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To unleash the potential of quantum computers, noise effects on qubits' performance must be carefully managed. The decoders responsible for diagnosing noise-induced computational errors must use resources efficiently to enable scaling to…

We consider the problem of decentralized frequency and phase synchronization in distributed phased arrays via local broadcast of the node electrical states. Frequency and phase synchronization between nodes in a distributed array is…

Signal Processing · Electrical Eng. & Systems 2022-04-11 Mohammed Rashid , Jeffrey A. Nanzer

To extend the applications of polar codes within next-generation wireless communication systems, it is essential to incorporate support for Incremental Redundancy (IR) Hybrid Automatic Repeat Request (HARQ) schemes. For very high-throughput…

Signal Processing · Electrical Eng. & Systems 2026-05-28 Marwan Jalaleddine , Mohamad Ali Jarkas , Jiajie Li , Warren J. Gross

The GPU as a digital signal processing accelerator for cloud RAN is investigated. A new design for a 5G NR low density parity check code decoder running on a GPU is presented. The algorithm is flexibly adaptable to GPU architecture to…

Networking and Internet Architecture · Computer Science 2020-09-14 Jonathan Ling , Paul Cautereels

Independent Component Analysis (ICA) is a dimensionality reduction technique that can boost efficiency of machine learning models that deal with probability density functions, e.g. Bayesian neural networks. Algorithms that implement…

Machine Learning · Computer Science 2017-07-10 Mahdi Nazemi , Shahin Nazarian , Massoud Pedram

Polar encoding, described by Arikan in IEEE Transactions on Information Theory, Vol. 55, No. 7, July 2009, was a milestone for telecommunications. A Polar code distributes information among high and low-capacity channels, showing the…

Information Theory · Computer Science 2025-07-29 Geraldo A. Barbosa

This paper investigates the decoding process of asynchronous convolutional-coded physical-layer network coding (PNC) systems. Specifically, we put forth a layered decoding framework for convolutional-coded PNC consisting of three layers:…

Information Theory · Computer Science 2013-12-06 Qing Yang , Soung Chang Liew

Deep-learning accelerators are increasingly in demand; however, their performance is constrained by the size of the feature map, leading to high bandwidth requirements and large buffer sizes. We propose an adaptive scale feature map…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuan Yao , Tian-Sheuan Chang

A low-power precision-scalable processor for ConvNets or convolutional neural networks (CNN) is implemented in a 40nm technology. Its 256 parallel processing units achieve a peak 102GOPS running at 204MHz. To minimize energy consumption…

Hardware Architecture · Computer Science 2016-06-17 Bert Moons , Marian Verhelst

The presented paper introduces a design for a phase-locked loop (PLL) that is utilized in frequency synthesis and modulation-demodulation within communication systems and in VLSI applications. The CMOS PLL is designed using 180 nm…

Systems and Control · Electrical Eng. & Systems 2024-06-21 Priyam Kumar , Akshada Khele , Aditee C. Joshi

A pruned variant of polar coding is reinvented for all binary erasure channels. For small $\varepsilon>0$, we construct codes with block length $\varepsilon^{-5}$, code rate $\text{Capacity}-\varepsilon$, error probability $\varepsilon$,…

Information Theory · Computer Science 2018-12-20 Hsin-Po Wang , Iwan Duursma

Even if Application-Specific Integrated Circuits (ASIC) have proven to be a relevant choice for integrating inference at the edge, they are often limited in terms of applicability. In this paper, we demonstrate that an ASIC neural network…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Van Thien Nguyen , William Guicquero , Gilles Sicard

Arikan's recursive code construction is designed to polarize a collection of memoryless channels into a set of good and a set of bad channels, and it can be efficiently decoded using successive cancellation. It was recently shown that the…

Information Theory · Computer Science 2019-01-16 Benjamin Bourassa , Maxime Tremblay , David Poulin

Realizing the full potential of quantum computation requires quantum error correction (QEC), with most recent breakthrough demonstrations of QEC using the surface code. QEC codes use multiple noisy physical qubits to encode information in…

We study the use of polar codes for both discrete and continuous variables Quantum Key Distribution (QKD). Although very large blocks must be used to obtain the efficiency required by quantum key distribution, and especially continuous…

Quantum Physics · Physics 2013-07-30 Paul Jouguet , Sébastien Kunz-Jacques

Message-passing iterative decoders for low-density parity-check (LDPC) block codes are known to be subject to decoding failures due to so-called pseudo-codewords. These failures can cause the large signal-to-noise ratio performance of…

Information Theory · Computer Science 2007-07-13 Roxana Smarandache , Ali E. Pusane , Pascal O. Vontobel , Daniel J. Costello

Previous work showed that polar codes can be decoded using off-the-shelf LDPC decoders by imposing special constraints on the LDPC code structure, which, however, resulted in some performance degradation. In this paper we show that this…

Information Theory · Computer Science 2019-09-27 Moustafa Ebada , Ahmed Elkelesh , Stephan ten Brink

In this paper we address the problem of selecting factor-graph permutations of polar codes under belief propagation (BP) decoding to significantly improve the error-correction performance of the code. In particular, we formalize the…

Information Theory · Computer Science 2020-09-16 Nghia Doan , Seyyed Ali Hashemi , Warren Gross

Recent efforts have demonstrated the first prototypes of compact and programmable photonic quantum computers~(PQCs). Utilization of time-bin encoding in loop-like architectures enabled a programmable generation of quantum states and…

Quantum Physics · Physics 2023-08-02 Shakir Ullah , Mehmet Emre Tasgin , Rasim Volga Ovali , Mehmet Günay

Autoencoders are unsupervised neural networks that are used to process and compress input data and then reconstruct the data back to the original data size. This allows autoencoders to be used for different processing applications such as…

Machine Learning · Computer Science 2023-01-18 Murat Isik , Matthew Oldland , Lifeng Zhou