4.7 Article

Spectrum Allocation and Power Control for Non-Orthogonal Multiple Access in HetNets

Journal

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 16, Issue 9, Pages 5825-5837

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2017.2716921

Keywords

Fairness; heterogeneous networks (HetNets); matching game; non-orthogonal multiple access (NOMA); sequential convex programming; sum rate

Funding

  1. ESRC U.K. [ES/M008509/1]
  2. Queen Mary University of London
  3. Beijing University of Posts and Telecommunications
  4. U.S. NSF [CNS-1702850, CNS-1646607, ECCS-1547201, CCF-1456921, CMMI-1434789, CNS-1443917, ECCS-1405121]
  5. ESRC [ES/M008509/1] Funding Source: UKRI

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In this paper, a novel resource allocation design is investigated for non-orthogonal multiple access (NOMA) enhanced heterogeneous networks (HetNets), where small cell base stations (SBSs) are capable of communicating with multiple small cell users (SCUs) via the NOMA protocol. With the aim of maximizing the sum rate of SCUs while taking the fairness issue into consideration, a joint problem of spectrum allocation and power control is formulated. In particular, the spectrum allocation problem is modeled as a many-to-one matching game with peer effects. We propose a novel algorithm where the SBSs and resource blocks interact to decide their desired allocation. The proposed algorithm is proved to converge to a twosided exchange-stable matching. Furthermore, we introduce the concept of 'exploration' into the matching game for further improving the SCUs' sum rate. The power control of each SBS is formulated as a non-convex problem, where the sequential convex programming is adopted to iteratively update the power allocation result by solving the approximate convex problem. The obtained solution is proved to satisfy the Karush-Kuhn-Tucker conditions. We unveil that: 1) the proposed algorithm closely approaches the optimal solution within a limited number of iterations; 2) the 'exploration' action is capable of further enhancing the performance of the matching algorithm; and 3) the developed NOMA-enhanced HetNets achieve a higher SCUs' sum rate compared with the conventional OMA-based HetNets.

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