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An Admm Algorithm for Peak Transmission Energy Minimization in Symbol-level Precoding

This paper considers symbol-level precoding (SLP) for the multiuser multiple-input single-output (MISO) downlink scenario. By exploiting symbol constellation information, SLP has the ability to achieve much better performance than traditional linear beamforming schemes. In this work, we propose an SLP design formulation under quadrature amplitude modulation (QAM) constellations. The objective of the design is to minimize the peak transmission energy over symbol time slots, while, at the same time, satisfying pre-specified symbol error probability (SEP) requirements of all the users. This kind of design can reduce the energy spread over symbol time. The resulting problem is a large-scale convex problem, and we develop an efficient alternating direction method of multipliers (ADMM) algorithm for the problem. Simulation results demonstrate that our proposed algorithm significantly outperforms some conventional linear beamforming schemes.