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Secure Rate-Splitting and RIS Beamforming with Untrusted Energy Harvesting Receivers

Hamid Reza Hashempour, Le-Nam Tran, Duy H. N. Nguyen, Hien Quoc Ngo

Abstract

We consider a reconfigurable intelligent surface (RIS)-assisted heterogeneous network comprising legitimate information-harvesting receivers (IHRs) and untrusted energy-harvesting receivers (UEHRs). A multi-antenna base station (BS) transmits confidential information to IHRs while ensuring sufficient energy transfer to UEHRs that may attempt eavesdropping. To enhance physical-layer security, we propose a secure rate-splitting multiple access (RSMA) scheme aided by a UAV-mounted RIS. The objective is to maximize fairness-based secrecy energy efficiency (SEE). Owing to the non-convexity of the formulated problem, we develop an alternating optimization framework that jointly designs the common message allocation, active precoders, and RIS phase shifts under transmit power and energy harvesting constraints, leveraging sequential convex approximation (SCA). Simulation results demonstrate the scalability of the proposed algorithm and its superior SEE performance compared to space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA) benchmarks.

Secure Rate-Splitting and RIS Beamforming with Untrusted Energy Harvesting Receivers

Abstract

We consider a reconfigurable intelligent surface (RIS)-assisted heterogeneous network comprising legitimate information-harvesting receivers (IHRs) and untrusted energy-harvesting receivers (UEHRs). A multi-antenna base station (BS) transmits confidential information to IHRs while ensuring sufficient energy transfer to UEHRs that may attempt eavesdropping. To enhance physical-layer security, we propose a secure rate-splitting multiple access (RSMA) scheme aided by a UAV-mounted RIS. The objective is to maximize fairness-based secrecy energy efficiency (SEE). Owing to the non-convexity of the formulated problem, we develop an alternating optimization framework that jointly designs the common message allocation, active precoders, and RIS phase shifts under transmit power and energy harvesting constraints, leveraging sequential convex approximation (SCA). Simulation results demonstrate the scalability of the proposed algorithm and its superior SEE performance compared to space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA) benchmarks.
Paper Structure (8 sections, 2 theorems, 37 equations, 4 figures, 3 algorithms)

This paper contains 8 sections, 2 theorems, 37 equations, 4 figures, 3 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Problem Formulation
  4. Optimal Allocation of Common Message Among IHRs
  5. Optimization of Common and Private Precoders
  6. RIS Reflection Phase Optimization
  7. Simulation Results
  8. Conclusions

Key Result

Proposition 1

The affine approximation of constraint 29f and 29g, $\forall k \in \mathcal{K}$ are given by: where $\mathbf{v}^H \triangleq \mathbf{g}_k^H \boldsymbol{\Theta} \mathbf{G}_b$ and $\Psi^{(t)}(\mathbf{u},x;\mathbf{h}) \triangleq \dfrac{2 \,\mathfrak{Re} \left\{ ( \mathbf{u}^{(t-1)})^H \mathbf{h} \mathbf{h}^H \mathbf{u} \right\} }{x^{(t-1)}} \;-\; \dfrac{\left | \mathbf{h}^H \mathbf{u}^{(t-1)} \

Figures (4)

  • Figure 1: System model of UAV-assisted RIS-RSMA network.
  • Figure 2: SEE versus $N_t$ for $P_{\max}=10$ dBm and $M=16$ compared with NOMA and SDMA benchmarks.
  • Figure 3: SEE versus $M$ for $N_t=4$ and different schemes.
  • Figure 4: SEE versus number of legitimate users ($K$) and UEHRs ($J$) for $P_{\max}=20$ dBm.

Theorems & Definitions (4)

  • Proposition 1
  • proof
  • Proposition 2
  • proof