A dithered scalar quantization scheme with truncated Gaussian shaping and polar codes achieves the Berger-Tung corner points for distributed Gaussian source coding and reduces distortion in Wyner-Ziv setups.
The CEO problem [multi- terminal source coding],
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Derives closed-form DG-optimal and MSE-optimal transceiver designs for ISAC under compress-and-estimate framework, with numerical results showing DG-optimal design is more power-efficient at low SNR by selective feature allocation.
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Polar Coded Quantization for Distributed Source Coding
A dithered scalar quantization scheme with truncated Gaussian shaping and polar codes achieves the Berger-Tung corner points for distributed Gaussian source coding and reduces distortion in Wyner-Ziv setups.
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Inference-Optimal ISAC via Task-Oriented Feature Transmission and Power Allocation
Derives closed-form DG-optimal and MSE-optimal transceiver designs for ISAC under compress-and-estimate framework, with numerical results showing DG-optimal design is more power-efficient at low SNR by selective feature allocation.