We consider a model where a source equipped with fewer radio-frequency  (RF) chains than the number of transmit antennas employs antenna selection (AS) and is assisted by an intelligent reflecting surface (IRS) to transfer energy wirelessly as depicted in Figure 1. Since the source employs AS, it reduces the required RF chains, thus reducing hardware complexity, power consumption and cost. For this model, we analyse the outage probability in the context of energy transfer when the source employs AS and is assisted by an IRS under perfect and estimated channel state information (CSI). We also derive diversity order and study the impact of subset AS, discrete phase shift and limited scattering on outage probability.

The publication based on this work can be accessed using the below link:

On the Feasibility of Wireless Energy Transfer Based on Low Complexity Antenna Selection and Passive IRS Beamforming 

We consider a scenario where a single antenna source assisted by double intelligent reflecting surface (IRS) transfers downlink (DL) energy to a single antenna user, as illustrated in Figure 2. And the main objective of this model is to ascertain whether the use of double IRSs can help save radiated power at the source while keeping outage probability (OP) fixed at the specific level and improve power transfer efficiency (PTE). For this system, we derive new expressions for OP with double IRS-assisted configuration under non-linear energy harvesting (EH) at the user. As benchmark, we also derive new expressions for OP with single IRS-assisted configuration and with massive multiple input multiple output (MIMO) enabled WET. We extend our analysis to the case where each link via the direct and the cascaded paths between the source and the user follows Rician fading. We also study the impact of modeling four communication links between the source and the user on OP.

The publication based on this work can be accessed using the below link:

On the Power Transfer Efficiency and Feasibility of Wireless Energy Transfer Using Double IRS 

We consider the DL of a single-cell massive MIMO set-up where a BS equipped with massive number of antennas serves two heterogeneous sets of user terminals, namely the mobile terminals and the IoT devices with different data rate requirements simultaneously over the same time and frequency. In order to construct precoders to beam distinct data streams on the DL to mobile terminals and the IoT devices over a channel that varies over time, the CSI must be learnt at the BS every coherence interval. To facilitate this, we consider orthogonal pilot assignment strategy for mobile terminals where every mobile terminal is allocated an orthogonal pilot for channel estimation. Since the number of IoT devices is fairly high and the coherence interval has finite time-frequency samples, we consider two different low overhead pilot assignment and channel estimation strategies for the IoT devices to address the infeasibility of assigning an orthogonal pilot to every IoT device.

The publication based on this work can be accessed using the below link:

Massive MIMO enabled joint unicast transmission to IoT devices and mobile terminals