Exploiting Spectral-Energy Efficiency Tradeoff with Fairness in Non-Orthogonal Multiple Access Systems
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摘要
The spectral efficiency( SE) and energy efficiency( EE) tradeoff while ensuring rate fairness among users in non-orthogonal multiple access( NOMA) systems is investigated. In order to characterize the SE-EE tradeoff with rate fairness,a multi-objective optimization( MOO) problem is first formulated,where the rate fairness is represented with the α-fair utility function. Then,the MOO problem is converted into a single-objective optimization( SOO) problem by the weighted sum method. To solve the converted non-convex SOO problem,we apply sequential convex programming,which helps to propose a general power allocation algorithm to realize the SE-EE tradeoff with rate fairness. We prove the convergence of the proposed algorithm and the convergent solution satisfies the KKT conditions. Simulation results demonstrate the proposed power allocation algorithm can achieve various levels of rate fairness,and higher fairness results in degraded performance of SE-EE tradeoff. A pivotal conclusion is reached that NOMA systems significantly outperform orthogonal multiple access systems in terms of SE-EE tradeoff with the same level of rate fairness.
The spectral efficiency( SE) and energy efficiency( EE) tradeoff while ensuring rate fairness among users in non-orthogonal multiple access( NOMA) systems is investigated. In order to characterize the SE-EE tradeoff with rate fairness,a multi-objective optimization( MOO) problem is first formulated,where the rate fairness is represented with the α-fair utility function. Then,the MOO problem is converted into a single-objective optimization( SOO) problem by the weighted sum method. To solve the converted non-convex SOO problem,we apply sequential convex programming,which helps to propose a general power allocation algorithm to realize the SE-EE tradeoff with rate fairness. We prove the convergence of the proposed algorithm and the convergent solution satisfies the KKT conditions. Simulation results demonstrate the proposed power allocation algorithm can achieve various levels of rate fairness,and higher fairness results in degraded performance of SE-EE tradeoff. A pivotal conclusion is reached that NOMA systems significantly outperform orthogonal multiple access systems in terms of SE-EE tradeoff with the same level of rate fairness.
The spectral efficiency( SE) and energy efficiency( EE) tradeoff while ensuring rate fairness among users in non-orthogonal multiple access( NOMA) systems is investigated. In order to characterize the SE-EE tradeoff with rate fairness,a multi-objective optimization( MOO) problem is first formulated,where the rate fairness is represented with the α-fair utility function. Then,the MOO problem is converted into a single-objective optimization( SOO) problem by the weighted sum method. To solve the converted non-convex SOO problem,we apply sequential convex programming,which helps to propose a general power allocation algorithm to realize the SE-EE tradeoff with rate fairness. We prove the convergence of the proposed algorithm and the convergent solution satisfies the KKT conditions. Simulation results demonstrate the proposed power allocation algorithm can achieve various levels of rate fairness,and higher fairness results in degraded performance of SE-EE tradeoff. A pivotal conclusion is reached that NOMA systems significantly outperform orthogonal multiple access systems in terms of SE-EE tradeoff with the same level of rate fairness.
引文
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[9]Fang F,Zhang H,Cheng J,et al.Energy-efficient resource allocation for downlink non-orthogonal multiple access(NOMA)network[J].IEEE Transactions on Communications,2016,64(9):3722-3732.
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[11]Tang J,So D K C,Alsusa E,et al.Resource efficiency:A new paradigm on energy efficiency and spectral efficiency tradeoff[J].IEEE Transactions on Wireless Communications,2014,13(8):4656-4669.
[12]Mo J,Walrand J.Fair end-to-end window-based congestion control[J].IEEE/ACM Transactions on Networking,2000,8(5):556-567.
[13]Marler R T,Arora J S.Survey of multi-objective optimization methods for engineering[J].Structural&Multidisciplinary Optimization,2004,26(6):369-395.
[14]Zappone A,Sanguinetti L,Bacci G,et al.Energy-efficient power control:A look at 5G wireless technologies[J].IEEE Transactions on Signal Processing,2016,64(7):1668-1683.
[15]Boyd S,Vandenberghe L.Convex optimization[M].Cambridge,UK:Cambridge University Press,2004.
[16]Shi H,Prasad R V,Onur E,et al.Fairness in wireless networks:issues,measures and challenges[J].IEEECommunications Surveys&Tutorials,2014,16(1):5-24.
[2]Cover T M,Thomas J A.Elements of information theory(2nd ed)[M].Hoboken,USA:Wiley-Interscience,2006.
[3]Xu P,Ding Z,Dai X,et al.A new evaluation criterion for non-orthogonal multiple access in 5 G software defined networks[J].IEEE Access,2015,3:1633-1639.
[4]Lei L,Yuan D,Ho C K,et al.Joint optimization of power and channel allocation with non-orthogonal multiple access for 5 G cellular systems[C]∥Proceedings of IEEE Global Communications Conference(GLOBECOM),San Diego,CA,USA:IEEE,2015:1-6.
[5]Sun Q,Han S,I C-L,et al.On the ergodic capacity of MIMO NOMA systems[J].IEEE Wireless Communications Letters,2015,4(4):405-408.
[6]Yang Z,Xu W,Pan C,et al.On the optimality of power allocation for NOMA downlinks with individual QoS constraints[J].IEEE Communications Letters,2017,21(7):1649-1652.
[7]Timotheou S,Krikidis I.Fairness for non-orthogonal multiple access in 5G systems[J].IEEE Signal Processing Letters,2015,22(10):1647-1651.
[8]Sun Q,Han S F,Chin-Lin I,et al.Energy efficiency optimization for fading MIMO non-orthogonal multiple access systems[C]∥Proceedings of IEEE International Conference on Communications(ICC).London,UK:IEEE,2015:2668-2673.
[9]Fang F,Zhang H,Cheng J,et al.Energy-efficient resource allocation for downlink non-orthogonal multiple access(NOMA)network[J].IEEE Transactions on Communications,2016,64(9):3722-3732.
[10]Zhang Y,Wang H M,Zheng T X,et al.Energy-efficient transmission design in non-orthogonal multiple access[J].IEEE Transactions on Vehicular Technology,2017,66(3):2852-2857.
[11]Tang J,So D K C,Alsusa E,et al.Resource efficiency:A new paradigm on energy efficiency and spectral efficiency tradeoff[J].IEEE Transactions on Wireless Communications,2014,13(8):4656-4669.
[12]Mo J,Walrand J.Fair end-to-end window-based congestion control[J].IEEE/ACM Transactions on Networking,2000,8(5):556-567.
[13]Marler R T,Arora J S.Survey of multi-objective optimization methods for engineering[J].Structural&Multidisciplinary Optimization,2004,26(6):369-395.
[14]Zappone A,Sanguinetti L,Bacci G,et al.Energy-efficient power control:A look at 5G wireless technologies[J].IEEE Transactions on Signal Processing,2016,64(7):1668-1683.
[15]Boyd S,Vandenberghe L.Convex optimization[M].Cambridge,UK:Cambridge University Press,2004.
[16]Shi H,Prasad R V,Onur E,et al.Fairness in wireless networks:issues,measures and challenges[J].IEEECommunications Surveys&Tutorials,2014,16(1):5-24.