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Throughput Optimization for Massive MIMO Systems Powered by Wireless Energy Transfer

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TLDR
In this article, the authors considered a massive multiple-input-multiple-output (MIMO) system with a hybrid data-and-energy access point (H-AP) and multiple single-antenna users, where the H-AP estimates the uplink channels and obtains the downlink channels by exploiting channel reciprocity.
Abstract
This paper studies a wireless-energy-transfer (WET) enabled massive multiple-input-multiple-output (MIMO) system (MM) consisting of a hybrid data-and-energy access point (H-AP) and multiple single-antenna users. In the WET-MM system, the H-AP is equipped with a large number $M$ of antennas and functions like a conventional AP in receiving data from users, but additionally supplies wireless power to the users. We consider frame-based transmissions. Each frame is divided into three phases: the uplink channel estimation (CE) phase, the downlink WET phase, as well as the uplink wireless information transmission (WIT) phase. Firstly, users use a fraction of the previously harvested energy to send pilots, while the H-AP estimates the uplink channels and obtains the downlink channels by exploiting channel reciprocity. Next, the H-AP utilizes the channel estimates just obtained to transfer wireless energy to all users in the downlink via energy beamforming. Finally, the users use a portion of the harvested energy to send data to the H-AP simultaneously in the uplink (reserving some harvested energy for sending pilots in the next frame). To optimize the throughput and ensure rate fairness, we consider the problem of maximizing the minimum rate among all users. In the large-$M$ regime, we obtain the asymptotically optimal solutions and some interesting insights for the optimal design of WET-MM system. We define a metric, namely, the massive MIMO degree-of-rate-gain (MM-DoRG), as the asymptotic UL rate normalized by $\log(M)$. We show that the proposed WET-MM system is optimal in terms of MM-DoRG, i.e., it achieves the same MM-DoRG as the case with ideal CE.

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References
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Journal ArticleDOI

Fundamentals of statistical signal processing: estimation theory

TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Journal ArticleDOI

Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays

TL;DR: The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time.
Journal ArticleDOI

Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems

TL;DR: In this paper, the tradeoff between the energy efficiency and spectral efficiency of a single-antenna system is quantified for a channel model that includes small-scale fading but not large scale fading, and it is shown that the use of moderately large antenna arrays can improve the spectral and energy efficiency with orders of magnitude compared to a single antenna system.
Journal ArticleDOI

Scaling up MIMO: Opportunities and Challenges with Very Large Arrays

TL;DR: Very large MIMO as mentioned in this paper is a new research field both in communication theory, propagation, and electronics and represents a paradigm shift in the way of thinking both with regards to theory, systems and implementation.
Journal ArticleDOI

MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer

TL;DR: This paper studies a multiple-input multiple-output (MIMO) wireless broadcast system consisting of three nodes, where one receiver harvests energy and another receiver decodes information separately from the signals sent by a common transmitter, and all the transmitter and receivers may be equipped with multiple antennas.
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