Kang G. Shin
University of Michigan
915 Papers
11.3K Citations
Kang G. Shin is an academic researcher from University of Michigan. The author has contributed to research in topics: Computer science & Scheduling (computing). The author has an hindex of 98, co-authored 885 publications. Previous affiliations of Kang G. Shin include IBM & Sungkyunkwan University.
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Papers
Fast and accurate cardinality estimation in cellular-based wireless communications
Mohammad G. Khoshkholgh,Victor C. M. Leung,Kang G. Shin +2 more
- 09 Mar 2015
TL;DR: This paper provides a fresh look at this fundamental problem, and proposes a novel scheme for fast and accurate cardinality estimation that utilizes the experienced outage probability in detecting IDs of the devices in the uplink.
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Inside-Out Precoding to Manage Multiple Interferences From the Same Source
TL;DR: The proposed Inside-Out Precoding (IOP) can effectively manage multiple interferences from the same source while guaranteeing the performance of transmission from the interfering Tx to its intended Rx and a protocol to realize the synchronization of processing parameters at the interference Tx and its intended RX so that the Rx can adapt itself to the precoding strategy employed at the Tx side.
Generalized geometry-based optimal power control in wireless networks
Wei Wang,Kang G. Shin,Zhaoyang Zhang,Wenbo Wang,Tao Peng +4 more
- 18 Jun 2012
TL;DR: This work proposes a novel geometry-based optimization scheme for the general power-control problem that provides a novel visual perspective and lowers the complexity of optimization, and generalizes this scheme to a larger class of power- control optimization problems so as to maximize the network utility with multiple average and peak power constraints in wireless networks.
Queueing analysis of a canonical model of real-time multiprocessors
Chandan Krishna,Kang G. Shin +1 more
- 29 Aug 1983
TL;DR: A computation of the response time distribution for a canonical model of real-time multiprocessor for control applications with control applications in mind is presented.
DynaMIX: Resource Optimization for DNN-Based Real-Time Applications on a Multi-Tasking System
Min-gyu Cho,Kang G. Shin +1 more
TL;DR: In this paper , the authors propose DynaMIX (Dynamic MIXed-precision model construction), which optimizes the resource requirement of concurrent in-vehicle applications and aims to maximize execution accuracy.
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