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Resilient-By-Design Framework for MIMO-OFDM Communications under Smart Jamming

Vlad C. Andrei, Aladin Djuhera, Xinyang Li, Ullrich J. Mönich, Holger Boche, Walid Saad

TL;DR

The paper addresses anti-jamming in 6G-like MIMO-OFDM uplinks by introducing a sensing-assisted, resilience-by-design framework that uses DoA information to form a surrogate noise covariance $\widetilde{C}_{z,nk}$ and avoid assuming a precise adversary model. It integrates the surrogate covariance into a joint optimization of scheduling, beamforming and power via an iterative water-filling approach, and provides a scalable two-step approximation to the worst-case jamming problem. Results show strong resilience against worst-case and barrage jamming, with performance approaching full jammer knowledge using only DoA information, across varying antenna counts, jamming powers, and user numbers. This framework enables preemptive physical-layer resilience by leveraging sensing data, with practical scalability and clear avenues for field validation.

Abstract

Native jamming mitigation is essential for addressing security and resilience in future 6G wireless networks. In this paper a resilient-by-design framework for effective anti-jamming in MIMO-OFDM wireless communications is introduced. A novel approach that integrates information from wireless sensing services to develop anti-jamming strategies, which do not rely on any prior information or assumptions on the adversary's concrete setup, is explored. To this end, a method that replaces conventional approaches to noise covariance estimation in anti-jamming with a surrogate covariance model is proposed, which instead incorporates sensing information on the jamming signal's directions-of-arrival (DoAs) to provide an effective approximation of the true jamming strategy. The study further focuses on integrating this novel, sensing-assisted approach into the joint optimization of beamforming, user scheduling and power allocation for a multi-user MIMO-OFDM uplink setting. Despite the NP-hard nature of this optimization problem, it can be effectively solved using an iterative water-filling approach. In order to assess the effectiveness of the proposed sensing-assisted jamming mitigation, the corresponding worst-case jamming strategy is investigated, which aims to minimize the total user sum-rate. Experimental simulations eventually affirm the robustness of our approach against both worst-case and barrage jamming, demonstrating its potential to address a wide range of jamming scenarios. Since such an integration of sensing-assisted information is directly implemented on the physical layer, resilience is incorporated preemptively by-design.

Resilient-By-Design Framework for MIMO-OFDM Communications under Smart Jamming

TL;DR

The paper addresses anti-jamming in 6G-like MIMO-OFDM uplinks by introducing a sensing-assisted, resilience-by-design framework that uses DoA information to form a surrogate noise covariance and avoid assuming a precise adversary model. It integrates the surrogate covariance into a joint optimization of scheduling, beamforming and power via an iterative water-filling approach, and provides a scalable two-step approximation to the worst-case jamming problem. Results show strong resilience against worst-case and barrage jamming, with performance approaching full jammer knowledge using only DoA information, across varying antenna counts, jamming powers, and user numbers. This framework enables preemptive physical-layer resilience by leveraging sensing data, with practical scalability and clear avenues for field validation.

Abstract

Native jamming mitigation is essential for addressing security and resilience in future 6G wireless networks. In this paper a resilient-by-design framework for effective anti-jamming in MIMO-OFDM wireless communications is introduced. A novel approach that integrates information from wireless sensing services to develop anti-jamming strategies, which do not rely on any prior information or assumptions on the adversary's concrete setup, is explored. To this end, a method that replaces conventional approaches to noise covariance estimation in anti-jamming with a surrogate covariance model is proposed, which instead incorporates sensing information on the jamming signal's directions-of-arrival (DoAs) to provide an effective approximation of the true jamming strategy. The study further focuses on integrating this novel, sensing-assisted approach into the joint optimization of beamforming, user scheduling and power allocation for a multi-user MIMO-OFDM uplink setting. Despite the NP-hard nature of this optimization problem, it can be effectively solved using an iterative water-filling approach. In order to assess the effectiveness of the proposed sensing-assisted jamming mitigation, the corresponding worst-case jamming strategy is investigated, which aims to minimize the total user sum-rate. Experimental simulations eventually affirm the robustness of our approach against both worst-case and barrage jamming, demonstrating its potential to address a wide range of jamming scenarios. Since such an integration of sensing-assisted information is directly implemented on the physical layer, resilience is incorporated preemptively by-design.
Paper Structure (12 sections, 20 equations, 2 figures, 2 algorithms)

This paper contains 12 sections, 20 equations, 2 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model and Problem Statement
  3. Proposed Approach
  4. Resilient-by-Design Transceivers
  5. Worst-Case Jamming Strategy
  6. Simulation Results and Analysis
  7. Wireless Setup and Methodology
  8. Impact of Number of Antennas
  9. Impact of Jamming Power
  10. Impact of Jamming DoAs
  11. Impact of Number of Users
  12. Conclusions

Figures (2)

  • Figure 1: Qualitative rendering of the considered scenario.
  • Figure 2: Simulation results for all considered scenarios.