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Sparse superposition codes, also called sparse regression codes (SPARCs), are a class of codes for efficient communication over the AWGN channel at rates approaching the channel capacity. In a standard SPARC, codewords are sparse linear…

Information Theory · Computer Science 2021-06-25 Cynthia Rush , Kuan Hsieh , Ramji Venkataramanan

We determine the rank of a random matrix over an arbitrary field with prescribed numbers of non-zero entries in each row and column. As an application we obtain a formula for the rate of low-density parity check codes. This formula…

Combinatorics · Mathematics 2024-06-21 Amin Coja-Oghlan , Alperen A. Ergür , Pu Gao , Samuel Hetterich , Maurice Rolvien

Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-rank components. Such a problem arises in a number of…

Optimization and Control · Mathematics 2011-08-09 Venkat Chandrasekaran , Sujay Sanghavi , Pablo A. Parrilo , Alan S. Willsky

Due to the short and bursty incoming messages, channel access activities in a wireless random access system are often fractional. The lack of frequent data support consequently makes it difficult for the receiver to estimate and track the…

Information Theory · Computer Science 2011-10-11 Zheng Wang , Jie Luo

In this paper, we prove the existence of capacity achieving linear codes with random binary sparse generating matrices. The results on the existence of capacity achieving linear codes in the literature are limited to the random binary codes…

Information Theory · Computer Science 2011-08-31 A. Makhdoumi Kakhaki , H. Karkeh Abadi , P. Pad , H. Saeedi , F. Marvasti , K. Alishahi

An approach is established for maximizing the Lower bound on the Mismatch capacity (hereafter abbreviated as LM rate), a key performance bound in mismatched decoding, by optimizing the channel input probability distribution. Under a fixed…

Information Theory · Computer Science 2024-05-02 Lingyi Chen , Shitong Wu , Xinwei Li , Huihui Wu , Hao Wu , Wenyi Zhang

We consider communication over a noisy network under randomized linear network coding. Possible error mechanism include node- or link- failures, Byzantine behavior of nodes, or an over-estimate of the network min-cut. Building on the work…

Information Theory · Computer Science 2007-11-27 Andrea Montanari , Ruediger Urbanke

In this survey, we provide a detailed review of recent advances in the recovery of continuous domain multidimensional signals from their few non-uniform (multichannel) measurements using structured low-rank matrix completion formulation.…

Computer Vision and Pattern Recognition · Computer Science 2020-02-19 Mathews Jacob , Merry P. Mani , Jong Chul Ye

Matrices with low-rank structure are ubiquitous in scientific computing. Choosing an appropriate rank is a key step in many computational algorithms that exploit low-rank structure. However, estimating the rank has been done largely in an…

Numerical Analysis · Mathematics 2024-01-08 Maike Meier , Yuji Nakatsukasa

In the context of the compressed sensing problem, we propose a new ensemble of sparse random matrices which allow one (i) to acquire and compress a {\rho}0-sparse signal of length N in a time linear in N and (ii) to perfectly recover the…

Information Theory · Computer Science 2013-04-15 Maria Chiara Angelini , Federico Ricci-Tersenghi , Yoshiyuki Kabashima

Composed of multiple interconnected pixels controlled by on/off RF switches, the pixel antenna can generate reconfigurable radiation patterns that can be further exploited to construct diverse pilot sequences for effective channel…

Signal Processing · Electrical Eng. & Systems 2026-05-19 Yiting Chen , Yumeng Zhang , Hongyu Li

The matrix completion problem aims to reconstruct a low-rank matrix based on a revealed set of possibly noisy entries. Prior works consider completing the entire matrix with generalization error guarantees. However, the completion accuracy…

Machine Learning · Computer Science 2023-12-19 Elad Hazan , Adam Tauman Kalai , Varun Kanade , Clara Mohri , Y. Jennifer Sun

This paper applies Information Theoretic analysis to packet-based random multiple access communication systems. A new channel coding approach is proposed for coding within each data packet with built-in support for bursty traffic…

Information Theory · Computer Science 2016-11-17 Jie Luo , Anthony Ephremides

Batched network coding is a variation of random linear network coding which has low computational and storage costs. In order to adapt to random fluctuations in the number of erasures in individual batches, it is not optimal to recode and…

Information Theory · Computer Science 2021-09-16 Hoover H. F. Yin , Bin Tang , Ka Hei Ng , Shenghao Yang , Xishi Wang , Qiaoqiao Zhou

As a typical dimensionality reduction technique, random projection can be simply implemented with linear projection, while maintaining the pairwise distances of high-dimensional data with high probability. Considering this technique is…

Machine Learning · Computer Science 2014-10-14 Weizhi Lu , Weiyu Li , Kidiyo Kpalma , Joseph Ronsin

This paper considers the multiple-access relay channel in a setting where two source nodes transmit packets to a destination node, both directly and via a relay node, over packet erasure channels. Intra-session network coding is used at the…

Information Theory · Computer Science 2022-03-08 Amjad Saeed Khan , Ioannis Chatzigeorgiou

We consider stability of scheduled multiaccess message communication with random coding and joint maximum-likehood decoding of messages. The framework we consider here models both the random message arrivals and the subsequent reliable…

Information Theory · Computer Science 2007-07-13 KCV Kalyanarama Sesha Sayee , Utpal Mukherji

In "On Coding for Reliable Communication over Packet Networks" (Lun, Medard, and Effros, Proc. 42nd Annu. Allerton Conf. Communication, Control, and Computing, 2004), a capacity-achieving coding scheme for unicast or multicast over lossy…

Information Theory · Computer Science 2007-07-16 Desmond S. Lun , Muriel Medard , Ralf Koetter , Michelle Effros

In this paper, we propose two new algorithms for transduction with Matrix Completion (MC) problem. The joint MC and prediction tasks are addressed simultaneously to enhance the accuracy, i.e., the label matrix is concatenated to the data…

Machine Learning · Computer Science 2018-05-22 Ashkan Esmaeili , Kayhan Behdin , Mohammad Amin Fakharian , Farokh Marvasti

Data gathering operations in remote locations often rely on relay drones, which collect, store and deliver transmitted information to a ground control station. The probability of the ground control station successfully reconstructing the…

Information Theory · Computer Science 2022-03-08 Ioannis Chatzigeorgiou