IRS-Assisted Cooperative Communication for Wireless-Powered Mobile Edge Computing Systems in Obstructed Environments

The rapid development of Internet of Things technology has led to a surge in demand for computationally intensive and low-latency services, posing significant challenges for resource-constrained wireless devices (WDs). Signal obstructions caused by buildings and complex geographical environments further degrade system performance, especially in obstructed environments. To address these challenges, we proposes a novel wireless-powered mobile edge computing (WP-MEC) system that integrates intelligent reflecting surfaces (IRS) and device-to-device (D2D) communication technologies to overcome signal blockage and enhance system performance. We use energy efficiency as the key metric for evaluating the system’s long-term performance and design a joint optimization problem that involves task offloading, transmission time, transmission power, IRS beamforming, and CPU frequency. To solve this problem, we apply Lyapunov optimization theory and design a cooperative communication optimization penalty dual decomposition (CCO-PDD) algorithm to efficiently tackle the complex scheduling and resource allocation challenges. Simulation results demonstrate that the proposed algorithm significantly improves system energy efficiency, resolves transmission blockage issues in obstructed environments, and effectively ensures the stability of user queues.