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Self-Sustainable Active Reconfigurable Intelligent Surfaces for Anti-Jamming in Wireless Communications

Yang Cao, Wenchi Cheng, Jingqing Wang, Wei Zhang

TL;DR

The paper addresses anti-jamming in wireless networks by deploying a self-sustainable active RIS powered through TD-SWIPT energy harvesting. It develops a joint transmit/reflection beamforming design solved via a stochastic SSCA-based AO framework, deriving convex subproblems for $\tau$, $\mathbf{w}_1$, $\mathbf{w}_2$, and $\boldsymbol{\Theta}$ at each channel realization. A random waypoint Nakagami-$m$ fading model captures UE mobility with imperfect CSI for hostile nodes. Simulations show that the proposed BS-harvesting scheme outperforms passive RIS and no-RIS setups, achieving higher anti-jamming performance with fewer RIS elements and highlighting the trade-offs between transmit power, amplification budget, and path loss. The work demonstrates a practical pathway for deploying energy-self-sufficient active RIS in secure wireless systems.

Abstract

Wireless devices can be easily attacked by jammers during transmission, which is a potential security threat for wireless communications. Active reconfigurable intelligent surface (RIS) attracts considerable attention and is expected to be employed in anti-jamming systems for secure transmission to significantly enhance the anti-jamming performance. However, active RIS introduces external power load, which increases the complexity of hardware and restricts the flexible deployment of active RIS. To overcome these drawbacks, we design a innovative self-sustainable structure in this paper, where the active RIS is energized by harvesting energy from base station (BS) signals through the time dividing based simultaneous wireless information and power transfer (TD-SWIPT) scheme. Based on the above structure, we develop the BS harvesting scheme based on joint transmit and reflecting beamforming with the aim of maximizing the achievable rate of active RIS-assisted system, where the alternating optimization (AO) algorithm based on stochastic successive convex approximation (SSCA) tackles the nonconvex optimization problem in the scheme. Simulation results verified the effectiveness of our developed BS harvesting scheme, which can attain higher anti-jamming performance than other schemes when given the same maximum transmit power.

Self-Sustainable Active Reconfigurable Intelligent Surfaces for Anti-Jamming in Wireless Communications

TL;DR

The paper addresses anti-jamming in wireless networks by deploying a self-sustainable active RIS powered through TD-SWIPT energy harvesting. It develops a joint transmit/reflection beamforming design solved via a stochastic SSCA-based AO framework, deriving convex subproblems for , , , and at each channel realization. A random waypoint Nakagami- fading model captures UE mobility with imperfect CSI for hostile nodes. Simulations show that the proposed BS-harvesting scheme outperforms passive RIS and no-RIS setups, achieving higher anti-jamming performance with fewer RIS elements and highlighting the trade-offs between transmit power, amplification budget, and path loss. The work demonstrates a practical pathway for deploying energy-self-sufficient active RIS in secure wireless systems.

Abstract

Wireless devices can be easily attacked by jammers during transmission, which is a potential security threat for wireless communications. Active reconfigurable intelligent surface (RIS) attracts considerable attention and is expected to be employed in anti-jamming systems for secure transmission to significantly enhance the anti-jamming performance. However, active RIS introduces external power load, which increases the complexity of hardware and restricts the flexible deployment of active RIS. To overcome these drawbacks, we design a innovative self-sustainable structure in this paper, where the active RIS is energized by harvesting energy from base station (BS) signals through the time dividing based simultaneous wireless information and power transfer (TD-SWIPT) scheme. Based on the above structure, we develop the BS harvesting scheme based on joint transmit and reflecting beamforming with the aim of maximizing the achievable rate of active RIS-assisted system, where the alternating optimization (AO) algorithm based on stochastic successive convex approximation (SSCA) tackles the nonconvex optimization problem in the scheme. Simulation results verified the effectiveness of our developed BS harvesting scheme, which can attain higher anti-jamming performance than other schemes when given the same maximum transmit power.
Paper Structure (15 sections, 1 theorem, 48 equations, 9 figures, 2 algorithms)

This paper contains 15 sections, 1 theorem, 48 equations, 9 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Channel Model
  4. Signal Transmission Model
  5. Problem Formulation
  6. Power Consumption Model
  7. Problem Formulation
  8. Alternating Optimization
  9. Optimize $\tau$ And $\boldsymbol{\rm {w}}_{1,k}$
  10. Optimize the time dividing factor $\tau$
  11. Optimize the transmit beamforming vector $\boldsymbol{\rm {w}}_{1,k}$
  12. Optimize The Transmit Beamforming vector $\boldsymbol{\rm {w}}_{2,k}$
  13. Optimize The Reflecting Beamforming $\boldsymbol{\rm {\Theta}}$
  14. Numerical Simulations and Analysis
  15. Conclusions

Key Result

Theorem 1

The probability density function (PDF) of the RWP-based Nakagami-$m$ fading channel model is derived as follows: where $\gamma(\cdot)$ denotes the lower incomplete Gamma function. The moving range of the UE is given as $D_L\le r\le D_U$, where $D_L$ and $D_U$ represent maximum and minimum distances between the BS and the UE, respectively. The notations $B_n$, $\Upsilon_n$, and $N_T$ represent par

Figures (9)

  • Figure 1: The active RIS-assisted anti-jamming communication system.
  • Figure 2: The signal transmission stage according to the TD-SWIPT scheme.
  • Figure 3: Plane diagram of simulated active RIS-assisted anti-jamming system.
  • Figure 4: Achievable rate $R_{sum}$ versus the number of iterations.
  • Figure 5: Achievable rate $R_{sum}$ versus the number of REs $M$.
  • ...and 4 more figures

Theorems & Definitions (1)

  • Theorem 1