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Bruno Clerckx

Researcher at Imperial College London

Publications -  532
Citations -  15723

Bruno Clerckx is an academic researcher from Imperial College London. The author has contributed to research in topics: MIMO & Channel state information. The author has an hindex of 52, co-authored 458 publications receiving 11901 citations. Previous affiliations of Bruno Clerckx include Xidian University & Mitsubishi Electric Research Laboratories.

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Coordinated multipoint transmission and reception in LTE-advanced: deployment scenarios and operational challenges

TL;DR: Some of the deployment scenarios in which CoMP techniques will likely be most beneficial and an overview of CoMP schemes that might be supported in LTE-Advanced given the modern silicon/DSP technologies and backhaul designs available today are discussed.
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Fundamentals of Wireless Information and Power Transfer: From RF Energy Harvester Models to Signal and System Designs

TL;DR: This paper highlights three different energy harvester models, namely, one linear model and two nonlinear models, and shows how WIPT designs differ for each of them in single-user and multi-user deployments, and identifies the fundamental tradeoff between conveying information and power wirelessly.
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MIMO techniques in WiMAX and LTE: a feature overview

TL;DR: A survey of the MIMO techniques in the two standards, IEEE 802.16e/m and 3GPP LTE/LTE-Advanced, which compares the features of the two and depicts the engineering considerations.
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Communications and Signals Design for Wireless Power Transmission

TL;DR: In this paper, the authors give an overview on the various radiative wireless power transfer (WPT) technologies, the historical development of the radiative WPT technology and the main challenges in designing contemporary WPT systems, focusing on the state-of-the-art communication and signal processing techniques that can be applied to tackle these challenges.
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Waveform Design for Wireless Power Transfer

TL;DR: This paper derives a tractable model of the nonlinearity of the rectenna and compares with a linear model conventionally used in the literature and uses those models to design novel multisine waveforms that are adaptive to the channel state information (CSI).