A Novel Approach to Enhance the Energy Efficiency of a NOMA Network
Abstract
:1. Introduction
2. Related Works and Motivation
- We propose a new user allocation algorithm called User Sub-channel Fair Matching Algorithm (USFMA), benefiting from existing user allocation algorithms and combining their advantages. Unlike USMA, we propose an optimum channel gain compensation, sorting, and selection that can enhance the overall system capacity and performance. This algorithm has a lower computational complexity than the Exhaustive Search Algorithm (ESA) and can ensure user fairness. Moreover, the complexity of the USFMA will not increase sharply when increasing the number of superimposed users.
- Optimization of the energy efficiency of NOMA systems. We propose using the DC programming method to allocate power for end users superimposed on the corresponding sub-channel. The main idea is to utilize DC programming to convert non-convex problems into convex problems.
- Simulations of the proposed algorithm in Matlab. The simulation results confirm that NOMA systems surpass OFDM systems. Additionally, the USFMA is better than the existing USMA and CSS-PA. Therefore, using DC programming to allocate power for end users can improve the system’s energy efficiency.
3. System Model
4. Problem Description
5. The Sub-Optimal Solution
5.1. User Sub-Channel Fair Matching Algorithm
Algorithm 1: User Sub-Channel Fair Matching Algorithm (USFMA) |
|
Complexity Analysis
5.2. Power Allocation by DC Programming
Algorithm 2: Power Allocation by DC Programming [46] |
|
6. Performance Analysis
Simulation Results
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Wang, Y.; Ren, B.; Sun, S.; Kang, S.; Yue, X. Analysis of non-orthogonal multiple access for 5G. China Commun. 2016, 13, 52–66. [Google Scholar] [CrossRef]
- Kizilirmak, R.C.; Bizaki, H.K. Non-orthogonal multiple access (NOMA) for 5G networks. Towards 5G Wirel. Netw. Phys. Layer Perspect. 2016, 83, 83–98. [Google Scholar]
- Islam, S.R.; Avazov, N.; Dobre, O.A.; Kwak, K.S. Power-domain non-orthogonal multiple access (NOMA) in 5G systems: Potentials and challenges. IEEE Commun. Surv. Tutor. 2016, 19, 721–742. [Google Scholar] [CrossRef]
- Ding, Z.; Xu, J.; Dobre, O.A.; Poor, H.V. Joint power and time allocation for NOMA–MEC offloading. IEEE Trans. Veh. Technol. 2019, 68, 6207–6211. [Google Scholar] [CrossRef]
- Ai, Y.; Wang, L.; Han, Z.; Zhang, P.; Hanzo, L. Social networking and caching aided collaborative computing for the Internet of Things. IEEE Commun. Mag. 2018, 56, 149–155. [Google Scholar] [CrossRef]
- Ding, Z.; Liu, Y.; Choi, J.; Sun, Q.; Elkashlan, M.; Chih-Lin, I.; Poor, H.V. Application of non-orthogonal multiple access in LTE and 5G networks. IEEE Commun. Mag. 2017, 55, 185–191. [Google Scholar] [CrossRef]
- Yang, Z.; Ding, Z.; Fan, P.; Al-Dhahir, N. A general power allocation scheme to guarantee quality of service in downlink and uplink NOMA systems. IEEE Trans. Wirel. Commun. 2016, 15, 7244–7257. [Google Scholar] [CrossRef]
- Ding, Z.; Adachi, F.; Poor, H.V. The application of MIMO to non-orthogonal multiple access. IEEE Trans. Wirel. Commun. 2015, 15, 537–552. [Google Scholar] [CrossRef]
