In this paper, we study a multiple-input-multiple-output (MIMO) non-orthogonal multiple access (NOMA) downlink system, where a base station employs beamforming to transmit multiple data streams simultaneously to a central user and a cell-edge user. Over each beam, the orthogonal frequency division multiplexing (OFDM) modulated signals intended for both users are superimposed and then transmitted. Because of beamforming and OFDM modulation, the central user may have weaker beams compared with the cell-edge user. This causes the unsuccessful successive interference cancellation (SIC). To solve this problem, we derive the necessary and sufficient conditions to ensure the successful SIC for arbitrary beamforming matrices. Based on these conditions, we design a specialized beamforming structure where signals over weak beams can be orthogonally separated from those over strong ones. We propose that joint encoding and decoding are applied to signals over weak beams and similarly to those over strong ones. To optimize the beamforming matrices, we propose a constrained convex concave procedure based algorithm and a matrix fractional programming based algorithm. It is verified through simulation results that the proposed scheme performs better than the conventional OFDM-NOMA scheme.

To combine the orthogonal frequency division multiplexing (OFDM) modulation with non-orthogonal multiple access (NOMA) technique, it is required to ensure the successful successive interference cancellation procedure. Because of the fast Fourier transform (FFT) and inverse FFT employed at the OFDM transceivers, the central user may have weak subcarriers and the cell-edge user may have strong subcarriers. In this paper, we propose that for the central or cell-edge user, signals over the weak (strong) subcarriers are jointly encoded and decoded. Our objective is to maximize the weighted sum average achievable rates at both the central and cell-edge users through power allocation optimization. To solve the optimization problem, we propose a constrained convex-concave procedure (CCCP) based locally optimal solution, a Lagrangian dual transformation based locally optimal solution, and a prime decomposition based near-optimal solution. The prime decomposition based algorithm, which solves the problem based on water-filling, has extremely low computational complexity. It is shown through simulation results that the proposed scheme outperforms the conventional OFDM-NOMA scheme. Furthermore, it is found that the results obtained by the CCCP based solution, Lagrangian dual transformation based solution, and prime decomposition based solution match one another.

This article considers the problem of prescribed performance control for a class of affine nonlinear systems with state constraints. Fuzzy logic systems (FLSs) are employed to cope with unknown nonlinear functions. In addition, an additive transformation and one-to-one mapping method are introduced to handle the control problem of nonlinear systems with full-state constraints. Then, based on adaptive backstepping control, we develop a new prescribed performance adaptive fuzzy control method, which not only makes the tracking error be constrained within the prescribed range but also ensures the other state variables do not violate the predefined constraints. The simulation example verify the feasibility of the control method.