Energy efficiency of resource scheduling for non-orthogonal multiple access (NOMA) wireless network

Non-orthogonal multiple access (NOMA) is a promising technique for the fifth generation mobile communication due to its high spectrum efficiency. By applying superposition coding and successive interference cancellation techniques, multiple users can be multiplexed on the same subchannel in NOMA systems. Previous works focus on subchannel and power allocation to maximize the sum rate; however, the energy-efficient resource allocation problem has not been studied for NOMA systems. In this paper, we aim to optimize subchannel assignment and power allocation to maximize the energy efficiency for the downlink NOMA network. Assuming perfect knowledge of the channel state information at base station, we propose low-complexity suboptimal algorithms which include subchannel assignment and power allocation for subchannel users. In the power allocation scheme, difference of convex functions programming approach is exploited to transform and approximate the original optimal problem into a convex optimization problem. Simulation results show that our proposed algorithms yield much better improvements than orthogonal frequency division multiple in terms of sum rate and energy efficiency.

[1]  Li Ping,et al.  Interleave division multiple-access , 2006, IEEE Trans. Wirel. Commun..

[2]  Yoshihisa Kishiyama,et al.  Non-Orthogonal Access with Random Beamforming and Intra-Beam SIC for Cellular MIMO Downlink , 2013, 2013 IEEE 78th Vehicular Technology Conference (VTC Fall).

[3]  Anass Benjebbour,et al.  System-level performance evaluation of downlink non-orthogonal multiple access (NOMA) , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[4]  Xiaohu Ge,et al.  5G wireless communication systems: prospects and challenges [Guest Editorial] , 2014 .

[5]  H. Vincent Poor,et al.  Cooperative Non-Orthogonal Multiple Access in 5G Systems , 2015, IEEE Communications Letters.

[6]  Chunxiao Jiang,et al.  Resource Allocation for Cognitive Small Cell Networks: A Cooperative Bargaining Game Theoretic Approach , 2015, IEEE Transactions on Wireless Communications.

[7]  Zhu Han,et al.  Distributed User Association and Femtocell Allocation in Heterogeneous Wireless Networks , 2014, IEEE Transactions on Communications.

[8]  Jing Lin,et al.  Interleave-division-multiple-access based intercell interference cancellation for cellular OFDM system , 2011, 2011 International Conference on Machine Learning and Cybernetics.

[9]  Hsiao-Hwa Chen,et al.  Energy-efficient non-cooperative cognitive radio networks: micro, meso, and macro views , 2014, IEEE Communications Magazine.

[10]  Suvra Sekhar Das,et al.  Power allocation in OFDM based NOMA systems: A DC programming approach , 2014, 2014 IEEE Globecom Workshops (GC Wkshps).

[11]  Muhammad Imran,et al.  Non-Orthogonal Multiple Access (NOMA) for cellular future radio access , 2017 .

[12]  Yoshihisa Kishiyama,et al.  Performance of non-orthogonal access with SIC in cellular downlink using proportional fair-based resource allocation , 2012, 2012 International Symposium on Wireless Communication Systems (ISWCS).