System-level analysis of receiver diversity in SWIPT-enabled cellular networks

In this paper, we study the feasibility of receiver diversity for application to downlink cellular networks, where low-energy devices are equipped with information decoding and energy harvesting receivers for simultaneous wireless information and power transfer. We compare several options that are based on selection combining and maximum ratio combining, which provide different implementation complexities. By capitalizing on the Frechet inequality, we shed light on the advantages and limitations of each scheme as a function of the transmission rate and harvested power that need to be fulfilled at the low-energy devices. Our analysis shows that no scheme outperforms the others for every system setup. It suggests, on the other hand, that the low-energy devices need to operate in an adaptive fashion, by choosing the receiver diversity scheme as a function of the imposed requirements. With the aid of stochastic geometry, we introduce mathematical frameworks for system-level analysis. We show that they constitute an important tool for system-level optimization and, in particular, for identifying the diversity scheme that optimizes wireless information and power transmission as a function of a sensible set of parameters. Monte Carlo simulations are used to validate our findings and to illustrate the trade-off that emerge in cellular networks with simultaneous wireless information and power transfer.