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Enhancing Physical Layer Security in Cognitive Radio-Enabled NTNs with Beyond Diagonal RIS

Wali Ullah Khan, Chandan Kumar Sheemar, Eva Lagunas, Symeon Chatzinotas

TL;DR

The work addresses secure communication in a cognitive radio-enabled multilayer NTN where a transmissive BD-RIS-mounted UAV acts as the secondary transmitter under a HAPS-based primary transmitter, with secrecy rate defined as $R_{ ext{sec}} = [\log_2(1+\\gamma_s) - \\log_2(1+\\gamma_e)]^+$ under an interference constraint $|\\mathbf{g}\\mathbf{\\Phi}|^2 P_s \le I_{ ext{th}}$. An alternating-optimization framework decouples the problem into a power-allocation subproblem and a phase-shift-design subproblem, solving the latter on the Stiefel manifold. A closed-form-like power rule $P_s^* = \min\left( \dfrac{I_{ ext{th}}}{|\\mathbf{g}\\mathbf{\\Phi}|^2}, P_{ ext{max}} \right)$ is derived for favorable channel conditions, while BD-RIS phase shifts are obtained via gradient-based manifold optimization with updates on the BD-RIS unitary constraint. Numerical results demonstrate BD-RIS’s secrecy-rate gains over diagonal RIS and show substantial improvements with larger BD-RIS size and relaxed interference constraints, highlighting the practical potential of BD-RIS for secure multi-layer NTNs.

Abstract

Beyond diagonal reconfigurable intelligent surfaces (BD-RIS) have emerged as a transformative technology for enhancing wireless communication by intelligently manipulating the propagation environment. This paper explores the potential of BD-RIS in improving cognitive radio enabled multilayer non-terrestrial networks (NTNs). It is assumed that a high-altitude platform station (HAPS) has set up the primary network, while an uncrewed aerial vehicle (UAV) establishes the secondary network in the HAPS footprint. We formulate a joint optimization problem to maximize the secrecy rate by optimizing BD-RIS phase shifts and the secondary transmitter power allocation while controlling the interference temperature from the secondary network to the primary network. To solve this problem efficiently, we decouple the original problem into two sub-problems, which are solved iteratively by relying on alternating optimization. Simulation results demonstrate the effectiveness of BD-RIS in cognitive radio-enabled multilayer NTNs to accommodate the secondary network while satisfying the constraints imposed from the primary network.

Enhancing Physical Layer Security in Cognitive Radio-Enabled NTNs with Beyond Diagonal RIS

TL;DR

The work addresses secure communication in a cognitive radio-enabled multilayer NTN where a transmissive BD-RIS-mounted UAV acts as the secondary transmitter under a HAPS-based primary transmitter, with secrecy rate defined as under an interference constraint . An alternating-optimization framework decouples the problem into a power-allocation subproblem and a phase-shift-design subproblem, solving the latter on the Stiefel manifold. A closed-form-like power rule is derived for favorable channel conditions, while BD-RIS phase shifts are obtained via gradient-based manifold optimization with updates on the BD-RIS unitary constraint. Numerical results demonstrate BD-RIS’s secrecy-rate gains over diagonal RIS and show substantial improvements with larger BD-RIS size and relaxed interference constraints, highlighting the practical potential of BD-RIS for secure multi-layer NTNs.

Abstract

Beyond diagonal reconfigurable intelligent surfaces (BD-RIS) have emerged as a transformative technology for enhancing wireless communication by intelligently manipulating the propagation environment. This paper explores the potential of BD-RIS in improving cognitive radio enabled multilayer non-terrestrial networks (NTNs). It is assumed that a high-altitude platform station (HAPS) has set up the primary network, while an uncrewed aerial vehicle (UAV) establishes the secondary network in the HAPS footprint. We formulate a joint optimization problem to maximize the secrecy rate by optimizing BD-RIS phase shifts and the secondary transmitter power allocation while controlling the interference temperature from the secondary network to the primary network. To solve this problem efficiently, we decouple the original problem into two sub-problems, which are solved iteratively by relying on alternating optimization. Simulation results demonstrate the effectiveness of BD-RIS in cognitive radio-enabled multilayer NTNs to accommodate the secondary network while satisfying the constraints imposed from the primary network.

Paper Structure

This paper contains 7 sections, 39 equations, 4 figures.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. Proposed Solution
  4. Power Allocation
  5. Phase Shift Matrix Design
  6. Numerical Results
  7. Conclusion

Figures (4)

  • Figure 1: System model.
  • Figure 2: Number of iterations versus achievable secrecy rate of the system, considering $P_{\text{max}}=20$ dBm and $I_{\text{th}}=10^{-5}$.
  • Figure 3: Available power of UAV versus achievable secrecy rate of the system considering different interference temperatures, considering $M=32$.
  • Figure 4: Number of reconfigurable elements versus achievable secrecy rate of the system considering different transmit power of UAV, considering $I_{\text{th}}=10^{-5}$.