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Title: NOMA Decoding: Successive Interference Cancellation or Maximum Likelihood Detection?
Is successive interference cancellation (SIC) decoding always the optimal choice in non-orthogonal multiple access (NOMA) systems? While the answer is positive based on Shannon theory, which is applicable to infinite-length codewords drawn from a Gaussian distribution, this may not universally hold for systems with finite-alphabet inputs. Specifically, in this paper, we demonstrate that for quadrature amplitude modulation (QAM)-based NOMA, SIC decoding fails for certain values of power allocation coefficient a:, used to divide power among NOMA users. With this observation, we propose employing maximum likelihood (ML) detection to decode QAM-NOMA. While SIC decoding for QAM-NOMA requires allocating higher power to the user with a weaker channel to prevent symbol crossing in super-constellations, ML detection can successfully handle a broader range of power allocation coefficients. We then derive closed-form symbol error rates for quadrature phase shift keying-based NOMA systems across any a: and validate them through simulations. The results demonstrate the effectiveness of ML detection, particularly in scenarios where SIC decoding fails.  more » « less
Award ID(s):
2301778
PAR ID:
10528688
Author(s) / Creator(s):
;
Publisher / Repository:
IEEE
Date Published:
ISBN:
979-8-3503-6929-8
Page Range / eLocation ID:
1 to 6
Format(s):
Medium: X
Location:
Princeton, NJ, USA
Sponsoring Org:
National Science Foundation
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