Stochastic Geometry Modeling of Cellular Networks: A New Definition of Coverage and its Application to Energy Efficiency Optimization

Author(s):  
Marco Di Renzo ◽  
Alessio Zappone ◽  
Thanh Tu Lam ◽  
Merouane Debbah
2017 ◽  
Vol 24 (7) ◽  
pp. 2565-2578
Author(s):  
Song Cen ◽  
Xingjun Zhang ◽  
Ming Lei ◽  
Scott Fowler ◽  
Xiaoshe Dong

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jiaqi Lei ◽  
Hongbin Chen ◽  
Feng Zhao

The energy efficiency (EE) is a key metric of ultradense heterogeneous cellular networks (HCNs). Earlier works on the EE analysis of ultradense HCNs by using the stochastic geometry tool only focused on the impact of the base station density ratio and ignored the function of different tiers. In this paper, a two-tier ultradense HCN with small-cell base stations (SBSs) and user equipments (UEs) densely deployed in a traditional macrocell network is considered. Firstly, the performance of the ultradense HCN in terms of the association probability, average link spectral efficiency (SE), average downlink throughput, and average EE is theoretically analyzed by using the stochastic geometry tool. Then, the problem of maximizing the average EE while meeting minimum requirements of the average link SE and average downlink throughput experienced by UEs in macrocell and small-cell tiers is formulated. As it is difficult to obtain the explicit expression of average EE, impacts of the SBS density ratio and signal-to-interference-plus-noise ratio (SINR) threshold on the network performance are investigated through numerical simulations. Simulation results validate the accuracy of theoretical results and demonstrate that the maximum value of average EE can be achieved by optimizing the SBS density ratio and the SINR threshold.


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