Distributed massive MIMO for wireless power transfer in the industrial Internet of Things

This paper considers wireless power transfer (WPT) for powering low-power devices in massive Machine Type Communication (mMTC) using a distributed massive multiple-input multiple-output (MIMO) system. Each Internet of Things (IoT) device can be served by one or more access points (APs) which is equipped with a massive antenna array. During each time slot, each IoT device transmits pilot sequences to enable APs to perform channel estimation. This process is followed by the WPT using conjugate beamforming. The approach to transmission power control is formulated as a non-convex optimization problem aiming to maximize the total accumulated power achieved by all IoT devices while taking into account the power weights at the APs, pilot power control at the IoT devices, and the non-linearity of practical energy harvesting circuits. An alternating optimization approach is adopted to solve it iteratively, achieving convergence within just a few iterations. Furthermore, since the number of IoT devices might be enormous in mMTC networks, we propose a pilot sharing algorithm allowing IoT devices to reuse pilot sequences effectively. Numerical results are provided to validate the effectiveness of the proposed power control algorithms and the pilot sharing scheme. It is shown that by allowing IoT devices to share the pilot sequences instead of employing the orthogonal pilots, the per-user accumulated performance is enhanced considerably, especially when the number of IoT devices is large relative to the coherence interval. The advantage of using distributed massive MIMO compared to its collocated counterpart is demonstrated in terms of the per-user accumulated power.