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This paper presents a novel compressed sensing (CS) approach to high dimensional wireless channel estimation by optimizing the input to a deep generative network. Channel estimation using generative networks relies on the assumption that…

Signal Processing · Electrical Eng. & Systems 2020-06-25 Eren Balevi , Akash Doshi , Ajil Jalal , Alexandros Dimakis , Jeffrey G. Andrews

We develop a broadband channel estimation algorithm for millimeter wave (mmWave) multiple input multiple output (MIMO) systems with few-bit analog-to-digital converters (ADCs). Our methodology exploits the joint sparsity of the mmWave MIMO…

Information Theory · Computer Science 2017-12-07 Jianhua Mo , Philip Schniter , Robert W. Heath

Millimeter wave (mmWave) spectrum has drawn attention due to its tremendous available bandwidth. The high propagation losses in the mmWave bands necessitate beamforming with a large number of antennas. Traditionally each antenna is paired…

Information Theory · Computer Science 2018-05-31 Junmo Sung , Jinseok Choi , Brian L. Evans

Receivers with one-bit analog-to-digital converters (ADCs) are promising for high bandwidth millimeter wave (mmWave) systems as they consume less power than their full resolution counterparts. The extreme quantization in one-bit receivers…

Signal Processing · Electrical Eng. & Systems 2020-02-11 Nitin Jonathan Myers , Kayla N. Tran , Robert W. Heath

The estimation of millimeter wave (mmWave) massive multiple input multiple output (MIMO) channels becomes compelling when one-bit analog to digital converters (ADCs) are utilized. Furthermore, as the number of antenna increases, pilot…

Signal Processing · Electrical Eng. & Systems 2024-01-04 Erhan Karakoca , Hasan Nayir , Ali Görçin , Khalid Qaraqe

We consider the problem of pilot-aided, uplink channel estimation in a distributed massive multiple-input multiple-output (MIMO) architecture, in which the access points are connected to a central processing unit via fiber-optical fronthaul…

Signal Processing · Electrical Eng. & Systems 2024-07-08 Alireza Bordbar , Lise Aabel , Christian Häger , Christian Fager , Giuseppe Durisi

Channel estimation is a challenging task, especially in a massive multiple-input multiple-output (MIMO) system with one-bit analog-to-digital converters (ADC). Traditional deep learning (DL) methods, that learn the mapping from inputs to…

Signal Processing · Electrical Eng. & Systems 2021-06-04 Yudi Dong , Huaxia Wang , Yu-Dong Yao

This paper considers uplink massive MIMO systems with 1-bit analog-to-digital converters (ADCs) and develops a deep-learning based channel estimation framework. In this framework, the prior channel estimation observations and deep neural…

Information Theory · Computer Science 2020-05-11 Yu Zhang , Muhammad Alrabeiah , Ahmed Alkhateeb

Communication at high carrier frequencies such as millimeter wave (mmWave) and terahertz (THz) requires channel estimation for very large bandwidths at low SNR. Hence, allocating an orthogonal pilot tone for each coherence bandwidth leads…

Signal Processing · Electrical Eng. & Systems 2020-12-23 Eren Balevi , Jeffrey G. Andrews

Channel estimation is a critical task in multiple-input multiple-output (MIMO) digital communications that substantially effects end-to-end system performance. In this work, we introduce a novel approach for channel estimation using deep…

Signal Processing · Electrical Eng. & Systems 2022-11-09 Marius Arvinte , Jonathan I Tamir

In large-scale antenna systems, using one-bit analog-to-digital converters (ADCs) has recently become important since they offer significant reductions in both power and cost. However, in contrast to high-resolution ADCs, the coarse…

Information Theory · Computer Science 2022-07-19 In-soo Kim , Namyoon Lee , Junil Choi

Channel estimation is a critical task in digital communications that greatly impacts end-to-end system performance. In this work, we introduce a novel approach for multiple-input multiple-output (MIMO) channel estimation using score-based…

Signal Processing · Electrical Eng. & Systems 2022-02-16 Marius Arvinte , Jonathan I Tamir

Along with the prosperity of generative artificial intelligence (AI), its potential for solving conventional challenges in wireless communications has also surfaced. Inspired by this trend, we investigate the application of the advanced…

Information Theory · Computer Science 2026-03-10 Xingyu Zhou , Le Liang , Jing Zhang , Peiwen Jiang , Yong Li , Shi Jin

We investigate the information-theoretic throughout achievable on a fading communication link when the receiver is equipped with one-bit analog-to-digital converters (ADCs). The analysis is conducted for the setting where neither the…

Information Theory · Computer Science 2015-05-06 Sven Jacobsson , Giuseppe Durisi , Mikael Coldrey , Ulf Gustavsson , Christoph Studer

In this article, deep learning is applied to estimate the uplink channels for mixed analog-to-digital converters (ADCs) massive multiple-input multiple-output (MIMO) systems, where a portion of antennas are equipped with high-resolution…

Information Theory · Computer Science 2019-08-20 Shen Gao , Peihao Dong , Zhiwen Pan , Geoffrey Ye Li

This paper focuses on channel estimation in single-user and multi-user MIMO systems with multi-antenna base stations equipped with 1-bit spatial sigma-delta analog-to-digital converters (ADCs). A careful selection of the quantization…

Signal Processing · Electrical Eng. & Systems 2021-09-21 R. S. Prasobh Sankar , Sundeep Prabhakar Chepuri

This paper considers the channel estimation problem for massive multiple-input multiple-output (MIMO) systems that use one-bit analog-to-digital converters (ADCs). Previous channel estimation techniques for massive MIMO using one-bit ADCs…

Information Theory · Computer Science 2022-06-28 Hwanjin Kim , Junil Choi

The use of one-bit analog-to-digital converter (ADC) has been considered as a viable alternative to high resolution counterparts in realizing and commercializing massive multiple-input multiple-output (MIMO) systems. However, the issue of…

Information Theory · Computer Science 2024-03-04 Majdoddin Esfandiari , Sergiy A. Vorobyov , Robert W. Heath

It is well accepted that acquiring downlink channel state information in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems is challenging because of the large overhead in training and feedback. In this…

Information Theory · Computer Science 2022-05-18 Javad Mirzaei , Shahram ShahbazPanahi , Raviraj Adve , Navaneetha Gopal

We develop a direction of arrival (DoA) and channel estimation algorithm for the one-bit quantized millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) system. By formulating the estimation problem as a noisy one-bit…

Signal Processing · Electrical Eng. & Systems 2019-09-24 Liangyuan Xu , Feifei Gao , Cheng Qian
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