Joint power allocation and user association in non-orthogonal multiple access networks: An evolutionary approach

Abstract In this paper, the problem of joint power allocation and user association is studied for non-orthogonal multiple access (NOMA) downlink networks with multiple base stations (BSs). We consider that users are grouped into orthogonal clusters to allocate into different physical resource blocks (PRBs). The problem is formulated using two different utility functions. The first is the maximization of the weighted sum rate and the other is the maximization of the minimum achievable user rate. We apply two different evolutionary algorithms in order to solve this problem. Namely, the recently introduced Salp Swarm Algorithm (SSA) and the popular Particle Swarm Optimization (PSO). The simulation results show that the above-described problem can be effectively solved by both algorithms. SSA is more efficient in average than PSO. The effect of increasing the number of user is also studied. In this case the problem becomes more difficult to solve, which indicates that more network resources are required.

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

[2]  R. Rao Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems , 2016 .

[3]  Hossam Faris,et al.  Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems , 2017, Adv. Eng. Softw..

[4]  Tiankui Zhang,et al.  Distributed Energy Efficient Fair User Association in Massive MIMO Enabled HetNets , 2015, IEEE Communications Letters.

[5]  Zhijin Qin,et al.  User Association and Resource Allocation in Unified NOMA Enabled Heterogeneous Ultra Dense Networks , 2018, IEEE Communications Magazine.

[6]  Shiwen Mao,et al.  User Association in Massive MIMO HetNets , 2015, IEEE Systems Journal.

[7]  Lajos Hanzo,et al.  Nonorthogonal Multiple Access for 5G and Beyond , 2017, Proceedings of the IEEE.

[8]  Jeffrey G. Andrews,et al.  User Association for Load Balancing in Heterogeneous Cellular Networks , 2012, IEEE Transactions on Wireless Communications.

[9]  Pingzhi Fan,et al.  On the Performance of Non-Orthogonal Multiple Access in 5G Systems with Randomly Deployed Users , 2014, IEEE Signal Processing Letters.

[10]  Weng Chon Ao,et al.  Approximation Algorithms for Online User Association in Multi-Tier Multi-Cell Mobile Networks , 2017, IEEE/ACM Transactions on Networking.

[11]  Octavia A. Dobre,et al.  Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challenges , 2016, IEEE Communications Surveys & Tutorials.

[12]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[13]  George K. Karagiannidis,et al.  A Survey on Non-Orthogonal Multiple Access for 5G Networks: Research Challenges and Future Trends , 2017, IEEE Journal on Selected Areas in Communications.

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

[15]  Andrea J. Goldsmith,et al.  Capacity and optimal resource allocation for fading broadcast channels - Part I: Ergodic capacity , 2001, IEEE Trans. Inf. Theory.

[16]  Harald Haas,et al.  Joint User Association and Power Allocation for Cell-Free Visible Light Communication Networks , 2018, IEEE Journal on Selected Areas in Communications.

[17]  H. Vincent Poor,et al.  Application of Non-Orthogonal Multiple Access in LTE and 5G Networks , 2015, IEEE Communications Magazine.