Low-Complexity Nonlinear Hybrid Precoding for Massive MIMO Broadcast Channels

Nonlinear hybrid precoding can approach capacity, but is highly computational. This paper investigates a low-complexity nonlinear hybrid precoding algorithm designed to maximize the achievable sum-rate of massive multiple-input multiple-output broadcast channels (MIMO-BC). We propose a closed-form solution for the analog precoding design to reduce the computational complexity of nonlinear hybrid precoding. The key idea is to transform the intractable constant modulus problem into an equivalent unconstrained problem by treating the phases as optimization variables, which can be efficiently solved using the Fletcher-Reeves conjugate gradient method. Simulation results show that the proposed algorithm achieves near-optimal sum-rate performance while maintaining computational efficiency, with complexity scaling linearly with the number of transmit antennas, making it highly competitive in massive MIMO systems.