6 papers
PrismQuant: Rate-Distortion-Optimal Vector Quantization for Gaussian-Mixture Sources
Bumsu Park, Chanho Park, Youngmok Park +1
For a Gaussian source under mean-squared error (MSE), classical transform coding is rate--distortion (RD) optimal: the Karhunen--Loeve transform (KLT) diagonalizes the covariance,…
CSI Compression for Massive MIMO-OFDM: Mismatch-Aware Rate-Distortion Trade-offs
Bumsu Park, Youngmok Park, Chanho Park +1
We study channel state information (CSI) compression for wideband frequency division duplex massive multiple-input multiple-output (MIMO) when the base station (BS) reconstructs CS…
Fundamental Limits of CSI Compression in FDD Massive MIMO
Bumsu Park, Youngmok Park, Chanho Park +1
Channel state information (CSI) feedback in frequency-division duplex (FDD) massive multiple-input multiple-output (MIMO) systems is fundamentally limited by the high dimensionalit…
Hierarchical Subcode Ensemble Decoding of Polar Codes
Yubeen Jo, Geon Choi, Chanho Park +1
Subcode-ensemble decoders improve iterative decoding by running multiple decoders in parallel over carefully chosen subcodes, increasing the likelihood that at least one decoder av…
SignSGD with Federated Voting
Chanho Park, H. Vincent Poor, Namyoon Lee
Distributed learning is commonly used for accelerating model training by harnessing the computational capabilities of multiple-edge devices. However, in practical applications, the…
SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding
Chanho Park, Namyoon Lee
Distributed learning is an effective approach to accelerate model training using multiple workers. However, substantial communication delays emerge between workers and a parameter…