English
Related papers

Related papers: Low-Complexity and Power-Efficient Precoding Codeb…

200 papers

This letter proposes a pragmatic link adaptation algorithm considering power density offsets (PDOs) for next-generation uplink wireless channels. The proposed algorithm consists of PDO calculation between a physical uplink shared channel…

Information Theory · Computer Science 2020-09-21 Shu Sun , Sungho Moon , Jong-Kae Fwu

This work establishes the design, analysis, and fine-tuning of a Peak-to-Average-Power-Ratio (PAPR) reducing system, based on compressed sensing at the receiver of a peak-reducing sparse clipper applied to an OFDM signal at the transmitter.…

Information Theory · Computer Science 2015-05-27 Ebrahim B. Al-Safadi , Tareq Y. Al-Naffouri

Sparse Matrix-Vector Multiplication (SpMV) is a fundamental operation in the inference of sparse Large Language Models (LLMs). Because existing SpMV methods perform poorly under the low and unstructured sparsity (30-90%) commonly observed…

Machine Learning · Computer Science 2025-11-18 Vladimír Macko , Vladimír Boža

Reducing the memory footprint of neural networks is a crucial prerequisite for deploying them in small and low-cost embedded devices. Network parameters can often be reduced significantly through pruning. We discuss how to best represent…

Data Structures and Algorithms · Computer Science 2021-11-25 Elias Trommer , Bernd Waschneck , Akash Kumar

Orthogonal Frequency Division Multiplexing (OFDM) based multi-carrier systems can support high data rate wireless transmission without the requirement of any extensive equalization and yet offer excellent immunity against fading and…

Information Theory · Computer Science 2013-04-29 Md. Sakir Hossain , Sabbir Ahmed , Enayet Ullah , Md. Atiqul Islam

Sparse random linear network coding (SRLNC) is an attractive technique proposed in the literature to reduce the decoding complexity of random linear network coding. Recognizing the fact that the existing SRLNC schemes are not efficient in…

Information Theory · Computer Science 2013-11-12 Kaveh Mahdaviani , Raman Yazdani , Masoud Ardakani

Recent advances in computer vision and machine learning suggest that a wide range of problems can be addressed more appropriately by considering non-Euclidean geometry. In this paper we explore sparse dictionary learning over the space of…

Computer Vision and Pattern Recognition · Computer Science 2013-10-21 Mehrtash Harandi , Conrad Sanderson , Chunhua Shen , Brian C. Lovell

To address the challenge of increasing network size, researchers have developed sparse models through network pruning. However, maintaining model accuracy while achieving significant speedups on general computing devices remains an open…

Artificial Intelligence · Computer Science 2023-10-31 Haitao Xu , Songwei Liu , Yuyang Xu , Shuai Wang , Jiashi Li , Chenqian Yan , Liangqiang Li , Lean Fu , Xin Pan , Fangmin Chen

Sparse matrix-vector multiplication (SpMV) is a fundamental operation in machine learning, scientific computing, and graph algorithms. In this paper, we investigate the space, time, and energy efficiency of SpMV using various compressed…

Data Structures and Algorithms · Computer Science 2024-09-30 Francesco Tosoni , Philip Bille , Valerio Brunacci , Alessio De Angelis , Paolo Ferragina , Giovanni Manzini

Algebraic codes such as BCH code are receiving renewed interest as their short block lengths and low/no error floors make them attractive for ultra-reliable low-latency communications (URLLC) in 5G wireless networks. This paper aims at…

Information Theory · Computer Science 2020-12-22 Li Deng , Zilong Liu , Yong Liang Guan , Xiaobei Liu , Chaudhry Adnan Aslam , Xiaoxi Yu , Zhiping Shi

For the additive Gaussian noise channel with average codeword power constraint, sparse superposition codes and adaptive successive decoding is developed. Codewords are linear combinations of subsets of vectors, with the message indexed by…

Information Theory · Computer Science 2010-06-22 Andrew R Barron , Antony Joseph

We consider the problem of information flow over Gaussian relay networks. Similar to the recent work by Avestimehr \emph{et al.} [1], we propose network codes that achieve up to a constant gap from the capacity of such networks. However,…

Information Theory · Computer Science 2011-02-28 Theodoros K. Dikaliotis , Hongyi Yao , Salman Avestimehr , Sidharth Jaggi , Tracey Ho

Ultra reliable and low latency communication (URLLC) is a newly introduced service category in 5G to support delay-sensitive applications. In order to support this new service category, 3rd Generation Partnership Project (3GPP) sets an…

Information Theory · Computer Science 2018-08-02 Hyoungju Ji , Sunho Park , Byonghyo Shim

The Grassmannian space $\Gr$ is the set of all $k-$dimensional subspaces of the vector space~\smash{$\F_q^n$}. Recently, codes in the Grassmannian have found an application in network coding. The main goal of this paper is to present…

Information Theory · Computer Science 2010-08-31 Natalia Silberstein , Tuvi Etzion

An ultra-high throughput low-density parity check (LDPC) decoder with an unrolled full-parallel architecture is proposed, which achieves the highest decoding throughput compared to previously reported LDPC decoders in the literature. The…

In this paper, we consider the precoder design for an underloaded or critically loaded downlink multi-user multiple-input multiple-output (MIMO) communication system. We propose novel precoding and decoding schemes which enhance system…

Information Theory · Computer Science 2022-05-09 Aravindh Krishnamoorthy , Robert Schober

Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory consumption of GAN-based SR (usually generators) causes performance…

Hardware Architecture · Computer Science 2021-07-28 Wenlong Cheng , Mingbo Zhao , Zhiling Ye , Shuhang Gu

Coded caching scheme, which is an effective technique to increase the transmission efficiency during peak traffic times, has recently become quite popular among the coding community. Generally rate can be measured to the transmission in the…

Information Theory · Computer Science 2017-10-03 Minquan Cheng , Qifa Yan , Xiaohu Tang , Jing Jiang

The power consumption of digital-to-analog converters (DACs) constitutes a significant proportion of the total power consumption in a massive multiuser multiple-input multiple-output (MU-MIMO) base station (BS). Using 1-bit DACs can…

Signal Processing · Electrical Eng. & Systems 2019-06-11 Lei Chu , Fei Wen , Lily Li , Robert Qiu

Random projection, a dimensionality reduction technique, has been found useful in recent years for reducing the size of optimization problems. In this paper, we explore the use of sparse sub-gaussian random projections to approximate…

Optimization and Control · Mathematics 2024-06-21 Monse Guedes-Ayala , Pierre-Louis Poirion , Lars Schewe , Akiko Takeda
‹ Prev 1 8 9 10 Next ›