# Beamforming and Power Splitting Designs for AN-aided Secure Multi-user MIMO SWIPT Systems

## TL;DR

This paper proposes a joint beamforming, artificial noise, and power splitting optimization for secure multi-user MIMO SWIPT systems, introducing a low-complexity convex approximation method validated through simulations.

## Contribution

It develops a novel two-layer decomposition approach with a sequential parametric convex approximation for efficient, near-optimal solutions in secure MIMO SWIPT systems.

## Key findings

- SPCA method matches 1-D scheme performance
- Proposed schemes are robust under channel uncertainties
- Relaxation tightness confirmed by rank-one solutions

## Abstract

In this paper, an energy harvesting scheme for a multi-user multiple-input-multiple-output (MIMO) secrecy channel with artificial noise (AN) transmission is investigated. Joint optimization of the transmit beamforming matrix, the AN covariance matrix, and the power splitting ratio is conducted to minimize the transmit power under the target secrecy rate, the total transmit power, and the harvested energy constraints. The original problem is shown to be non-convex, which is tackled by a two-layer decomposition approach. The inner layer problem is solved through semi-definite relaxation, and the outer problem, on the other hand, is shown to be a single- variable optimization that can be solved by one-dimensional (1- D) line search. To reduce computational complexity, a sequential parametric convex approximation (SPCA) method is proposed to find a near-optimal solution. The work is then extended to the imperfect channel state information case with norm-bounded channel errors. Furthermore, tightness of the relaxation for the proposed schemes are validated by showing that the optimal solution of the relaxed problem is rank-one. Simulation results demonstrate that the proposed SPCA method achieves the same performance as the scheme based on 1-D but with much lower complexity.