A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
The budgeted maximum coverage problem
Information Processing Letters
Approximation Algorithms for Maximum Coverage and Max Cut with Given Sizes of Parts
Proceedings of the 7th International IPCO Conference on Integer Programming and Combinatorial Optimization
The all-or-nothing multicommodity flow problem
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Combination can be hard: approximability of the unique coverage problem
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
A note on maximizing a submodular set function subject to a knapsack constraint
Operations Research Letters
Distributed Approximation of Cellular Coverage
OPODIS '08 Proceedings of the 12th International Conference on Principles of Distributed Systems
Partial information spreading with application to distributed maximum coverage
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Bandwidth allocation in cellular networks with multiple interferences
Proceedings of the 6th International Workshop on Foundations of Mobile Computing
Distributed approximation of cellular coverage
Journal of Parallel and Distributed Computing
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Cell planning includes planning a network of base stations providing a coverage of the service area with respect to current and future traffic requirements, available capacities, interference, and the desired quality-of-service. This paper studies cell planning under budget constraints through a very close-to-practice model. This problem generalizes several problems such as budgeted maximum coverage, budgeted unique coverage, and the budgeted version of the facility location problem. We present the first study of the budgeted cell planning problem. Our model contains capacities, non-uniform demands, and interference that are modeled by a penalty-based mechanism that may reduce the contribution of a base station to a client as a result of simultaneously covering this client by other base stations. We show that this very general problem is NP-hard to approximate and thus we define a restrictive version of the problem that covers all interesting practical scenarios. We show that although this variant remains NP-hard, it can be approximated within a factor of $\frac{e-1}{2e-1}$ of the optimum.