Abstract

This paper studies the energy optimization in a two-tier heterogeneous cloud radio access networks (H-CRAN), where remote radio head (RRH) tier is powered by mixed renewable energy sources and the grid source and high power node (HPN) tier is powered by conventional grid power. We formulate the resource allocation problem as a non-convex mixed-integer programming problem. To solve this problem, a hybrid-fiteness function evolutionary algorithm is proposed. The simulation results demonstrate that the proposed algorithm can increase the energy efficiency by up to of 26.1% and 12.6% over the baseline max reference signal received power (RSRP) and max signal-to-interference-plus-noise ratio(SINR) schemes.

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