Energy-efficient power allocation for NOMA heterogeneous networks with imperfect CSI

doi:10.19682/j.cnki.1005-8885.2022.2011

The Journal of China Universities of Posts and Telecommunications ›› 2022, Vol. 29 ›› Issue (1): 102-112.doi: 10.19682/j.cnki.1005-8885.2022.2011

• Networks • Previous Articles Next Articles

Energy-efficient power allocation for NOMA heterogeneous networks with imperfect CSI

Song Xin, Huang Xue, Gao Yiming, Qian Haijun

School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066000, China

Received:2021-05-11 Revised:2021-07-05 Accepted:2021-09-15 Online:2022-02-26 Published:2022-02-28
Contact: Corresponding author: Huang Xue E-mail:1045430883@qq.com
Supported by:
This work was supported by the National Nature Science Foundation of China (61473066) and the Natural Science Foundation of Hebei Province (F2021501020).

Abstract

Abstract: In this paper, an optimal user power allocation scheme is proposed to maximize the energy efficiency for downlink non-orthogonal multiple access (NOMA) heterogeneous networks (HetNets). Considering channel estimation errors and inter-user interference under imperfect channel state information (CSI), the energy efficiency optimization problem is formulated, which is non-deterministic polynomial (NP)-hard and non-convex. To cope with this intractable problem, the optimization problem is converted into a convex problem and address it by the Lagrangian dual method. However, it is difficult to obtain closed-form solutions since the variables are coupled with each other. Therefore, a Lagrangian and sub-gradient based algorithm is proposed. In the inner layer loop, optimal powers are derived by the sub-gradient method. In the outer layer loop, optimal Lagrangian dual variables are obtained. Simulation results show that the proposed algorithm can significantly improve energy efficiency compared with traditional power allocation algorithms.

Key words: heterogeneous networks, non-orthogonal multiple access, imperfect channel state information, power allocation

CLC Number:

TN92

Song Xin, Huang Xue, Gao Yiming, Qian Haijun. Energy-efficient power allocation for NOMA heterogeneous networks with imperfect CSI[J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(1): 102-112.

References

[1] CHEN S Z, ZHAO J. The requirements, challenges, and technologies for 5G of telecommunication. IEEE Communications Magazine, 2014, 52(5): 36 - 42.

[2] 5G radio access: Requirements, concept and technologies. DOCOMO 5G White Paper. Tokyo, Japan: NTT DOCOMO Inc, 2014.

[3] CUI M M, HU B J, LI X H, et al. Energy-efficient power control algorithm in massive MIMO cognitive radio networks. IEEE Access, 2017, 5: 1164 - 1177.

[4] TANG J, CUMANAN K, LAMBOTHARAN S. Sum-rate maximization technique for spectrum-sharing MIMO OFDM broadcast channels. IEEE Transactions on Vehicular Technology, 2011, 60(4): 1960 - 1964.

[5] GUO C T, LIAO B, HUANG L, et al. Convexity of fairness-aware resource allocation in wireless powered communication networks. IEEE Communications Letter, 2016, 20(3): 474 - 477.

[6] ZHANG H J, JIANG C X, BEAULIEU N C, et al. Resource allocation in spectrum-sharing OFDMA femtocells with heterogeneous services. IEEE Transactions on Communications, 2014, 62(7): 2366 - 2377.

[7] TANG J, SO D K C, ALSUSA E, et al. Resource allocation for energy efficiency optimization in heterogeneous networks. IEEE Journal on Selected Areas in Communications, 2015, 33(10): 2104 - 2117.

[8] WANG X M, ZHENG F C, ZHU P C, et al. Energy-efficient resource allocation in coordinated downlink multicell OFDMA systems. IEEE Transactions on Vehicular Technology, 2016, 65(3): 1395 - 1408.

[9] XIE B, ZHANG Z K, HU R O, et al. Joint spectral efficiency and energy efficiency in FFR-based wireless heterogeneous networks. IEEE Transactions on Vehicular Technology, 2018, 67(9): 8154 - 9168.

