IRS-Assisted Physical Layer Security in MIMO-NOMA Networks

In this letter, we propose deploying the intelligent reflecting surface (IRS) to enhance the physical layer security in non-orthogonal multiple access (NOMA). The secrecy sum-rate of IRS-assisted multiple-input multiple-output (MIMO) NOMA is maximized in the presence of an eavesdropper. Because of the discrete unit-modulus constraint and the nonconvex property, the secrecy sum-rate maximization problem is hard to solve. We reformulate the original problem into an equivalent parameterized optimization using rotation matrices and apply the particle swarm algorithm for global optimization. Simulation results verify that the performance of the proposed algorithm is close to the secrecy capacity of the channel, realized by exhaustive search, and outperforms other methods like alternating optimization and zero-forcing in terms of complexity and achievable rates.