A Selective Secure Precoding Framework for MU-MIMO Rate-Splitting Multiple Access Networks Under Limited CSIT

TL;DR

This paper introduces a secure precoding framework for MU-MIMO rate-splitting networks that optimizes secrecy performance under limited CSIT, addressing security heterogeneity and non-convex optimization challenges.

Contribution

It develops a novel robust precoding algorithm using LogSumExp approximation and eigenvalue solutions, extended to scenarios with limited CSIT, enhancing secure communication in MU-MIMO systems.

Findings

The proposed algorithm improves sum secrecy spectral efficiency.

Effective handling of limited CSIT scenarios with conditional average rate.

Validation shows superior performance over existing methods.

Abstract

In this paper, we propose a robust and adaptable secure precoding framework designed to encapsulate a intricate scenario where legitimate users have different information security: secure private or normal public information. Leveraging rate-splitting multiple access (RSMA), we formulate the sum secrecy spectral efficiency (SE) maximization problem in downlink multi-user multiple-input multiple-output (MIMO) systems with multi-eavesdropper. To resolve the challenges including the heterogeneity of security, non-convexity, and non-smoothness of the problem, we initially approximate the problem using a LogSumExp technique. Subsequently, we derive the first-order optimality condition in the form of a generalized eigenvalue problem. We utilize a power iteration-based method to solve the condition, thereby achieving a superior local optimal solution. The proposed algorithm is further extended to a more realistic scenario involving limited channel state information at the transmitter (CSIT). To effectively utilize the limited channel information, we employ a conditional average rate approach. Handling the conditional average by deriving useful bounds, we establish a lower bound for the objective function under the conditional average. Then we apply the similar optimization method as for the perfect CSIT case. In simulations, we validate the proposed algorithm in terms of the sum secrecy SE.