[10] ZHANG H J, LIU H, CHENG J L, et al. Downlink energy efficiency of power allocation and wireless backhaul bandwidth allocation in heterogeneous small cell networks. IEEE Transactions on Wireless Communications, 2018, 66(4): 1705 - 1716.

[11] ZHANG H J, FENG M T, LONG K P, et al. Energy efficient resource management in SWIPT enabled heterogeneous networks with NOMA. IEEE Transactions on Wireless Communications, 2020, 19(2): 835 - 845.

[12] PAN C Y, YIN C C, Beaulieu N C, et al. Distributed resource allocation in SDCN-based heterogeneous networks utilizing licensed and unlicensed bands. IEEE Transactions on Wireless Communications, 2018, 17(2): 711 - 721.

[13] ZHOU T Q, LIU Z X, ZHAO J H, et al. Joint user association and power control for load balancing in downlink heterogeneous cellular networks. IEEE Transactions on Vehicular Technology, 2018, 67(3): 2582 - 2593.

[14] ZHAO J J, LIU Y W, CHAI K K, et al. Spectrum allocation and power control for non-orthogonal multiple access in HetNets. IEEE Transactions on Wireless Communications, 2017, 16(9): 5825 - 5837.

[15] MOLTAFET M, AZMI P, MOKARI N, et al. Optimal and fair energy efficient resource allocation for energy harvesting-enabled-PD-NOMA based HetNets. IEEE Transactions on Wireless Communications, 2018, 17(3): 2054 - 2067.

[16] XU B Y, CHEN Y, CARRION J R, et al. Resource allocation in energy-cooperation enabled two-tier NOMA HetNets toward green 5G. IEEE Journal on Selected Areas in Communications, 2017, 35(12): 2758 - 2770.

[17] QIN M, WU W H, YANG Q H, et al. Green-oriented dynamic resource-on-demand strategy for multi-RAT wireless networks powered by heterogeneous energy sources. IEEE Transactions on Wireless Communications, 2020, 19(8): 5547 - 5560.

[18] FANG F, CHENG J L, DING Z G. Joint energy efficient subchannel and power optimization for a downlink NOMA heterogeneous network. IEEE Transactions on Vehicular Technology, 2019, 68(2): 1351 - 1364.

[19] FANG F, ZHANG H J, CHENG J L, et al. Joint user scheduling and power allocation optimization for energy-efficient NOMA systems with imperfect CSI. IEEE Journal on Selected Areas in Communications, 2017, 35(12): 2874 - 2885.

[20] SONG X, DONG L, WANG J P, et al. Energy efficient power allocation for downlink NOMA heterogeneous networks with imperfect CSI. IEEE Access, 2019, 7: 39329 - 39340.

[21] ZAMANI M R, ESLAMI M, KHORRAMIZADEH M, et al. Energy-efficient power allocation for NOMA with imperfect CSI. IEEE Transactions on Vehicular Technology, 2019, 68(1): 1009 - 1013.

[22] YANG Z, DING Z G, FAN P Z, et al. On the performance of non-orthogonal multiple access systems with partial channel information. IEEE Transactions on Communications, 2016, 64(2): 654 - 667.

[23] WEI Z Q, NG D W K, YUAN J H, et al. Optimal resource allocation for power-efficient MC-NOMA with imperfect channel state information. IEEE Transactions on Communications, 2017, 65(9): 3944 - 3961.

[24] SONG X, DONG L, HUANG X, et al. Energy-efficient power allocation based on worst-case performance optimization under channel uncertainties. KSII Transactions on Internet and Information Systems, 2020, 14(11): 4595 - 4610.

[25] XU Y J, LI G Q, YANG Y, et al. Robust resource allocation and power splitting in SWIPT enabled heterogeneous networks: A robust minimax approach. IEEE Internet of Things Journal, 2019, 6(6): 10799 - 10811.

