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Related papers: Generalized Nearest Neighbor Decoding

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This paper addresses optimal decoding strategies in lossy compression where the assumed distribution for compressor design mismatches the actual (true) distribution of the source. This problem has immediate relevance in standardized…

Information Theory · Computer Science 2026-02-04 Saeed R. Khosravirad , Ahmed Alkhateeb , Ingrid van de Voorde

In this paper, a class of relay networks is considered. We assume that, at a node, outgoing channels to its neighbors are orthogonal, while incoming signals from neighbors can interfere with each other. We are interested in the multicast…

Information Theory · Computer Science 2016-11-17 Wooseok Nam , Sae-Young Chung , Yong H. Lee

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

This paper considers the problem of covert communication with mismatched decoding, in which a sender wishes to reliably communicate with a receiver whose decoder is fixed and possibly sub-optimal, and simultaneously to ensure that the…

Information Theory · Computer Science 2021-11-11 Qiaosheng Zhang , Vincent Y. F. Tan

The k-nearest neighbors (k-NN) is a basic machine learning (ML) algorithm, and several quantum versions of it, employing different distance metrics, have been presented in the last few years. Although the Euclidean distance is one of the…

Emerging Technologies · Computer Science 2024-04-25 Enrico Zardini , Enrico Blanzieri , Davide Pastorello

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang

We introduce Noise Recycling, a method that enhances decoding performance of channels subject to correlated noise without joint decoding. The method can be used with any combination of codes, code-rates and decoding techniques. In the…

Information Theory · Computer Science 2020-10-16 Alejandro Cohen , Amit Solomon , Ken R. Duffy , Muriel Médard

Nearest neighbor is a popular nonparametric method for classification and regression with many appealing properties. In the big data era, the sheer volume and spatial/temporal disparity of big data may prohibit centrally processing and…

Statistics Theory · Mathematics 2018-12-13 Jiexin Duan , Xingye Qiao , Guang Cheng

For the additive white Gaussian noise channel with average codeword power constraint, new coding methods are devised in which the codewords are sparse superpositions, that is, linear combinations of subsets of vectors from a given design,…

Information Theory · Computer Science 2010-06-21 Andrew R. Barron , Antony Joseph

We analyze coding for energy efficiency in relay channels at a fixed source rate. We first propose a half-duplex decode-forward coding scheme for the Gaussian relay channel. We then derive three optimal sets of power allocation, which…

Information Theory · Computer Science 2016-11-18 Fanny Parzysz , Mai Vu , François Gagnon

Interference alignment has emerged as a powerful tool in the analysis of multi-user networks. Despite considerable recent progress, the capacity region of the Gaussian K-user interference channel is still unknown in general, in part due to…

Information Theory · Computer Science 2016-11-15 Or Ordentlich , Uri Erez , Bobak Nazer

Feedback holds a pivotal role in practical communication schemes, even though it does not enhance channel capacity. Its main attribute includes adaptability in transmission that allows for a higher rate of convergence of the error…

Information Theory · Computer Science 2024-03-22 Ioannis Papoutsidakis , Robert J. Piechocki , Angela Doufexi

We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show…

Information Theory · Computer Science 2016-11-15 Andrew L. Jones , Ioannis Chatzigeorgiou , Andrea Tassi

The capacity of the Gaussian cognitive interference channel, a variation of the classical two-user interference channel where one of the transmitters (referred to as cognitive) has knowledge of both messages, is known in several parameter…

Information Theory · Computer Science 2016-11-17 Stefano Rini , Daniela Tuninetti , Natasha Devroye

In this paper, we consider full-duplex and half-duplex Gaussian relay channels where the noises at the relay and destination are arbitrarily correlated. We first derive the capacity upper bound and the achievable rates with three existing…

Information Theory · Computer Science 2016-11-17 Lili Zhang , Jinhua Jiang , Andrea J. Goldsmith , Shuguang Cui

A standard assumption in the design of ultra-reliable low-latency communication systems is that the duration between message arrivals is larger than the number of channel uses before the decoding deadline. Nevertheless, this assumption…

Information Theory · Computer Science 2025-01-31 Homa Nikbakht , Malcolm Egan , Jean-Marie Gorce , H. Vincent Poor

Gaussian channels with memory and with noiseless feedback have been widely studied in the information theory literature. However, a coding scheme to achieve the feedback capacity is not available. In this paper, a coding scheme is proposed…

Information Theory · Computer Science 2007-07-13 Jialing Liu , Nicola Elia

The two-user Gaussian interference channel with a shared out-of-band relay is considered. The relay observes a linear combination of the source signals and broadcasts a common message to the two destinations, through a perfect link of fixed…

Information Theory · Computer Science 2016-11-18 Peyman Razaghi , Song Nam Hong. Lei Zhou , Wei Yu , Giuseppe Caire

The problem of computing a linear combination of sources over a multiple access channel is studied. Inner and outer bounds on the optimal tradeoff between the communication rates are established when encoding is restricted to random…

Information Theory · Computer Science 2018-10-30 Pinar Sen , Sung Hoon Lim , Young-Han Kim

We study universal decoding over unknown discrete additive channels determined by a finite-state (unifilar) random process. Aiming at low-complexity decoders, we study variants of noise-guessing decoders that use estimators for the…

Information Theory · Computer Science 2025-07-24 Henrique K. Miyamoto , Sheng Yang
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