Energy Group-Buying with Loading Sharing for Green Cellular Networks
Jie Xu, Lingjie Duan, Rui Zhang

TL;DR
This paper introduces a collaborative energy purchasing and load sharing strategy for multiple mobile network operators to reduce energy costs by jointly optimizing their energy procurement and wireless traffic management.
Contribution
It proposes a novel energy group buying approach with load sharing, using stochastic programming and Nash bargaining for different ownership scenarios.
Findings
Joint optimization reduces energy costs significantly.
Load sharing enables more BSs to enter sleep mode.
Nash bargaining ensures fair cost sharing.
Abstract
In the emerging hybrid electricity market, mobile network operators (MNOs) of cellular networks can make day-ahead energy purchase commitments at low prices and real-time flexible energy purchase at high prices. To minimize electricity bills, it is essential for MNOs to jointly optimize the day-ahead and real-time energy purchase based on their time-varying wireless traffic load. In this paper, we consider two different MNOs coexisting in the same area, and exploit their collaboration in both energy purchase and wireless load sharing for energy cost saving. Specifically, we propose a new approach named energy group buying with load sharing, in which the two MNOs are aggregated as a single group to make the day-ahead and real-time energy purchase, and their base stations (BSs) share the wireless traffic to maximally turn lightly-loaded BSs into sleep mode. When the two MNOs belong to the…
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