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A generalized downlink multi-antenna non-orthogonal multiple access (NOMA)transmission framework is proposed with the novel concept of cluster-freesuccessive interference cancellation (SIC). In contrast to conventional NOMAapproaches, where SIC is successively carried out within the same cluster, thekey idea is that the SIC can be flexibly implemented between any arbitraryusers to achieve efficient interference elimination. Based on the proposedframework, a sum rate maximization problem is formulated for jointly optimizingthe transmit beamforming and the SIC operations between users, subject to theSIC decoding conditions and users' minimal data rate requirements. To tacklethis highly-coupled mixed-integer nonlinear programming problem, an alternatingdirection method of multipliers-successive convex approximation (ADMM-SCA)algorithm is developed. The original problem is first reformulated into atractable biconvex augmented Lagrangian (AL) problem by handling the non-convexterms via SCA. Then, this AL problem is decomposed into two subproblems thatare iteratively solved by the ADMM to obtain the stationary solution. Moreover,to reduce the computational complexity and alleviate the parameterinitialization sensitivity of ADMM-SCA, a Matching-SCA algorithm is proposed.The intractable binary SIC operations are solved through an extendedmany-to-many matching, which is jointly combined with an SCA process tooptimize the transmit beamforming. The proposed Matching-SCA can converge to anenhanced exchange-stable matching that guarantees the local optimality.Numerical results demonstrate that: i) the proposed Matching-SCA algorithmachieves comparable performance and a faster convergence compared to ADMM-SCA;ii) the proposed generalized framework realizes scenario-adaptivecommunications and outperforms traditional multi-antenna NOMA approaches invarious communication regimes.

Cluster-Free NOMA Communications Towards Next Generation Multiple Access