Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Dependent rounding and its applications to approximation algorithms
Journal of the ACM (JACM)
Network optimization and control
Foundations and Trends® in Networking
Downlink scheduling and resource allocation for OFDM systems
IEEE Transactions on Wireless Communications
Energy efficient management of two cellular access networks
ACM SIGMETRICS Performance Evaluation Review
Traffic-driven power saving in operational 3G cellular networks
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
Distributed interference compensation for wireless networks
IEEE Journal on Selected Areas in Communications
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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.