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Journal Article 4

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2019 2

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Semidefinite relaxation 3

Bad data detection 1

Beamforming 1

Channel state information 1

Composite optimization 1

Cramér-Rao bound 1

Cyber attack 1

Feasible point pursuit 1

General-rank 1

Generalized likelihood ratio test 1

Iterative sub-gradient 1

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Model mismatches 1

Multiple-symbol differential detection 1

Positive semidefinite (PSD) constraint 1

Proximal linear algorithm 1

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Simultaneous wireless information and power transfer 1

State estimation 1

Two-way relay transmission 1

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Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint Article

Yu-tang ZHU,Yong-bo ZHAO,Jun LIU,Peng-lang SHUI

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 11, Pages 1245-1252 doi: 10.1631/FITEE.1601112

Abstract: uncertainties in the desired and received signal covariance matrices, but also includes an additional positive semidefinite

Keywords： Beamforming General-rank Low complexity Positive semidefinite (PSD) constraint Model mismatches

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Semidefinite relaxation aided noncoherent detection in two-way relay transmission Regular Papers-Research Articles

Chan-fei WANG, Ji-ai HE, Wei-fang WANG, Ya-mei XU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 9, Pages 1259-1265 doi: 10.1631/FITEE.1800096

Abstract: Furthermore, GLRT-MSDD is reformulated and a semidefinite relaxation aided MSDD (SDR-MSDD) is proposed

Keywords： Multiple-symbol differential detection Generalized likelihood ratio test Semidefinite relaxation Two-way

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Distribution system state estimation: an overview of recent developments Review Article

Gang WANG, Georgios B. GIANNAKIS, Jie CHEN, Jian SUN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 1, Pages 4-17 doi: 10.1631/FITEE.1800590

Abstract:

In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of (industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate, fast, and robust power system state estimation (PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states (i.e., nodal voltage phasors). Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramér-Rao lower bound is developed. Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.

Keywords： State estimation Cramér-Rao bound Feasible point pursuit Semidefinite relaxation Proximal linear algorithm