  A generalized downlink multi-antenna non-orthogonal multiple access (NOMA)
transmission framework is proposed with the novel concept of cluster-free
successive interference cancellation (SIC). In contrast to conventional NOMA
approaches, where SIC is successively carried out within the same cluster, the
key idea is that the SIC can be flexibly implemented between any arbitrary
users to achieve efficient interference elimination. Based on the proposed
framework, a sum rate maximization problem is formulated for jointly optimizing
the transmit beamforming and the SIC operations between users, subject to the
SIC decoding conditions and users' minimal data rate requirements. To tackle
this highly-coupled mixed-integer nonlinear programming problem, an alternating
direction method of multipliers-successive convex approximation (ADMM-SCA)
algorithm is developed. The original problem is first reformulated into a
tractable biconvex augmented Lagrangian (AL) problem by handling the non-convex
terms via SCA. Then, this AL problem is decomposed into two subproblems that
are iteratively solved by the ADMM to obtain the stationary solution. Moreover,
to reduce the computational complexity and alleviate the parameter
initialization sensitivity of ADMM-SCA, a Matching-SCA algorithm is proposed.
The intractable binary SIC operations are solved through an extended
many-to-many matching, which is jointly combined with an SCA process to
optimize the transmit beamforming. The proposed Matching-SCA can converge to an
enhanced exchange-stable matching that guarantees the local optimality.
Numerical results demonstrate that: i) the proposed Matching-SCA algorithm
achieves comparable performance and a faster convergence compared to ADMM-SCA;
ii) the proposed generalized framework realizes scenario-adaptive
communications and outperforms traditional multi-antenna NOMA approaches in
various communication regimes.
