High-resolution cell breathing for improving energy efficiency of Ultra-Dense HetNets

The gap between the stable system resource supply and the traffic load (i.e, the demand) with temporal fluctuations and spatial disparities results in deficiency in the system resource (e.g, power and spectrum resources) utility in cellular networks. To bridge the variant gap, cell breathing schemes are adopted in prior arts, which mainly focus on the temporal variance. Therefore, there is every reason to further explore the improvement room in terms of efficiency in the system resource utilization of cell breathing, jointly considering temporal fluctuations and spatial disparities of the traffic load, especially under Ultra-Dense HetNets (UDHNs), the promising delivery of 5G networks. We propose the High-Resolution Cell Breathing (HiRCB) strategy for improving energy efficiency for UDHNs: 1) inspired by pixels in digital imaging, the UDHN coverage area is logically divided into Traffic Lattices (TLs), capturing spatial disparities of the traffic load; 2) the TL association problem with the objective of maximizing the accumulative energy efficiency utility is formulated; 3) to solve the formulated problem, the Parallel and Integer TL Association Algorithm (PITLAA) is proposed, featuring parallel computations and algorithmic conversions from multiple to single TL association. Numerical results show that HiRCB improves at least 50% energy efficiency.