Distributed base station activation for energy-efficient operation of cellular networks

Dynamic base station activation (DBA) has recently emerged as a viable solution for reducing energy consumption in cellular networks. While most of the works on this topic focused on centralized decision making algorithms, in this paper we investigate distributive solutions. These solutions are particularly desirable due to importance of self-organization and self-optimization in future cellular networks. The goal of DBA is to achieve an optimal trade-off between network operator's revenue and operational cost while guaranteeing coverage for network users. The problem is posed as a network utility maximization aiming to find the optimal activation schedule of each base station. Using Lagrangian duality, the problem is decomposed into smaller subproblems, where each subproblem is solved locally at its associated base station. Controlled message passing among base stations ensures convergence to the global optimal solution. Moreover, this general solution is further extended to capture the combinatorial nature of DBA. Finally, numerical results are provided to demonstrate the behavior of our solution in terms of utility and cost trade-off and convergence in some example network scenarios.