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Enhanced Physical Layer Security for Full-duplex Symbiotic Radio with AN Generation and Forward Noise Suppression

Chi Jin, Zheng Chang, Fengye Hu, Hsiao-Hwa Chen, Timo Hamalainen

TL;DR

This work tackles physical layer security in backscatter-based full-duplex symbiotic radio (FDSR) under proactive eavesdropping. It introduces a security framework combining artificial noise, forward noise suppression, pseudo-decoding, and phase control, solved via problem decomposition and alternating optimization. The main contributions include deriving optimum AN power allocation, optimal phase control rules, and a joint alternating optimization algorithm with low complexity, plus extensive simulations showing improved security throughput and attack mitigation over conventional AN. The results demonstrate robust security performance across diverse channel, reflection, and noise-processing settings, offering practical guidance for IoT backscatter security.

Abstract

Due to the constraints on power supply and limited encryption capability, data security based on physical layer security (PLS) techniques in backscatter communications has attracted a lot of attention. In this work, we propose to enhance PLS in a full-duplex symbiotic radio (FDSR) system with a proactive eavesdropper, which may overhear the information and interfere legitimate communications simultaneously by emitting attack signals. To deal with the eavesdroppers, we propose a security strategy based on pseudo-decoding and artificial noise (AN) injection to ensure the performance of legitimate communications through forward noise suppression. A novel AN signal generation scheme is proposed using a pseudo-decoding method, where AN signal is superimposed on data signal to safeguard the legitimate channel. The phase control in the forward noise suppression scheme and the power allocation between AN and data signals are optimized to maximize security throughput. The formulated problem can be solved via problem decomposition and alternate optimization algorithms. Simulation results demonstrate the superiority of the proposed scheme in terms of security throughput and attack mitigation performance.

Enhanced Physical Layer Security for Full-duplex Symbiotic Radio with AN Generation and Forward Noise Suppression

TL;DR

This work tackles physical layer security in backscatter-based full-duplex symbiotic radio (FDSR) under proactive eavesdropping. It introduces a security framework combining artificial noise, forward noise suppression, pseudo-decoding, and phase control, solved via problem decomposition and alternating optimization. The main contributions include deriving optimum AN power allocation, optimal phase control rules, and a joint alternating optimization algorithm with low complexity, plus extensive simulations showing improved security throughput and attack mitigation over conventional AN. The results demonstrate robust security performance across diverse channel, reflection, and noise-processing settings, offering practical guidance for IoT backscatter security.

Abstract

Due to the constraints on power supply and limited encryption capability, data security based on physical layer security (PLS) techniques in backscatter communications has attracted a lot of attention. In this work, we propose to enhance PLS in a full-duplex symbiotic radio (FDSR) system with a proactive eavesdropper, which may overhear the information and interfere legitimate communications simultaneously by emitting attack signals. To deal with the eavesdroppers, we propose a security strategy based on pseudo-decoding and artificial noise (AN) injection to ensure the performance of legitimate communications through forward noise suppression. A novel AN signal generation scheme is proposed using a pseudo-decoding method, where AN signal is superimposed on data signal to safeguard the legitimate channel. The phase control in the forward noise suppression scheme and the power allocation between AN and data signals are optimized to maximize security throughput. The formulated problem can be solved via problem decomposition and alternate optimization algorithms. Simulation results demonstrate the superiority of the proposed scheme in terms of security throughput and attack mitigation performance.
Paper Structure (22 sections, 57 equations, 9 figures, 1 table)

This paper contains 22 sections, 57 equations, 9 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. Attack and Defense Processes in the Primary System
  5. Attack and Defense Process in Secondary System
  6. Security Transmission Problem
  7. Proposed Approach
  8. Optimum AN Power Allocation
  9. Optimum Phase Control
  10. Joint Optimization
  11. Simulation Results
  12. Impacts of Transmission Power $P_A$
  13. Impacts of Transmission Power $P_E$
  14. Impacts of Constraint $\gamma^{th}_P$
  15. Impacts of Decoding / Noise-cancel Factor $\lambda$
  16. ...and 7 more sections

Figures (9)

  • Figure 1: FDSR system.
  • Figure 2: Pseudo-decoding process for signal $z$.
  • Figure 3: Security throughput, optimum signal power, and DAR versus the transmission power $P_A$.
  • Figure 4: Security throughput, optimum signal power, and DER versus the transmission power $P_E$.
  • Figure 5: Security throughput versus the SNR constraint $\gamma^{th}_P$.
  • ...and 4 more figures