OPTIMIZING INTEGRATED SENSING AND COMMUNICATION (ISAC)

Abstract

This report presents a comprehensive investigation into resource allocation strategies within Integrated Sensing and Communication (ISAC) systems, with a particular focus on optimizing antenna distribution between radar sensing and data transmission tasks. The study evaluates how beamforming can be utilized to control signal direction and improve overall system efficiency. To achieve this, two algorithmic approaches were implemented: a convex optimization method (CVX) for accurate and optimal antenna allocation under strict constraints, and a Greedy heuristic algorithm designed for faster computation under limited processing resources. The performance of both methods was evaluated through MATLAB-based simulations, analyzing their effectiveness under varying sensing and communication thresholds, power levels, and path loss conditions. The results highlight the trade-offs between computational complexity and solution accuracy, providing insight into the practical deployment of ISAC systems in real-world wireless networks. The report concludes with a discussion on possible improvements, including the integration of advanced multi-objective optimization techniques and adaptive algorithms for dynamic environments.