexity. Simulation results show that the algorithm proposed in this paper improves further the energy efficiency performance of the network under the constraint of ensuring user fairness.
- Heterogeneous Cloud Radio Access Networks(H-CRAN),
- Resource allocation,
- Network energy efficiency,
- Deep Reinforcement Learning(DRL)

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References

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