Adaptive NOMA in Time-Varying Wireless Networks With No CSIT/CDIT Relying on a 1-Bit Feedback

In this letter, the outage performance of a two-user downlink non-orthogonal multiple access (NOMA) time-varying network without any knowledge on the channel state or distribution at the base station (BS) is investigated. Building on reinforcement learning techniques and, more precisely, on multi-armed bandits (MAB), we propose a novel adaptive NOMA scheme that optimally tunes which user should perform successive interference cancellation (SIC) jointly with the power allocation at the BS. Remarkably, our proposed scheme requires only a single bit (ACK-type) of feedback from each user and is still able to outperform OMA, as demonstrated by the numerical results in many settings of interest including stochastic and even non-stationary (adversarial) ones.

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