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Author

Zhu Han

Bio: Zhu Han is an academic researcher from University of Houston. The author has contributed to research in topic(s): Wireless network & Resource allocation. The author has an hindex of 109, co-authored 1407 publication(s) receiving 48725 citation(s). Previous affiliations of Zhu Han include University of British Columbia & University of Maryland University College.

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Papers
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Journal ArticleDOI
Xiao Lu1, Ping Wang1, Dusit Niyato1, Dong In Kim2  +1 moreInstitutions (3)
TL;DR: This paper presents an overview of the RF-EHNs including system architecture, RF energy harvesting techniques, and existing applications, and explores various key design issues according to the network types, i.e., single-hop networks, multiantenna networks, relay networks, and cognitive radio networks.

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Abstract: Radio frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to power the next-generation wireless networks As this emerging technology enables proactive energy replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service requirements In this paper, we present a comprehensive literature review on the research progresses in wireless networks with RF energy harvesting capability, which is referred to as RF energy harvesting networks (RF-EHNs) First, we present an overview of the RF-EHNs including system architecture, RF energy harvesting techniques, and existing applications Then, we present the background in circuit design as well as the state-of-the-art circuitry implementations and review the communication protocols specially designed for RF-EHNs We also explore various key design issues in the development of RF-EHNs according to the network types, ie, single-hop networks, multiantenna networks, relay networks, and cognitive radio networks Finally, we envision some open research directions

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1,994 citations


Journal ArticleDOI
Lun Dong1, Zhu Han2, Athina P. Petropulu3, H.V. Poor4Institutions (4)
TL;DR: Novel system designs are proposed, consisting of the determination of relay weights and the allocation of transmit power, that maximize the achievable secrecy rate subject to a transmit power constraint, or minimize the transmit powersubject to a secrecy rate constraint.

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Abstract: Physical (PHY) layer security approaches for wireless communications can prevent eavesdropping without upper layer data encryption. However, they are hampered by wireless channel conditions: absent feedback, they are typically feasible only when the source-destination channel is better than the source-eavesdropper channel. Node cooperation is a means to overcome this challenge and improve the performance of secure wireless communications. This paper addresses secure communications of one source-destination pair with the help of multiple cooperating relays in the presence of one or more eavesdroppers. Three cooperative schemes are considered: decode-and-forward (DF), amplify-and-forward (AF), and cooperative jamming (CJ). For these schemes, the relays transmit a weighted version of a reencoded noise-free message signal (for DF), a received noisy source signal (for AF), or a common jamming signal (for CJ). Novel system designs are proposed, consisting of the determination of relay weights and the allocation of transmit power, that maximize the achievable secrecy rate subject to a transmit power constraint, or, minimize the transmit power subject to a secrecy rate constraint. For DF in the presence of one eavesdropper, closed-form optimal solutions are derived for the relay weights. For other problems, since the optimal relay weights are difficult to obtain, several criteria are considered leading to suboptimal but simple solutions, i.e., the complete nulling of the message signals at all eavesdroppers (for DF and AF), or the complete nulling of jamming signal at the destination (for CJ). Based on the designed relay weights, for DF in the presence of multiple eavesdroppers, and for CJ in the presence of one eavesdropper, the optimal power allocation is obtained in closed-form; in all other cases the optimal power allocation is obtained via iterative algorithms. Numerical evaluation of the obtained secrecy rate and transmit power results show that the proposed design can significantly improve the performance of secure wireless communications.

