S
Seok-Hwan Park
Researcher at Chonbuk National University
Publications - 150
Citations - 3167
Seok-Hwan Park is an academic researcher from Chonbuk National University. The author has contributed to research in topics: Radio access network & Telecommunications link. The author has an hindex of 25, co-authored 142 publications receiving 2773 citations. Previous affiliations of Seok-Hwan Park include Korea University & New Jersey Institute of Technology.
Papers
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Joint Precoding and Multivariate Backhaul Compression for the Downlink of Cloud Radio Access Networks
TL;DR: From numerical results, it is confirmed that the proposed joint precoding and compression strategy outperforms conventional approaches based on the separate design of precode and compression or independent compression across the BSs.
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Fronthaul Compression for Cloud Radio Access Networks: Signal processing advances inspired by network information theory
TL;DR: A survey of the work in this area with emphasis on advanced signal processing solutions based on network information theoretic concepts is provided, illustrating the considerable performance gains to be expected for standard cellular models.
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Linear precoder designs for K-user interference channels
TL;DR: Simulation results show that the proposed iterative algorithm outperforms other existing methods in terms of sum rate and the proposed non-iterative method approaches a local optimal solution at high signal-to-noise ratio with reduced complexity.
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Joint Optimization of Cloud and Edge Processing for Fog Radio Access Networks
TL;DR: Numerical results are provided to compare the performance of hard- and soft-transfer fronthauling modes, as well as of the hybrid scheme, for different baseline pre-fetching strategies.
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Robust and Efficient Distributed Compression for Cloud Radio Access Networks
TL;DR: From numerical results, it is observed that the proposed robust compression scheme compensates for a large fraction of the performance loss induced by the imperfect statistical information, and the proposed BS selection algorithm is seen to perform close to the more complex exhaustive search solution.