LAUSR

The densification of small cells in heterogeneous networks (HetNets) causes huge energy consumption and severe network interference. To fully exploit the potential of new network architecture, the cell selection (CS) in such HetNets should couple with reducing power consumption and network interference. To this end, we jointly perform cell activation and selection (CAS) to maximize the network energy efficiency (EE) under users’ long-term rate constraints. The formulated problem is in a mixed-integer fractional form and hard to tackle. We need to transform it into a parametric subtractive form, by which we reach its solution through a three-layer iterative algorithm. The first layer searches an EE parameter using a bisection method; the second layer alternately optimizes CAS indices; the third layer solves CS and cell activation (CA) problems using dual decomposition and fixed point iteration, respectively. At last, we give some complexity and convergence analyses for the designed algorithm, and investigate the impacts of different network parameters on system performance. The simulation results show that the CA introduced in CS is a good option to reduce energy consumption and network interference.