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Inner and outer bounds are established on the capacity region of two-sender, two-receiver interference channels where one transmitter knows both messages. The transmitter with extra knowledge is referred to as being cognitive. The inner…

Information Theory · Computer Science 2007-10-22 I. Maric , A. Goldsmith , G. Kramer , S. Shamai

Consider a multihop wireless network serving multiple flows in which wireless link interference constraints are described by a link interference graph. For such a network, we design routing-scheduling policies that maximize the end-to-end…

Networking and Internet Architecture · Computer Science 2017-09-13 Rahul Singh , P. R. Kumar , Eytan Modiano

Low-resolution digital-to-analog and analog-to-digital converters (DACs and ADCs) have attracted considerable attention in efforts to reduce power consumption in millimeter wave (mmWave) and massive MIMO systems. This paper presents an…

Information Theory · Computer Science 2020-08-04 Sourjya Dutta , Abbas Khalili , Elza Erkip , Sundeep Rangan

We study ensemble-based graph-theoretical methods aiming to approximate the size of the minimum dominating set (MDS) in scale-free networks. We analyze both analytical upper bounds of dominating sets and numerical realizations for…

Physics and Society · Physics 2014-09-23 F. Molnár , N. Derzsy , É. Czabarka , L. Székely , B. K. Szymanski , G. Korniss

This paper studies the capacity of the two-user intensity-modulation/direct-detection (IM/DD) interference channel (IC), which is relevant in the context of multi-user optical wireless communications. Despite some known single-letter…

Information Theory · Computer Science 2022-07-05 Zhenyu Zhang , Anas Chaaban

We develop upper bounds on code size for an independent and identically distributed deletion and insertion channels for a given code length and target frame error probability. The bounds are obtained as a variation of a general converse…

Information Theory · Computer Science 2026-04-14 Ruslan Morozov , Tolga Mete Duman

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

We consider a $K$-user multiple-input single-output (MISO) broadcast channel (BC) where the channel state information (CSI) of user $i(i=1,2,\ldots,K)$ may be instantaneously perfect (P), delayed (D) or not known (N) at the transmitter with…

Information Theory · Computer Science 2016-01-28 Borzoo Rassouli , Chenxi Hao , Bruno Clerckx

A modification is proposed for the formula known from the literature that characterizes the boundary of the capacity region of Gaussian multiaccess fading channels. The modified version takes into account potentially negative arguments of…

Information Theory · Computer Science 2008-10-22 Mohamed Shaqfeh , Norbert Goertz

In this paper, we characterize the degrees of freedom (DoF) for $K $-user $M \times 1 $ multiple-input single-output interference channels with reconfigurable antennas which have multiple preset modes at the receivers, assuming linear…

Information Theory · Computer Science 2016-02-15 Heecheol Yang , Wonjae Shin , Jungwoo Lee

One of the important unsolved problems in information theory is the conjecture that network coding has no rate benefit over routing in undirected unicast networks. Three known bounds on the symmetric rate in undirected unicast information…

Information Theory · Computer Science 2020-10-27 Mohammad Ishtiyaq Qureshi , Satyajit Thakor

This paper studies the interpretability of neural network features from a Bayesian Gaussian view, where optimizing a cost is reaching a probabilistic bound; learning a model approximates a density that makes the bound tight and the cost…

Machine Learning · Computer Science 2025-11-18 Bo Hu , Jose C. Principe

Recent work has characterized the sum capacity of time-varying/frequency-selective wireless interference networks and $X$ networks within $o(\log({SNR}))$, i.e., with an accuracy approaching 100% at high SNR (signal to noise power ratio).…

Information Theory · Computer Science 2012-04-03 Viveck R. Cadambe , Syed A. Jafar

In this paper, we study upper bounds on the sum capacity of the downlink multicell processing model with finite backhaul capacity for the simple case of 2 base stations and 2 mobile users. It is modelled as a two-user multiple access…

Information Theory · Computer Science 2016-09-06 Tianyu Yang , Nan Liu , Wei Kang , Shlomo Shamai

Wireless fading networks with multiple antennas are typically studied information-theoretically from two different perspectives - the outage characterization and the ergodic capacity characterization. A key parameter in the outage…

Information Theory · Computer Science 2008-02-14 K. Sreeram , S. Birenjith , P. Vijay Kumar

The paper presents a generalization bound for quantum neural networks based on a dynamical Lie algebra. Using covering numbers derived from a dynamical Lie algebra, the Rademacher complexity is derived to calculate the generalization bound.…

Quantum Physics · Physics 2025-04-15 Hiroshi Ohno

Opportunistic analysis has traditionally relied on independence assumptions that break down in many interesting and useful network topologies. This paper develops techniques that expand opportunistic analysis to a broader class of networks,…

Information Theory · Computer Science 2015-03-19 Mohamed Abouelseoud , Aria Nosratinia

We derive bounds on the noncoherent capacity of wide-sense stationary uncorrelated scattering (WSSUS) channels that are selective both in time and frequency, and are underspread, i.e., the product of the channel's delay spread and Doppler…

Information Theory · Computer Science 2016-11-15 Giuseppe Durisi , Ulrich G. Schuster , Helmut Bölcskei , Shlomo Shamai

We consider the distributed optimization problem for the sum of convex functions where the underlying communications network connecting agents at each time is drawn at random from a collection of directed graphs. Building on an earlier work…

Optimization and Control · Mathematics 2020-09-16 Pouya Rezaeinia , Bahman Gharesifard

Generalization bounds are a critical tool to assess the training data requirements of Quantum Machine Learning (QML). Recent work has established guarantees for in-distribution generalization of quantum neural networks (QNNs), where…

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