Antenna Selection for MIMO Nonorthogonal Multiple Access Systems

This paper considers the antenna selection (AS) problem for a multiple-input multiple-output nonorthogonal multiple access system. In particular, we develop new computationally efficient AS algorithms for two commonly used scenarios: NOMA with fixed power allocation (F-NOMA) and NOMA with cognitive radio-inspired power allocation (CR-NOMA). For the F-NOMA scenario, a new max-max-max AS (A ³ -AS) scheme is first proposed to maximize the system sum-rate. This is achieved by selecting one antenna at the base station (BS) and corresponding best receive antenna at each user that maximizes the channel gain of the resulting strong user. To improve the user fairness, a new max-min-max AS (AIA-AS) scheme is subsequently developed, in which we jointly select one transmit antenna at BS and corresponding best receive antennas at users to maximize the channel gain of the resulting weak user. For the CR-NOMA scenario, we propose another new AS algorithm, termed maximum-channel-gain-based antenna selection (MCG-AS), to maximize the achievable rate of the secondary user, under the condition that the primary user's quality-of-service requirement is satisfied. The asymptotic closed-form expressions of the average sum-rate for A ³ -AS and AIA-AS and that of the average rate of the secondary user for MCG-AS are derived. Numerical results demonstrate that the AIA-AS provides better user fairness, whereas the A ³ -AS achieves a near-optimal sum-rate in F-NOMA systems. For the CR-NOMA scenario, MCG-AS achieves a near-optimal performance in a wide signal-to-noise-ratio regime. Furthermore, all the proposed AS algorithms yield a significant computational complexity reduction, compared to exhaustive search-based counterparts.