Anti-jamming 5G Sub-6GHz communications
Anti-jamming mechanisms are critically important for 5G communications given the increasing reliance on wireless connectivity in mission-critical and safety-sensitive applications such as autonomous driving, remote healthcare, industrial automation, and military operations. While 5G offers unprecedented data rates, ultra-low latency, and massive device connectivity, its wireless nature makes it inherently vulnerable to deliberate interference from jammers, which can disrupt links, degrade quality of service, or even cause complete outages. Ensuring robust, anti-jamming communication is therefore essential not only for maintaining service reliability and user experience but also for protecting the integrity and resilience of critical infrastructure enabled by 5G and beyond.
In this demonstration, we present a real-time anti-jamming MIMO-OFDM wireless communication system consisting of a transmitter, a receiver, and a wideband high-power radio jammer. The centerpiece of our design is a novel physical layer (PHY) architecture at the receiver, which is capable of mitigating strong jamming signals and reliably recovering the desired signal—even without prior knowledge of the jammer’s waveform or characteristics. Using National Instruments (NI) USRP devices, we demonstrate that robust real-time wireless communication between a transmitter and receiver can be sustained in the presence of diverse wideband, high-power jamming attacks, thereby validating the effectiveness and practicality of our anti-jamming design.
Anti-jamming 5G mmWave communications
Reliable 5G millimeter-wave (mmWave) communications are essential for supporting bandwidth-intensive and latency-sensitive applications such as immersive extended reality (XR), autonomous vehicles, and industrial automation. However, ensuring reliability in mmWave systems remains challenging due to their inherent susceptibility to radio interference, blockage, and intentional jamming attacks. These disruptions can severely degrade link quality, compromise user experience, and undermine the robustness of mission-critical services.
To address these challenges, this project presents a joint analog–digital beamforming scheme for 5G mmWave receivers that enables robust data packet decoding in the presence of strong jamming signals. The proposed design combines two complementary techniques:
Online-learning Bayesian optimization for analog beamforming: This framework dynamically adapts the analog beam direction to maximize signal quality while suppressing interference, even under rapidly changing wireless conditions.
Modified Minimum Mean Square Error (M-MMSE) digital detection: At the digital baseband stage, this detector further mitigates residual interference by optimally balancing noise suppression and signal recovery.
By integrating these two techniques, the receiver can effectively suppress jamming in both the analog and digital domains, providing enhanced resilience and significantly improving decoding performance under adversarial conditions. This cross-layer beamforming strategy allows the system to leverage fast analog adaptation with intelligent digital processing, thereby achieving both robustness and efficiency.
We have developed a 28 GHz over-the-air (OTA) testbed prototype to validate the proposed scheme under realistic conditions. Extensive experimental evaluations across diverse scenarios demonstrate that the system maintains high decoding reliability even under targeted jamming, highlighting its potential for practical deployment in future 5G and beyond networks.
Key features of the proposed system include:
joint analog–digital beamforming for multi-domain interference suppression,
online-learning frameworks for adaptive beam selection,
real-time resilience against jamming attacks, and
comprehensive OTA evaluation on a mmWave testbed.