QoE-Based Resource Allocation for Multi-Cell NOMA Networks

Jingjing Cui, Yuanwei Liu, Zhiguo Ding, Pingzhi Fan, Arumugam Nallanathan

Research output: Contribution to journalArticlepeer-review

77 Scopus citations

Abstract

Quality of experience (QoE) is an important indicator in the fifth generation (5G) wireless communication systems. For characterizing user-base station (BS) association, subchannel assignment, and power allocation, we investigate the resource allocation problem in multi-cell multicarrier non-orthogonal multiple access (MC-NOMA) networks. An optimization problem is formulated with the objective of maximizing the sum mean opinion scores (MOSs) of users in the networks. To solve the challenging mixed integer programming problem, we first decompose it into two subproblems, which are characterized by combinational variables and continuous variables, respectively. For the combinational subproblem, a 3-D matching problem is proposed for modeling the relation among users, BSs, and subchannels. Then, a two-step approach is proposed to attain a suboptimal solution. For the continuous power allocation subproblem, the branch and bound approach is invoked to obtain the optimal solution. Furthermore, a low complexity suboptimal approach based on successive convex approximation techniques is developed for striking a good computational complexity-optimality tradeoff. Simulation results reveal that: 1) the proposed NOMA networks is capable of outperforming conventional orthogonal multiple access networks in terms of QoE and 2) the proposed algorithms for sum-MOS maximization can achieve significant fairness improvement against the sum-rate maximization scheme.

Original languageBritish English
Article number8415760
Pages (from-to)6160-6176
Number of pages17
JournalIEEE Transactions on Wireless Communications
Volume17
Issue number9
DOIs
StatePublished - Sep 2018

Keywords

  • Multi-cell multicarrier non-orthogonal multiple access (MC-NOMA)
  • quality of experience (QoE)
  • resource allocation
  • the branch and bound (BB) approach
  • three-dimensional (3D) matching

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