[26] FANG F, ZHANG H J, CHENG J L, et al. Energy-efficient resource allocation for downlink non-orthogonal multiple access network. IEEE Transactions on Communications, 2016, 64(9): 3722 - 3732.

[27] SUN S Q, NI W M, ZHU Y. Robust power control in cognitive radio networks: A distributed way. Proceeding of the 2011 IEEE International Conference on Communications (ICC'11), 2011, Jun 5 - 9, Kyoto, Japan. Piscataway, NJ, USA: IEEE, 2011: 1 - 6.

Metrics

Comments

Copyright © 2020 The Journal of China Universities of Posts and Telecommunications
　 Adress: P.O. Box 231,Beijing University of Posts and Telecommunications,10 Xi Tucheng Road,Beijing 100876,P.R.China　Post Code: 100081
Tel：86-010-62282493　Fax： 86-010-62283461　E-mail: jchupt@bupt.edu.cn
Support by: Beijing Magtech Co.Ltd

Energy-efficient power allocation for NOMA heterogeneous networks with imperfect CSI

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	. Dynamic coverage of mobile multi-target in sensor networks based on virtual force [J]. The Journal of China Universities of Posts and Telecommunications, 2024, 31(4): 83-94.
[2]	Wang Qiang, Zhang Yijia, Zhang Tianjiao, Zhang Wenqi, Gao Yue, Tafazolli Rahim. Secure degrees of freedom for general MIMO interference channel under rank-deficiency [J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(3): 65-77.
[3]	Guo Hui, Zhao Xuehui. Maximum throughput design of wireless powered communication network with IRS-NOMA based on user clustering [J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(3): 55-64.
[4]	Xu Siyang, Song Xin, Zhu Jiahui. Resource allocation optimization for SWIPT full-duplex relaying networks with practical energy harvester [J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(1): 39-46.
[5]	Zhang Huibin, Li Tianzhu, Liu Haojiang, Li Zhuotong. Deep learning-based symbol detection algorithm in IMDD-OOFDM system [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(6): 36-45.
[6]	Guo Xuerang, Li Feng, Zhu Bohan, Zhang Zhijun, Guo Qingrui, Yang Huiting. Prediction-based dynamic routing intelligent algorithm in power optical communication network [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(6): 46-52.
[7]	Li Yajie, Zhang Jie. Artificial intelligence for optical transport networks: architecture, application and challenges [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(6): 3-17.
[8]	Zhang Ping, Xu Xiaodong, Dong Chen, Han Shujun, Wang Bizhu. Intellicise communication system: model-driven semantic communications [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(1): 2-12.
[9]	Zhang Zezhong, Chen Mingzhe, Xu Jie, Cui Shuguang. Air interface design for edge intelligence [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(1): 13-26.
[10]	Liu Guangyi, Deng Juan, Zheng Qingbi, Li Gang, Sun Xin, Huang Yuhong. Native intelligence for 6G mobile network: technical challenges, architecture and key features [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(1): 27-40.
[11]	Sun Junshuai, Zhu Xinghui, Xiao Yeqiu, Cheng Ke, Zhao Shuangrui. Adaptive TTI bundling with self-healing scheme for 5G [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(1): 64-70.
[12]	Guo Hui, Zhao Xuehui. Maximum throughput design for IRS aided WPCN system based on NOMA [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(1): 93-101.
[13]	Kang Mancong, Li Xi, Ji Hong, Zhang Heli. Resource allocation and hybrid prediction scheme for low-latency visual feedbacks to support tactile Internet multimodal perceptions [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(4): 13-28.
[14]	Wang Hang, Li Xi, Ji Hong, Zhang Heli. QoE-based video segments caching strategy in urban public transportation system [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(4): 29-38.
[15]	Li Zongyan, Li Jiahui, Yu Honglu, Li Shiyin. New spatial quadrature modulation scheme for indoor visible light communication systems [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(2): 89-96.