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A Dual Belief-Driven Bayesian-Stackelberg Framework for Low-Complexity and Secure Near-Field ISAC Systems

Mehzabien Iqbal, Ahmad Y Javaid

TL;DR

This work tackles secure near-field ISAC in mmWave–THz regimes under dynamic channels and potential eavesdroppers by proposing a dual Bayesian–Stackelberg framework. It couples Adaptive Hybrid Node role switching with belief-driven sensing and beamforming to jointly optimize sensing, communication, and secrecy at low computational cost. Per-slot belief updates, leader–follower decisions, and meta-adaptation yield substantial secrecy improvements (up to ~35% gain) and high reliability (>98% success) across 28–410 GHz, with linear runtime overhead suitable for real-time deployment. The approach demonstrates scalable, secure ISAC operation for future 6G/7G networks and points to distributed architectures, AI-driven belief updates, and RIS-assisted extensions as promising directions.

Abstract

Ensuring robust security in near-field Integrated Sensing and Communication (ISAC) systems remains a critical challenge due to dynamic channel conditions, multi-eavesdropper threats, and the high computational burden of real-time optimization at mmWave and THz frequencies. To address these challenges, this paper introduces a novel Bayesian-Stackelberg framework that jointly optimizes sensing, beamforming, and communication. The dual-algorithm design integrates (i) Adaptive Hybrid Node Role Switching between secure transmission and cooperative jamming (ii) Belief-Driven Sensing and Beamforming for confidence based resource allocation. The proposed unified framework significantly improves robustness against attacks while preserving linear computational complexity. Simulation results across carrier frequencies ranging from 28 to 410 GHz demonstrate that the method achieves up to a 35% increase in secrecy rates and a success rate exceeding 98%, outperforming conventional communication systems with minimal runtime overhead. These findings underscore the scalability of belief-driven ISAC security solutions for low-complexity deployment in next generation communications.

A Dual Belief-Driven Bayesian-Stackelberg Framework for Low-Complexity and Secure Near-Field ISAC Systems

TL;DR

This work tackles secure near-field ISAC in mmWave–THz regimes under dynamic channels and potential eavesdroppers by proposing a dual Bayesian–Stackelberg framework. It couples Adaptive Hybrid Node role switching with belief-driven sensing and beamforming to jointly optimize sensing, communication, and secrecy at low computational cost. Per-slot belief updates, leader–follower decisions, and meta-adaptation yield substantial secrecy improvements (up to ~35% gain) and high reliability (>98% success) across 28–410 GHz, with linear runtime overhead suitable for real-time deployment. The approach demonstrates scalable, secure ISAC operation for future 6G/7G networks and points to distributed architectures, AI-driven belief updates, and RIS-assisted extensions as promising directions.

Abstract

Ensuring robust security in near-field Integrated Sensing and Communication (ISAC) systems remains a critical challenge due to dynamic channel conditions, multi-eavesdropper threats, and the high computational burden of real-time optimization at mmWave and THz frequencies. To address these challenges, this paper introduces a novel Bayesian-Stackelberg framework that jointly optimizes sensing, beamforming, and communication. The dual-algorithm design integrates (i) Adaptive Hybrid Node Role Switching between secure transmission and cooperative jamming (ii) Belief-Driven Sensing and Beamforming for confidence based resource allocation. The proposed unified framework significantly improves robustness against attacks while preserving linear computational complexity. Simulation results across carrier frequencies ranging from 28 to 410 GHz demonstrate that the method achieves up to a 35% increase in secrecy rates and a success rate exceeding 98%, outperforming conventional communication systems with minimal runtime overhead. These findings underscore the scalability of belief-driven ISAC security solutions for low-complexity deployment in next generation communications.
Paper Structure (20 sections, 23 equations, 5 figures, 2 tables, 2 algorithms)

This paper contains 20 sections, 23 equations, 5 figures, 2 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Architecture
  4. Network Model
  5. Near Field Antenna Arrays and Geometry, and RF Chains
  6. Near-Field MIMO Channel
  7. Signal Model, Secrecy Metrics, and Sensing Model
  8. Problem Formulation
  9. Proposed Unified Framework
  10. Bayesian–Stackelberg Framework and Adaptive Control
  11. Bayesian Belief Prediction and Update
  12. Leader Optimization and Policy Announcement
  13. Follower Role Selection and Cooperative Response
  14. Dual Updates and Meta-Adaptation
  15. Utility and Low-Complexity Objective
  16. ...and 5 more sections

Figures (5)

  • Figure 1: Dual belief driven Bayesian-Stackelberg System Model for Near-Field ISAC Systems
  • Figure 2: Comparison of maximum secrecy rate ($R_s$) and success rate (%) across four slots over high-frequency bands from 28–410 GHz
  • Figure 3: Total slot power versus HN distance at $f_c=100$ GHz.
  • Figure 4: Per-slot utilities of Baseline and Algorithm\ref{['alg:isac_BayStack']} across carrier frequencies
  • Figure 5: Per-slot utilities of Baseline and Algorithm\ref{['alg:adaptive']} across carrier frequencies