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Shalinee Kishore

Researcher at Lehigh University

Publications -  110
Citations -  3448

Shalinee Kishore is an academic researcher from Lehigh University. The author has contributed to research in topics: Microcell & Smart grid. The author has an hindex of 23, co-authored 110 publications receiving 3286 citations. Previous affiliations of Shalinee Kishore include Rutgers University & AT&T.

Papers
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Proceedings ArticleDOI

Wireless diversity through network coding

TL;DR: The results show that network-coded DAS leads to better diversity performance as compared to conventional DAS, at a lower hardware cost and higher spectral efficiency.
Patent

CDMA mobile station wireless transmission power management with adaptive scheduling priorities based on battery power level

TL;DR: In this article, a method adapts scheduling priorities in a CDMA wireless communications system to conserve battery power in mobile terminals operating within the system, based on the battery power level information and other setup information, the base station adjusts scheduling priorities for the mobile terminals to expedite wireless transmissions from those mobile terminals reporting low battery power levels.
Journal ArticleDOI

MPC-Based Appliance Scheduling for Residential Building Energy Management Controller

TL;DR: This paper proposes an appliance scheduling scheme for residential building energy management controllers, by taking advantage of the time-varying retail pricing enabled by the two-way communication infrastructure of the smart grid.
Journal ArticleDOI

A Distributed Direct Load Control Approach for Large-Scale Residential Demand Response

TL;DR: In this paper, the authors proposed a distributed direct load control scheme for large-scale residential demand response (DR) built on a two-layer communication-based control architecture, which utilizes the average consensus algorithm to distribute portions of the desired aggregated demand to each EMC in a decentralized fashion.
Journal ArticleDOI

Dynamic resource allocation schemes during handoff for mobile multimedia wireless networks

TL;DR: The results indicate that using dynamic estimation and allocation, this paper can significantly reduce the dropping probability for handoff connections.