During the past decades, mobile communication is in the vigorous development, where the cell planning problem (CPP) is one of impressive research issues. CPP has been proved to be NP-Complete, and many works develop intelligent heuristic search strategies to solve it. Among many factors to affect the cell planning, the major one is the signaling cost, where the location management is critical to the cost. In this paper, we focus on how to tackle CPP such that the signaling cost can be minimized. We adopt a meta-heuristic iterative search algorithm, Tabu Search (TS), to deal with the cell planning issue for the base station and propose novel designs to improve the TS capability, including initialization and neighbor swap strategy. The simulation results reveal that our TS outperforms traditional TS, genetic algorithms, and several previous works in CPP.
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