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Journal ArticleDOI

Convex Optimization-Based Beamforming

TLDR
It is demonstrated that convex optimization provides an indispensable set of tools for beamforming, enabling rigorous formulation and effective solution of both long-standing and emerging design problems.
Abstract
In this article, an overview of advanced convex optimization approaches to multisensor beamforming is presented, and connections are drawn between different types of optimization-based beamformers that apply to a broad class of receive, transmit, and network beamformer design problems. It is demonstrated that convex optimization provides an indispensable set of tools for beamforming, enabling rigorous formulation and effective solution of both long-standing and emerging design problems.

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Citations
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Journal ArticleDOI

Semidefinite Relaxation of Quadratic Optimization Problems

TL;DR: This article has provided general, comprehensive coverage of the SDR technique, from its practical deployments and scope of applicability to key theoretical results, and showcased several representative applications, namely MIMO detection, B¿ shimming in MRI, and sensor network localization.
Journal ArticleDOI

Outage Constrained Robust Transmit Optimization for Multiuser MISO Downlinks: Tractable Approximations by Conic Optimization

TL;DR: This paper studies a probabilistically robust transmit optimization problem under imperfect channel state information at the transmitter and under the multiuser multiple-input single-output (MISO) downlink scenario, and develops two novel approximation methods using probabilistic techniques.
Journal ArticleDOI

Multiuser MISO Beamforming for Simultaneous Wireless Information and Power Transfer

TL;DR: This paper studies a multiuser multiple-input single-output (MISO) broadcast system for simultaneous wireless information and power transfer (SWIPT), where a multi-antenna access point sends information and energy simultaneously via beamforming to multiple single-antennas receivers.
Journal ArticleDOI

Satellite Communications in the New Space Era: A Survey and Future Challenges

TL;DR: In this article, the authors present a survey of the state of the art in satellite communications, while highlighting the most promising open research topics, such as new constellation types, on-board processing capabilities, non-terrestrial networks and space-based data collection/processing.
Book

Optimal Resource Allocation in Coordinated Multi-Cell Systems

TL;DR: The use of multiple antennas at base stations is a key component in the design of cellular communication systems that can meet high-capacity demands in the downlink.
References
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Book

Convex Optimization

TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Journal ArticleDOI

Cooperative diversity in wireless networks: Efficient protocols and outage behavior

TL;DR: Using distributed antennas, this work develops and analyzes low-complexity cooperative diversity protocols that combat fading induced by multipath propagation in wireless networks and develops performance characterizations in terms of outage events and associated outage probabilities, which measure robustness of the transmissions to fading.
Journal ArticleDOI

Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones

TL;DR: This paper describes how to work with SeDuMi, an add-on for MATLAB, which lets you solve optimization problems with linear, quadratic and semidefiniteness constraints by exploiting sparsity.
Journal ArticleDOI

Capacity theorems for the relay channel

TL;DR: In this article, the capacity of the Gaussian relay channel was investigated, and a lower bound of the capacity was established for the general relay channel, where the dependence of the received symbols upon the inputs is given by p(y,y) to both x and y. In particular, the authors proved that if y is a degraded form of y, then C \: = \: \max \!p(x,y,x,2})} \min \,{I(X,y), I(X,Y,Y,X,Y

Capacity theorems for the relay channel

TL;DR: An achievable lower bound to the capacity of the general relay channel is established and superposition block Markov encoding is used to show achievability of C, and converses are established.
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