Multilayer Optimization of Heterogeneous Networks Using Grammatical Genetic Programming
用语法遗传编程为异构蜂窝网络设计控制启发式算法，同时优化小小区功率、宏小区占空比和用户调度，使下行速率比基准方法提高三倍。
Heterogeneous cellular networks are composed of macro cells (MCs) and small cells (SCs) in which all cells occupy the same bandwidth. Provision has been made under the third generation partnership project-long term evolution framework for enhanced intercell interference coordination (eICIC) between cell tiers. Expanding on previous works, this paper instruments grammatical genetic programming to evolve control heuristics for heterogeneous networks. Three aspects of the eICIC framework are addressed including setting SC powers and selection biases, MC duty cycles, and scheduling of user equipments (UEs) at SCs. The evolved heuristics yield minimum downlink rates three times higher than a baseline method, and twice that of a state-of-the-art benchmark. Furthermore, a greater number of UEs receive transmissions under the proposed scheme than in either the baseline or benchmark cases.