Modeling, optimization and analysis of wireless information and energy transfer in beyond 5g IOT networks

Abstract

This thesis focuses on system modeling, optimization and comprehensive performance analysis of wireless information and energy transfer to the Internet-of-Things (IoT) devices. These devices are likely to form a core component of beyond fifth generation (5G) wireless systems in order to support numerous applications foreseen in such systems. We first investigate whether a base station (BS) with massive number of antennas can support joint machine-centric communication among the IoT devices and human-centric communication among the mobile terminals. To this end, we derive downlink spectral efficiency (SE) of the IoT devices with maximum ratio precoding when channel estimates are acquired via the proposed distance-dependent grouping based hybrid pilot assignment strategy. As benchmarks, we also evaluate SE under non-orthogonal pilot assignment and distance-independent grouping. We show that under channel inversion based power control at the BS, the proposed pilot assignment and channel estimation strategy yields the highest sum SE and can serve the largest number of IoT devices when compared to the benchmarks. The corresponding performance under max-min power allocation is also presented