Dfrc System Achieves Maximum Sum Rate with Movable Antenna Optimisation

Researchers are increasingly focused on bolstering the security of wireless communications alongside radar functionality, and a new study by Ran Yang, Ning Wei, and Zheng Dong et al from the University of Electronic Science and Technology of China and Shandong University presents a significant advance in this field. Their work investigates a dual-functional radar-communication system utilising movable antenna technology to flexibly optimise wireless channels and enhance security, a crucial development given growing concerns around signal interception. By jointly optimising beamforming, filtering, and antenna placement, while accounting for both radar performance and transmission covertness, the team demonstrates a substantial improvement in achievable data rates and a superior balance between communication and radar capabilities compared to existing methods.

Secure DFRC via Optimised Antenna Placement, ensuring robust

The team achieved this by first reformulating a complex optimisation problem using a Lagrangian dual transformation, making it more manageable for computational analysis. Subsequently, an efficient block coordinate descent (BCD) algorithm was developed, integrating sophisticated techniques such as semidefinite relaxation (SDR), projected gradient descent (PGD), Dinkelbach transformation, and successive convex approximation (SCA) to solve the resulting problem. For scenarios involving colluding Willies, the research establishes the minimum detection error probability (DEP) by characterising the optimal detection statistic, which is proven to follow a generalized Erlang distribution, a key innovation in understanding detection limitations. This allowed the scientists to then formulate a minimum mean square error (MMSE)-based algorithm specifically designed to address the challenges posed by colluding detection attempts.
Experiments show that this proposed method significantly improves the covert sum rate, enabling more secure data transmission in DFRC systems. Simulation results demonstrate a superior balance between communication and radar performance when compared to existing benchmark schemes, highlighting the practical benefits of this approach. The work opens avenues for applications in emerging technologies like smart grids, unmanned aerial vehicles (UAVs), and the Industrial Internet of Things (IIoT), where secure and reliable data transmission is paramount. Furthermore, the use of movable antennas, capable of millimetre-level positioning accuracy, up to 0.05mm as demonstrated in prior work, allows for dynamic reconfiguration of wireless channels, mitigating the impact of fading and enhancing overall system performance.

This research not only advances the theoretical understanding of secure DFRC systems but also provides a practical framework for implementation. The comprehensive complexity analysis conducted by the researchers ensures the feasibility of the proposed algorithms, paving the way for real-world deployment. By concealing the very act of transmission, this system offers a higher level of security than traditional methods focused solely on encrypting data, addressing a critical vulnerability in modern wireless communication networks. The. Experiments considered multiple Willies operating in both non-colluding and colluding modes, providing a comprehensive analysis of security implications.

This work addresses a critical need for enhanced security in emerging 6G mobile networks, particularly for applications like smart grids and the Industrial Internet of Things. For non-colluding Willies, researchers employed a Lagrangian dual transformation to simplify a challenging optimization problem. Subsequently, an efficient block coordinate descent (BCD) algorithm was developed, integrating semidefinite relaxation (SDR), projected gradient descent (PGD), Dinkelbach transformation, and successive convex approximation (SCA) techniques. This sophisticated algorithm successfully tackles the resulting complex problem, demonstrating a significant advancement in optimization methodologies.

The team’s approach allows for precise control over both radar and communication functionalities within the same system, maximizing efficiency and performance. Investigations into colluding Willies yielded the derivation of the minimum detection error probability (DEP), characterized by an optimal detection statistic proven to follow the generalized Erlang distribution. A minimum mean square error (MMSE)-based algorithm was then developed to address the colluding detection problem, offering a robust solution against coordinated eavesdropping attempts. Measurements confirm that this algorithm effectively minimizes the risk of detection, enhancing the overall security of the DFRC system.

Simulation results demonstrate a significant improvement in the covert sum rate achieved by the proposed method. Tests prove the proposed method achieves a superior balance between communication and radar performance compared with existing benchmark schemes. The breakthrough delivers the potential for covertly transmitting information while maintaining robust radar functionality. The research highlights the benefits of movable antennas, achieving an antenna positioning accuracy of up to 0.05mm in prototype systems, and paving the way for future advancements in secure and efficient wireless communication. Data shows this unified design framework offers a compelling solution for addressing the growing security concerns in modern wireless networks.

DFRC Optimisation via Advanced Algorithm Design is crucial

Scientists have demonstrated a novel approach to secure dual-functional radar-communication (DFRC) systems utilising movable antennas. This research focused on maximising the achievable sum rate of communication while simultaneously satisfying radar signal-to-noise ratio requirements and maintaining transmission covertness, considering both non-colluding and colluding scenarios for multiple Willis. A key contribution lies in the development of an efficient block coordinate descent (BCD) algorithm, integrating techniques such as semidefinite relaxation, projected gradient descent, Dinkelbach transformation, and successive convex approximation, to solve the complex optimisation problem for non-colluding Willis. Furthermore, researchers derived the minimum detection error probability for colluding Willis by characterising the optimal detection statistic, which was proven to follow a generalised Erlang distribution, and subsequently proposed a minimum mean square error (MMSE)-based algorithm to address the colluding detection problem.

Simulation results confirm that the proposed method significantly improves the covert sum rate and achieves a superior balance between communication and radar performance when compared to existing benchmark schemes, particularly in scenarios with multiple Willis. The effectiveness of flexible antenna movement in enhancing transmission covertness was also highlighted, with performance gains being more pronounced in colluding scenarios. The authors acknowledge that the complexity of the proposed algorithm increases with the number of Willis, potentially limiting its scalability for very large networks. Future research directions could explore distributed or decentralised algorithms to reduce computational burden and enhance the system’s adaptability to dynamic environments. Overall, this work underscores the potential of movable antennas and offers a promising solution for future covert-aware 6G wireless networks, demonstrating a substantial advancement in secure wireless communication and radar integration.