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20242026
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cs.IT2025

PolarZero: A Reinforcement Learning Approach for Low-Complexity Polarization Kernel Design

Yi-Ting Hong, Stefano Rini, Luca Barletta

Polar codes with large kernels can achieve improved error exponents but are challenging to design with low decoding complexity. This work investigates kernel construction under rec…

cs.IT2025

Reinforcement Learning-Aided Design of Efficient Polarization Kernels

Yi-Ting Hong, Stefano Rini, Luca Barletta

Polar codes with large kernels achieve optimal error exponents but are difficult to construct when low decoding complexity is also required. We address this challenge under recursi…

cs.IT2025

The Query/Hit Model for Sequential Hypothesis Testing

Mahshad Shariatnasab, Stefano Rini, Farhad Shirani +1

This work introduces the Query/Hit (Q/H) learning model. The setup consists of two agents. One agent, Alice, has access to a streaming source, while the other, Bob, does not have d…

cs.IT2024

ARMA Processes with Discrete-Continuous Excitation: Compressibility Beyond Sparsity

Mohammad-Amin Charusaie, Stefano Rini, Arash Amini

Rényi Information Dimension (RID) plays a central role in quantifying the compressibility of random variables with singularities in their distribution, encompassing and extending…

cs.IT2024

Coding for the unsourced B-channel with erasures: enhancing the linked loop code

William W. Zheng, Jamison R. Ebert, Stefano Rini +1

In [1], the linked loop code (LLC) is presented as a promising code for the unsourced A-channel with erasures (UACE). The UACE is an unsourced multiple access channel in which acti…