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Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering

Annals of Computer Science and Information Systems, Volume 33

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

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DOI: http://dx.doi.org/10.15439/2022R15

Citation: Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering, Vu Dinh Khoa, Shivani Agarwal, Gloria Jeanette Rincon Aponte, Nguyen Thi Hong Nga, Vijender Kumar Solanki, Ewa Ziemba (eds). ACSIS, Vol. 33, pages 115–120 ()

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Abstract. 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 in the first phase. In the second phase, based on the amount of harvested energy at the first phase 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) requirements. Moreover, the present work takes into account 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. Three key vital metrics are studied, namely, coverage probability (Pcov), occurrence probabilities of the different modulation schemes (Poc), and achievable spectral efficiency (ASE). Finally, numerical results provided to highlight the superiority of the proposed scheme compared with the conventional fixed modulation.

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