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Iterative thresholding algorithms are well-suited for high-dimensional problems in sparse recovery and compressive sensing. The performance of this class of algorithms depends heavily on the tuning of certain threshold parameters. In…

Information Theory · Computer Science 2013-11-04 Ali Mousavi , Arian Maleki , Richard G. Baraniuk

We study the compressed sensing reconstruction problem for a broad class of random, band-diagonal sensing matrices. This construction is inspired by the idea of spatial coupling in coding theory. As demonstrated heuristically and…

Information Theory · Computer Science 2015-03-19 David L. Donoho , Adel Javanmard , Andrea Montanari

We consider a multiple-input multiple-output (MIMO) multiple access channel (MAC), where the channel between each transmitter and the receiver is modeled by the doubly-scattering channel model. Based on novel techniques from random matrix…

Information Theory · Computer Science 2011-05-11 Jakob Hoydis , Romain Couillet , Merouane Debbah

This work explores multi-modal inference in a high-dimensional simplified model, analytically quantifying the performance gain of multi-modal inference over that of analyzing modalities in isolation. We present the Bayes-optimal performance…

Machine Learning · Statistics 2025-09-30 Christian Keup , Lenka Zdeborová

In this paper, we analyze the symbol error rate (SER) performance of the simultaneous wireless information and power transfer (SWIPT) enabled three-node differential decode-and-forward (DDF) relay networks, which adopt the power splitting…

Information Theory · Computer Science 2020-05-08 Yuxin Lu , Wai Ho Mow

In theory coordinated multi-point transmission (CoMP) promises vast gains in spectral efficiency. But industrial field trials show rather disappointing throughput gains, whereby the major limiting factor is proper sharing of channel state…

Information Theory · Computer Science 2016-11-18 Jan Schreck , Gerhard Wunder , Peter Jung

Differential spatial modulation (DSM) exploits the time dimension to facilitate the differential modulation, which can perfectly avoid the challenge in acquiring of heavily entangled channel state information of visible light communication…

Signal Processing · Electrical Eng. & Systems 2024-09-11 Zichun Shi , Pu Miao , Peng Chen , Lei Xue , Li-Yang Zheng , Laiyuan Wang , Gaojie Chen

A simple geometric shaping method is proposed for optical wireless communication systems based on intensity modulation and direct detection (IM/DD) from an information-theoretic perspective. Constellations consisting of equiprobable levels…

Information Theory · Computer Science 2024-12-03 Suhua Zhou , Tianqi Li , Zhaoxi Fang , Jing Zhou , Wenyi Zhang

This work proposes a blind adaptive reduced-rank scheme and constrained constant-modulus (CCM) adaptive algorithms for interference suppression in wireless communications systems. The proposed scheme and algorithms are based on a two-stage…

Information Theory · Computer Science 2013-01-10 Rodrigo C. de Lamare , Raimundo Sampaio-Neto , Martin Haardt

This paper considers error probabilities of random codes for memoryless channels in the fixed-rate regime. Random coding is a fundamental scheme to achieve the channel capacity and many studies have been conducted for the asymptotics of the…

Information Theory · Computer Science 2017-07-17 Junya Honda

In this paper, we propose a sparse signal estimation algorithm that is suitable for many wireless communication systems, especially for the future millimeter wave and underwater communication systems. This algorithm is not only…

Information Theory · Computer Science 2018-07-20 Chongwen Huang , Lei Liu , Chau Yuen

We propose a blind ML-based modulation detection for OFDM-based technologies. Unlike previous works that assume an ideal environment with precise knowledge of subcarrier count and cyclic prefix location, we consider blind modulation…

Machine Learning · Computer Science 2024-08-16 Ali Pourranjbar , Georges Kaddoum , Verdier Assoume Mba , Sahil Garg , Satinder Singh

Approximate message passing (AMP) algorithms have shown great promise in sparse signal reconstruction due to their low computational requirements and fast convergence to an exact solution. Moreover, they provide a probabilistic framework…

Sound · Computer Science 2018-02-02 Turab Iqbal , Wenwu Wang

The generalized approximate message passing (GAMP) algorithm under the Bayesian setting shows advantage in recovering under-sampled sparse signals from corrupted observations. Compared to conventional convex optimization methods, it has a…

Information Theory · Computer Science 2017-01-12 Shuai Huang , Trac D. Tran

Approximate Message Passing (AMP) algorithms are a family of iterative algorithms based on large random matrices with the special property of tracking the statistical properties of their iterates. They are used in various fields such as…

Probability · Mathematics 2025-03-27 Mohammed-Younes Gueddari , Walid Hachem , Jamal Najim

We present a simple randomized algorithm for approximate matrix multiplication (AMM) whose error scales with the *output* norm $\|AB\|_F$. Given any $n\times n$ matrices $A,B$ and a runtime parameter $r\leq n$, the algorithm produces in…

Data Structures and Algorithms · Computer Science 2026-02-05 Yahel Uffenheimer , Omri Weinstein

An adaptive joint power allocation (JPA) and linear receiver design algorithm using the minimum bit error rate (MBER) criterion for a cooperative Multiple-Input Multiple-Output (MIMO) network is proposed. The system employs multiple relays…

Information Theory · Computer Science 2013-03-21 Tong Peng , Rodrigo C. de Lamare , Anke Schmeink

Media-based modulation (MBM) is a novel modulation technique that can improve the spectral efficiency of the existing wireless systems. In MBM, multiple radio frequency (RF) mirrors are placed near the transmit antenna(s) and are switched…

Information Theory · Computer Science 2021-01-07 Manish Mandloi , Devendra Singh Gurjar

The common approach of designing a communication device is to maximize a well-defined objective function, e.g., the channel capacity and the cut-off rate. We propose easy-to-implement solutions for Gaussian channels that approximate the…

Information Theory · Computer Science 2016-03-24 Qian Yu

We consider the problem of reconstructing a signal from multi-layered (possibly) non-linear measurements. Using non-rigorous but standard methods from statistical physics we present the Multi-Layer Approximate Message Passing (ML-AMP)…

Information Theory · Computer Science 2020-01-22 Andre Manoel , Florent Krzakala , Marc Mézard , Lenka Zdeborová