2024/01/10 by Argha Sen, Sen, Argha, Bhupendra Pal +3
Computer Science · Engineering · #Software-Defined Networks and 5G #Advanced MIMO Systems Optimization #Green IT and Sustainability
paper · pdf · doi:10.48550/arxiv.2401.05329
In the landscape of next-generation cellular networks, a projected surge of over 12 billion subscriptions foreshadows a considerable upswing in the network's overall energy consumption. The proliferation of User Equipment (UE) drives this energy demand, urging 5G deployments to seek more energy-efficient methodologies. In this work, we propose SmartMME, as a pivotal solution aimed at optimizing Base Station (BS) energy usage. By harnessing and analyzing critical network states-such as UE connections, data traffic at individual UEs, and other pertinent metrics-our methodology intelligently orchestrates the BS's power states, making informed decisions on when to activate or deactivate the BS. This meticulous approach significantly curtails the network's overall energy consumption. In a bid to validate its efficiency, we seamlessly integrated our module into Network Simulator-3 (ns-3), conducting extensive testing to demonstrate its prowess in effectively managing and reducing net energy consumption. As advocates of collaborative progress, we've opted to open-source this module, inviting the engagement and feedback of the wider research community on GitHub.