4.7 Article

Optimal Throughput Fairness Tradeoffs for Downlink Non-Orthogonal Multiple Access Over Fading Channels

Journal

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 17, Issue 6, Pages 3556-3571

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2018.2803177

Keywords

Non-orthogonal multiple access; orthogonal multiple access; fairness; fading channel; ergodic rate; outage probability; Lagrangian dual decomposition; strong duality

Funding

  1. Engineering and Physical Sciences Research Council of the U.K. [EP/N005651/2]
  2. U.S. National Science Foundation [CNS-1702808, ECCS-1647198]
  3. EPSRC [EP/N005651/2, EP/N005651/1, EP/P009719/1] Funding Source: UKRI

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Recently, non-orthogonal multiple access (NOMA) has attracted considerable interest as one of the 5G-enabling techniques. However, the users with better channel conditions in downlink communications intrinsically benefit more from NOMA than the users with worse channel conditions thanks to successive decoding, judicious designs are required to guarantee user fairness. In this paper, a two-user downlink NOMA system over fading channels is considered. For delay-tolerant transmission, the average sum rate is maximized subject to both average and peak-power constraints as well as a minimum average user rate constraint. The optimal resource allocation is obtained using the Lagrangian dual decomposition under full channel state information at the transmitter (CSIT), while an effective power allocation policy under partial CSIT is also developed based on analytical results. In parallel, for delay-limited transmission, the sum of delay-limited throughput (DLT) is maximized subject to a maximum allowable user outage constraint under full CSIT, and the analysis for the sum of DLT is also performed under partial CSIT. Furthermore, an optimal orthogonal multiple access (OMA) scheme is also studied as a benchmark to prove the superiority of NOMA over OMA under full CSIT. Finally, the theoretical analysis is verified by simulations via different tradeoffs for the average sum rate (sum-DLT) versus the minimum (maximum) average user rate (outage) requirement.

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