Sensing for Jamming in ISAC: Beam Scanning and Beamforming Optimization

The development of wireless technology enables numerous applications of remote-controlled devices (e.g., unmanned aerial vehicles), yet their intrusion poses significant threats to restricted areas, including military bases, airports, and private spaces belonging to individuals and organizations. To effectively counter the intruders, we propose a novel sensing assisted jamming (SAJA) scheme in two-stage transmission protocol, where we are the first to employ beam scanning to enhance the jamming gain to neutralize intruders. In the first stage, we determine the number of sensing beams <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> for detecting intruders. We show that a larger <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> leads to a more accurate angle range, thus enabling a higher jamming beam gain. In the second stage, robust jamming beamforming is designed to disable the intruders within the estimated angle range. The problem facing a single intruder is already non-convex, and we decouple it into two subproblems and develop algorithms for both single- and multi-intruder scenarios. In single-intruder scenarios, we first derive the closed-form expression for robust beamforming design with fixed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i>, and then apply the bisection search method to determine the minimum <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i>. Facing multiple possible intruders, we further design a multi-round anti-intruder algorithm to address power insufficiency. In each round, we check the problem feasibility with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> = <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L_max</i> (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L_max</i> is the maximum number of sensing beams) and use a jamming-to-noise-ratio based method to selectively target intruders until the problem is feasible. Furthermore, we derive a semi-closed-form solution to the robust jamming beamforming vector using Lagrange duality theory. Finally, simulation results validate the effectiveness and robustness of the proposed SAJA scheme against existing schemes.