PROJECT TITLE :

Active Base Station Set Optimization for Minimal Energy Consumption in Green Cellular Networks

ABSTRACT:

To decrease probably harmful effects to the atmosphere and cut back prices of cellular network operators, the exploration of energy saving is vital. In this paper, we tend to streamline the subsequent energy consumption minimization (ECM) drawback: “how to pick out the tiniest set of active base stations (BSs) which will preserve the standard of service (the minimum knowledge rate) required by the users.” Since the ECM drawback belongs to the sector of integer programming and is NP-hard, we have a tendency to propose 2 low-complexity approximation algorithms that yield performance guarantees: the iterative minimal set cowl algorithm and therefore the iterative maximal coverage (IMC) algorithm. Moreover, by leveraging the submodularity theory, we have a tendency to establish the performance certain of the IMC algorithm. Finally, the computational complexity of our proposed algorithms is analyzed, and a simulation platform is developed to guage the amount of active BSs of proposed approaches. The numerical results demonstrate that our proposed algorithms outperform the traditional counterpart.