On the Performance of Cellular Networks with Adaptive Modulation and Energy Harvesting : A Stochastic Geometry Approach

The performance of ultra-dense cellular networks considering both adaptive discrete modulation (ADM) and energy harvesting (EH) is investigated. Particularly, mobile users (MUs) are charged its battery from all ambient radio frequency (RF) signals. Based on the amount of harvested energy as well as the channel conditions, MU will actively choose an appropriate modulation scheme that not only maximizes the rate but also satisfies the quality-of-service (QoS). Moreover, we consider the spatial-temporal correlation at the signal-to-interference-plus-noise ratios (SINRs) of base stations (BSs) which are totally different from work in the literature. Several important metrics are investigated such as, occurrence probabilities of different modulation schemes (Poc), coverage probability (Pcov), and achievable spectral efficiency (ASE). Finally, the results highlight the superiority of the proposed scheme compared to the conventional fixed modulation.