Closed-Form Solution for Computationally Efficient Symbol-Level Precoding

We present a convex optimization based Symbol-Level Precoding (SLP) for sum power minimization and propose the low-latency closed-form algorithm to find a heuristic solution to the optimization problem. The technique exploits constructive interference at the multi-user MIMO systems and minimizes the sum power of the transmitted precoded signal per each symbol slot. As a result, the received signals gain extra Signal-to-Noise Ratio (SNR), which leads to the improved data rate and energy efficiency. We benchmark the low-complexity algorithm for solving the optimization technique against the conventional Fast Non-Negative Least Squares algorithm (NNLS). The demonstrated design of the SLP technique combined with the proposed closed-form algorithm has low computational complexity and fast processing time, which is applicable in low-latency high-throughput satellite communication systems.