Energy Optimization and Coverage in 6G Wireless Communications Using Intelligent Reflecting Surfaces Under Dynamic Channel Conditions

Abstract

Energy efficiency and coverage optimization are key challenges in the development of sixth-generation (6G) wireless networks, particularly with the integration of Intelligent Reflecting Surfaces (IRS). Leveraging IRS technology can significantly enhance signal propagation and network performance, but optimizing their deployment under dynamic channel conditions remains a complex problem. This paper conducts an in-depth analysis of energy efficiency and coverage optimization in 6G networks utilizing IRS-assisted communication. We develop a novel mathematical framework that captures the intricate relationship between energy consumption and coverage enhancement in IRS-based systems operating under fluctuating channel conditions. Using stochastic geometry, we model the spatial distribution of IRS units and user equipment, while a tensor-based representation is employed to characterize the multi-dimensional channel state information. To adapt to time-varying wireless environments, we propose an adaptive phase-shift configuration protocol that dynamically adjusts IRS elements, resulting in a 43% improvement in energy efficiency compared to static configurations. Additionally, a deep reinforcement learning approach is integrated into our framework to optimize the balance between coverage extension and power consumption, considering both direct and IRS-reflected transmission paths. Extensive numerical simulations validate our theoretical insights, showing that the strategic deployment of IRS units based on our optimization model can expand coverage by 68% in urban environments while maintaining quality of service constraints. Moreover, we derive closed-form expressions for the probability of coverage under Rician fading conditions, incorporating the effects of hardware impairments and phase noise in IRS elements. These findings offer critical insights into the practical implementation of energy-efficient IRS deployments, laying the groundwork for future advancements in 6G cellular networks.