Power Allocation Strategies for Secure Spatial Modulation

TL;DR

This paper proposes efficient power allocation strategies for secure spatial modulation networks, introducing a convex optimization method and a low-complexity analytic solution to enhance secrecy rate performance across different SNR regions.

Contribution

It develops a novel approximate secrecy rate expression and two power allocation methods, one convex optimization-based and one low-complexity analytic, improving security performance in spatial modulation.

Findings

The convex optimization method achieves near-optimal secrecy rate performance.

The low-complexity Max-P-SAN method outperforms in low and medium SNR regions.

Proposed methods significantly reduce computational complexity while maintaining high security performance.

Abstract

In secure spatial modulation (SM) networks, power allocation (PA) strategies are investigated in this paper under the total power constraint. Considering that there is no closed-form expression for secrecy rate (SR), an approximate closed-form expression of SR is presented, which is used as an efficient metric to optimize PA factor and can greatly reduce the computation complexity. Based on this expression, a convex optimization (CO) method of maximizing SR (Max-SR) is proposed accordingly. Furthermore, a method of maximizing the product of signal-to-leakage and noise ratio (SLNR) and artificial noise-to-leakage-and noise ratio (ANLNR) (Max-P-SAN) is proposed to provide an analytic solution to PA with extremely low-complexity. Simulation results demonstrate that the SR performance of the proposed CO method is close to that of the optimal PA strategy of Max-SR with exhaustive search and better than that of Max-P-SAN in the high signal-to-noise ratio (SNR) region. However, in the low and medium SNR regions, the SR performance of the proposed Max-P-SAN slightly exceeds that of the proposed CO.