Efficient Power Allocation for Multi-Cell Uplink NOMA Network

Digital technologies are rapidly shaping the modern concepts of urbanization. It is a key element of developing practical smart cities of the future. In fact, they are the catalyst for the increasing networking of all areas of life in a smart city. Recent development in the domain of communication technologies has opened new avenues to realize the concept of smart cities. One of such communication technology is non-orthogonal multiple access (NOMA) for future cellular communications. This article, therefore, focuses on the interference management of uplink cellular NOMA systems. Specifically, we propose a power optimization technique for NOMA to improve the sum-rate in a multi-cell environment. We also consider Nakagami-m faded links to analyze the applicability of our proposed scheme under various channel conditions. The simulation results show that the proposed NOMA approach outperforms conventional orthogonal multiple access (OMA) technique in the multi-cell uplink scenario.

[1]  Yujie Han,et al.  5G Converged Cell-Less Communications in Smart Cities , 2016, IEEE Communications Magazine.

[2]  Shuangfeng Han,et al.  Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends , 2015, IEEE Communications Magazine.

[3]  Patrick P. Bergmans,et al.  Random coding theorem for broadcast channels with degraded components , 1973, IEEE Trans. Inf. Theory.

[4]  Lingyang Song,et al.  Sub-Channel Assignment, Power Allocation, and User Scheduling for Non-Orthogonal Multiple Access Networks , 2016, IEEE Transactions on Wireless Communications.

[5]  Miao Pan,et al.  Joint Sensing Duration Adaptation, User Matching, and Power Allocation for Cognitive OFDM-NOMA Systems , 2018, IEEE Transactions on Wireless Communications.

[6]  Robert G. Gallager,et al.  Capacity and coding for degraded broadcast channels , 1974 .

[7]  Martin Haenggi,et al.  Superposition Coding Strategies: Design and Experimental Evaluation , 2012, IEEE Transactions on Wireless Communications.

[8]  Tapani Ristaniemi,et al.  Outage Analysis of Relay-Aided Non-Orthogonal Multiple Access with Partial Relay Selection , 2018, 2018 IEEE Globecom Workshops (GC Wkshps).

[9]  Ekram Hossain,et al.  Dynamic User Clustering and Power Allocation for Uplink and Downlink Non-Orthogonal Multiple Access (NOMA) Systems , 2016, IEEE Access.

[10]  Mauro Fadda,et al.  Multimedia Multicast Services in 5G Networks: Subgrouping and Non-Orthogonal Multiple Access Techniques , 2018, IEEE Communications Magazine.

[11]  Srihari Nelakuditi,et al.  Successive interference cancellation: a back-of-the-envelope perspective , 2010, Hotnets-IX.

[12]  Frank Schaich,et al.  5GNOW: non-orthogonal, asynchronous waveforms for future mobile applications , 2014, IEEE Communications Magazine.

[13]  Pingzhi Fan,et al.  Impact of User Pairing on 5G Nonorthogonal Multiple-Access Downlink Transmissions , 2016, IEEE Transactions on Vehicular Technology.

[14]  Dong In Kim,et al.  LTE/LTE-A Random Access for Massive Machine-Type Communications in Smart Cities , 2016, IEEE Communications Magazine.

[15]  Anass Benjebbour,et al.  Non-Orthogonal Multiple Access (NOMA) for Cellular Future Radio Access , 2013, 2013 IEEE 77th Vehicular Technology Conference (VTC Spring).

[16]  Wei Liang,et al.  User Pairing for Downlink Non-Orthogonal Multiple Access Networks Using Matching Algorithm , 2017, IEEE Transactions on Communications.

[17]  Ju Liu,et al.  Efficient power allocation in downlink multi-cell multi-user NOMA networks , 2019, IET Commun..

[18]  Dimitrios D. Vergados,et al.  A Survey on the Successive Interference Cancellation Performance for Single-Antenna and Multiple-Antenna OFDM Systems , 2013, IEEE Communications Surveys & Tutorials.