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1,294 citations


Journal ArticleDOI
Walid Saad1, Zhu Han2, Merouane Debbah3, Are Hjorungnes1  +1 moreInstitutions (4)
Abstract: In this tutorial, we provided a comprehensive overview of coalitional game theory, and its usage in wireless and communication networks. For this purpose, we introduced a novel classification of coalitional games by grouping the sparse literature into three distinct classes of games: canonical coalitional games, coalition formation games, and coalitional graph games. For each class, we explained in details the fundamental properties, discussed the main solution concepts, and provided an in-depth analysis of the methodologies and approaches for using these games in both game theory and communication applications. The presented applications have been carefully selected from a broad range of areas spanning a diverse number of research problems. The tutorial also sheds light on future opportunities for using the strong analytical tool of coalitional games in a number of applications. In a nutshell, this article fills a void in existing communications literature, by providing a novel tutorial on applying coalitional game theory in communication networks through comprehensive theory and technical details as well as through practical examples drawn from both game theory and communication application.

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805 citations


Book
Zhu Han1, Dusit Niyato2, Walid Saad3, Tamer Baar4  +1 moreInstitutions (5)
20 Oct 2011-
TL;DR: This unified treatment of game theory focuses on finding state-of-the-art solutions to issues surrounding the next generation of wireless and communications networks and covers a wide range of techniques for modeling, designing and analysing communication networks using game theory, as well as state of theart distributed design techniques.

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Abstract: This unified treatment of game theory focuses on finding state-of-the-art solutions to issues surrounding the next generation of wireless and communications networks. Future networks will rely on autonomous and distributed architectures to improve the efficiency and flexibility of mobile applications, and game theory provides the ideal framework for designing efficient and robust distributed algorithms. This book enables readers to develop a solid understanding of game theory, its applications and its use as an effective tool for addressing wireless communication and networking problems. The key results and tools of game theory are covered, as are various real-world technologies including 3G networks, wireless LANs, sensor networks, dynamic spectrum access and cognitive networks. The book also covers a wide range of techniques for modeling, designing and analysing communication networks using game theory, as well as state-of-the-art distributed design techniques. This is an ideal resource for communications engineers, researchers, and graduate and undergraduate students.

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773 citations


Journal ArticleDOI
Chunxiao Jiang1, Haijun Zhang2, Yong Ren1, Zhu Han3  +2 moreInstitutions (5)
TL;DR: The goal is to assist the readers in refining the motivation, problem formulation, and methodology of powerful machine learning algorithms in the context of future networks in order to tap into hitherto unexplored applications and services.

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Abstract: Next-generation wireless networks are expected to support extremely high data rates and radically new applications, which require a new wireless radio technology paradigm. The challenge is that of assisting the radio in intelligent adaptive learning and decision making, so that the diverse requirements of next-generation wireless networks can be satisfied. Machine learning is one of the most promising artificial intelligence tools, conceived to support smart radio terminals. Future smart 5G mobile terminals are expected to autonomously access the most meritorious spectral bands with the aid of sophisticated spectral efficiency learning and inference, in order to control the transmission power, while relying on energy efficiency learning/inference and simultaneously adjusting the transmission protocols with the aid of quality of service learning/inference. Hence we briefly review the rudimentary concepts of machine learning and propose their employment in the compelling applications of 5G networks, including cognitive radios, massive MIMOs, femto/small cells, heterogeneous networks, smart grid, energy harvesting, device-todevice communications, and so on. Our goal is to assist the readers in refining the motivation, problem formulation, and methodology of powerful machine learning algorithms in the context of future networks in order to tap into hitherto unexplored applications and services.

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743 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.

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Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

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30,199 citations



Christopher M. Bishop1Institutions (1)
01 Jan 2006-
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

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10,141 citations


Journal ArticleDOI
Andrew B. Lawson1, Noel A CressieInstitutions (1)
01 Mar 1993-The Statistician

6,278 citations


01 Feb 1977-

5,933 citations


Network Information
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Performance
Metrics

Author's H-index: 109

No. of papers from the Author in previous years
YearPapers
2021133
2020150
2019148
2018157
2017164
2016116

Top Attributes

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Author's top 5 most impactful journals

arXiv: Information Theory

47 papers, 1.6K citations

IEEE Access

43 papers, 693 citations