- Sun, Q.; Han, S.; Xu, Z.; Wang, S.; Chih-Lin, I.; Pan, Z. Sum rate optimization for MIMO non-orthogonal multiple access systems. In Proceedings of the 2015 IEEE Wireless Communications and Networking Conference (WCNC), New Orleans, LA, USA, 9–12 March 2015; pp. 747–752. [Google Scholar]
- Ding, Z.; Fan, P.; Poor, H.V. On the coexistence between full-duplex and NOMA. IEEE Wirel. Commun. Lett. 2018, 7, 692–695. [Google Scholar] [CrossRef]
- Kader, M.F.; Shin, S.Y.; Leung, V.C. Full-duplex non-orthogonal multiple access in cooperative relay sharing for 5G systems. IEEE Trans. Veh. Technol. 2018, 67, 5831–5840. [Google Scholar] [CrossRef]
- Elbamby, M.S.; Bennis, M.; Saad, W.; Debbah, M.; Latva-Aho, M. Resource optimization and power allocation in in-band full duplex-enabled non-orthogonal multiple access networks. IEEE J. Sel. Areas Commun. 2017, 35, 2860–2873. [Google Scholar] [CrossRef]
- Choi, J. Minimum power multicast beamforming with superposition coding for multiresolution broadcast and application to NOMA systems. IEEE Trans. Commun. 2015, 63, 791–800. [Google Scholar] [CrossRef]
- Liu, G.; Chen, X.; Ding, Z.; Ma, Z.; Yu, F.R. Hybrid half-duplex/full-duplex cooperative non-orthogonal multiple access with transmit power adaptation. IEEE Trans. Wirel. Commun. 2017, 17, 506–519. [Google Scholar] [CrossRef]
- Zhang, Z.; Ma, Z.; Xiao, M.; Ding, Z.; Fan, P. Full-duplex device-to-device-aided cooperative nonorthogonal multiple access. IEEE Trans. Veh. Technol. 2016, 66, 4467–4471. [Google Scholar]
- Huang, Y.; Zhang, C.; Wang, J.; Jing, Y.; Yang, L.; You, X. Signal processing for MIMO-NOMA: Present and future challenges. IEEE Wirel. Commun. 2018, 25, 32–38. [Google Scholar] [CrossRef]
- Dai, L.; Wang, B.; Peng, M.; Chen, S. Hybrid precoding-based millimeter-wave massive MIMO-NOMA with simultaneous wireless information and power transfer. IEEE J. Sel. Areas Commun. 2018, 37, 131–141. [Google Scholar] [CrossRef]
- Zhang, S.; Di, B.; Song, L.; Li, Y. Radio resource allocation for non-orthogonal multiple access (NOMA) relay network using matching game. In Proceedings of the 2016 IEEE International Conference on Communications (ICC), Kuala Lumpur, Malaysia, 22–27 May 2016; pp. 1–6. [Google Scholar]
- Al-Abbasi, Z.Q.; So, D.K. Resource allocation in non-orthogonal and hybrid multiple access system with proportional rate constraint. IEEE Trans. Wirel. Commun. 2017, 16, 6309–6320. [Google Scholar] [CrossRef]
- Lei, L.; Yuan, D.; Ho, C.K.; Sun, S. Power and channel allocation for non-orthogonal multiple access in 5G systems: Tractability and computation. IEEE Trans. Wirel. Commun. 2016, 15, 8580–8594. [Google Scholar] [CrossRef]
- Wei, Z.; Ng, D.W.K.; Yuan, J. Power-efficient resource allocation for MC-NOMA with statistical channel state information. In Proceedings of the 2016 IEEE Global Communications Conference (GLOBECOM), Washington, DC, USA, 4–8 December 2016; pp. 1–7. [Google Scholar]
- Wei, Z.; Ng, D.W.K.; Yuan, J.; Wang, H.M. Optimal resource allocation for power-efficient MC-NOMA with imperfect channel state information. IEEE Trans. Commun. 2017, 65, 3944–3961. [Google Scholar] [CrossRef]
- Zaman, N.; Tang Jung, L.; Yasin, M.M. Enhancing energy efficiency of wireless sensor network through the design of energy efficient routing protocol. J. Sens. 2016, 2016, 9278701. [Google Scholar] [CrossRef]
- Hao, W.; Zeng, M.; Chu, Z.; Yang, S. Energy-efficient power allocation in millimeter wave massive MIMO with non-orthogonal multiple access. IEEE Wirel. Commun. Lett. 2017, 6, 782–785. [Google Scholar] [CrossRef]
