GENESIS: Green Energy Efficiency Optimization in Integrated Sensing and Communication Networks
Arianna Santamaria Penafiel, Md Sadman Siraj, Eirini Eleni Tsiropoulou, Symeon Papavassiliou · 2024
In the emerging landscape of Integrated Sensing and Communication (ISAC) networks, achieving energy efficiency while concurrently performing sensing and communication tasks remains challenging. This paper introduces the GENESIS framework, a novel solution that empowers User Equipment (UEs) to make informed decisions regarding their transmission power allocation, optimizing the energy efficiency of sensing, communication, and data reporting to the gNB (gNodeB) functions. Initially, a novel ISAC network paradigm is proposed, where the gNB employs rewards, such as monetary incentives, to motivate UEs to engage in sensing, data collection, and reporting within its coverage area based on the principles of Contract Theory. The proposed GENESIS framework integrates the incentive mechanism with an optimal resource management technique which facilitates UEs to make energy-efficient decisions that balance their dual roles of sensing and communication, distributedly, while maximizing overall energy efficiency. The resulting multi-variable resource management problem is formulated as a non-cooperative game, establishing the existence and uniqueness of a Nash Equilibrium. Through modeling and simulation, we demonstrate GENESIS benefits, showcasing its energy-efficient operation and rapid convergence to optimal operational points.