- Zhang, Y.; Wang, H.M.; Zheng, T.X.; Yang, Q. Energy-efficient transmission design in non-orthogonal multiple access. IEEE Trans. Veh. Technol. 2016, 66, 2852–2857. [Google Scholar] [CrossRef]
- Fang, F.; Zhang, H.; Cheng, J.; Leung, V.C. Energy-efficient resource allocation for downlink non-orthogonal multiple access network. IEEE Trans. Commun. 2016, 64, 3722–3732. [Google Scholar] [CrossRef]
- Fang, F.; Cheng, J.; Ding, Z. Joint energy efficient subchannel and power optimization for a downlink NOMA heterogeneous network. IEEE Trans. Veh. Technol. 2018, 68, 1351–1364. [Google Scholar] [CrossRef]
- Tran, T.N.; Voznak, M. Adaptive multiple access assists multiple users over multiple-input-multiple-output non-orthogonal multiple access wireless networks. Int. J. Commun. Syst. 2021, 34, e4803. [Google Scholar] [CrossRef]
- Ganesan, I.; Jayakumar, R.J.S.; Murugan, S.P.; Muneeswaran, D.B. Joint energy-efficient user scheduling and power allocation scheme for a millimeter-wave-NOMA system. Int. J. Commun. Syst. 2021, 34, e4901. [Google Scholar] [CrossRef]
- Rashid, B.; Ahmad, A.; Saleem, S.; Khan, A. Joint energy efficient power and subchannel allocation for uplink MC-NOMA networks. Int. J. Commun. Syst. 2020, 33, e4606. [Google Scholar] [CrossRef]
- Yang, K.; Yang, N.; Ye, N.; Jia, M.; Gao, Z.; Fan, R. Non-orthogonal multiple access: Achieving sustainable future radio access. IEEE Commun. Mag. 2018, 57, 116–121. [Google Scholar] [CrossRef]
- Di, B.; Bayat, S.; Song, L.; Li, Y. Radio resource allocation for downlink non-orthogonal multiple access (NOMA) networks using matching theory. In Proceedings of the 2015 IEEE Global Communications Conference (GLOBECOM), San Diego, CA, USA, 6–10 December 2015; pp. 1–6. [Google Scholar]
- Zhang, H.; Zhang, D.K.; Meng, W.X.; Li, C. User pairing algorithm with SIC in non-orthogonal multiple access system. In Proceedings of the 2016 IEEE International Conference on Communications (ICC), Kuala Lumpur, Malaysia, 22–27 May 2016; pp. 1–6. [Google Scholar]
- Venturino, L.; Zappone, A.; Risi, C.; Buzzi, S. Energy-Efficient Scheduling and Power Allocation in Downlink OFDMA Networks with Base Station Coordination. IEEE Trans. Wirel. Commun. 2015, 14, 1–14. [Google Scholar] [CrossRef]
- Ismail, S.; Sun, L. Decentralized hungarian-based approach for fast and scalable task allocation. In Proceedings of the 2017 International Conference on Unmanned Aircraft Systems (ICUAS), Miami, FL, USA, 13–16 June 2017; pp. 23–28. [Google Scholar]
- Kuhn, H. The hungarian method for the assignment problem. Nav. Res. Logist. Q. 1955, 2, 83–97. [Google Scholar] [CrossRef]
- Masaracchia, A.; Nguyen, L.D.; Yin, C.; Dobre, O.A.; Garcia-Palacios, E. The concept of time sharing noma into uav-enabled communications: An energy-efficient approach. In Proceedings of the 2020 4th International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom), Hanoi, Vietnam, 28–29 August 2020; pp. 61–65. [Google Scholar]
- Xie, X.; Fang, F.; Ding, Z. Joint optimization of beamforming, phase-shifting and power allocation in a multi-cluster IRS-NOMA network. IEEE Trans. Veh. Technol. 2021, 70, 7705–7717. [Google Scholar] [CrossRef]
- Fu, Y.; Shum, K.W.; Sung, C.W.; Liu, Y. Optimal user pairing in cache-based NOMA systems with index coding. In Proceedings of the ICC 2019—2019 IEEE International Conference on Communications (ICC), Shanghai, China, 20–24 May 2019; pp. 1–6. [Google Scholar]
- Vucic, N.; Shi, S.; Schubert, M. DC programming approach for resource allocation in wireless networks. In Proceedings of the 8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, Avignon, France, 31 May–4 June 2010; pp. 380–386. [Google Scholar]
- Zhai, D.; Zhang, R.; Cai, L.; Li, B.; Jiang, Y. Energy-efficient user scheduling and power allocation for NOMA-based wireless networks with massive IoT devices. IEEE Internet Things J. 2018, 5, 1857–1868. [Google Scholar] [CrossRef]
- Yuille, A.L.; Rangarajan, A. The concave-convex procedure. Neural Comput. 2003, 15, 915–936. [Google Scholar] [CrossRef] [PubMed]
- Schittkowski, K.; Zillober, C. Nonlinear programming: Algorithms, software, and applications. In Proceedings of the IFIP Conference on System Modeling and Optimization; Springer: Boston, MA, USA, 2003; pp. 73–107. [Google Scholar]
- Ben-Tal, A.; Nemirovski, A. Lectures on Modern Convex Optimization; Society for Industrial and Applied Mathematics: Philadelphia, PA, USA, 2001. [Google Scholar] [CrossRef]
- Boyd, S.; Boyd, S.P.; Vandenberghe, L. Convex Optimization; Cambridge University Press: Cambridge, UK, 2004. [Google Scholar]
- Bertsekas, D.P. Nonlinear programming. J. Oper. Res. Soc. 1997, 48, 334. [Google Scholar] [CrossRef]
- Ng, D.W.K.; Lo, E.S.; Schober, R. Energy-efficient resource allocation in OFDMA systems with large numbers of base station antennas. IEEE Trans. Wirel. Commun. 2012, 11, 3292–3304. [Google Scholar] [CrossRef]
- Jain, R.K.; Chiu, D.M.W.; Hawe, W.R. A Quantitative Measure of Fairness and Discrimination for Resource Allocation in Shared Computer Systems; Eastern Research Laboratory, Digital Equipment Corporation: Hudson, MA, USA, 1984. [Google Scholar]
- Al-Wani, M.M.; Sali, A.; Noordin, N.K.; Hashim, S.J.; Leow, C.Y.; Krikidis, I. Robust beamforming and user clustering for guaranteed fairness in downlink NOMA with partial feedback. IEEE Access 2019, 7, 121599–121611. [Google Scholar] [CrossRef]
Matching Results | |||
---|---|---|---|
10 | [39] | 22 | |
[61] | 54 | 38 | |
79 | 55 | [60] | |
171 | [215] | 516 | |
[328] | 232 | 1133 | |
403 | 837 | [1886] |
Simulation Parameters | Parameter Value |
---|---|
Cell radius | 500 m |
Minimum distance between BS and UEs | 50 m |
Minimum distance between two users | 40 m |
System bandwidth | 5 MHz |
Maximum number of UTs | 60 |
Fixed circuit power [47] | 1 W |
Noise power spectral density | −174 dBm/Hz |
Difference tolerance in Algorithm 2 | 0.01 |
Compensation matrix attenuation coefficient | 0.4 |
Base station peak power | 41 dBm |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Rajab, H.; Ren, B.; Cinkler, T. A Novel Approach to Enhance the Energy Efficiency of a NOMA Network. Telecom 2023, 4, 611-628. https://doi.org/10.3390/telecom4030027
Rajab H, Ren B, Cinkler T. A Novel Approach to Enhance the Energy Efficiency of a NOMA Network. Telecom. 2023; 4(3):611-628. https://doi.org/10.3390/telecom4030027
Chicago/Turabian StyleRajab, Husam, Baolin Ren, and Tibor Cinkler. 2023. "A Novel Approach to Enhance the Energy Efficiency of a NOMA Network" Telecom 4, no. 3: 611-628. https://doi.org/10.3390/telecom4030027