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相关论文: Sparse Channel Estimation in Wideband Systems with…

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We consider channel estimation within pulse-shaping multicarrier multiple-input multiple-output (MIMO) systems transmitting over doubly selective MIMO channels. This setup includes MIMO orthogonal frequency-division multiplexing (MIMO-OFDM)…

信息论 · 计算机科学 2016-08-03 Daniel Eiwen , Georg Tauboeck , Franz Hlawatsch , Hans Georg Feichtinger

This letter investigates channel estimation for ultra-massive multiple-input multiple-output (MIMO) communications. We propose a joint low-rank and sparse Bayesian estimation (LRSBE) algorithm for spatial non-stationary ultra-massive…

信息论 · 计算机科学 2025-12-05 Jianghan Ji , Cheng-Xiang Wang , Shuaifei Chen , Chen Huang , Xiping Wu , Emil Björnson

In this paper, we introduce a wideband dictionary framework for estimating sparse signals. By formulating integrated dictionary elements spanning bands of the considered parameter space, one may efficiently find and discard large parts of…

统计方法学 · 统计学 2018-08-01 Maksim Butsenko , Johan Swärd , Andreas Jakobsson

This paper investigates channel estimation for linear time-varying (LTV) wireless channels under double sparsity, i.e., sparsity in both the delay and Doppler domains. An on-grid approximation is first considered, enabling rigorous…

信息论 · 计算机科学 2025-11-10 Wissal Benzine , Ali Bemani , Nassar Ksairi , Dirk Slock

We consider the problem of channel estimation for millimeter wave (mmWave) systems, where, to minimize the hardware complexity and power consumption, an analog transmit beamforming and receive combining structure with only one radio…

信息论 · 计算机科学 2017-05-09 Xingjian Li , Jun Fang , Hongbin Li , Pu Wang

We propose new compressive parameter estimation algorithms that make use of polar interpolation to improve the estimator precision. Our work extends previous approaches involving polar interpolation for compressive parameter estimation in…

信息论 · 计算机科学 2016-11-17 Karsten Fyhn , Marco F. Duarte , Søren Holdt Jensen

This paper introduces a Compressed Sensing (CS) estimation scheme for Orthogonal Time Frequency Space (OTFS) channels with sparse multipath. The OTFS waveform represents signals in a two dimensional Delay-Doppler (DD) orthonormal basis. The…

信息论 · 计算机科学 2021-11-25 Felipe Gómez-Cuba

This paper investigates the sparse channel estimation for holographic multiple-input multiple-output (HMIMO) systems. Given that the wavenumber-domain representation is based on a series of Fourier harmonics that are in essence a series of…

信号处理 · 电气工程与系统科学 2024-06-14 Yuqing Guo , Yuanbin Chen , Ying Wang

Wireless OFDM channels can be approximated by a time varying filter with sparse time domain taps. Recent achievements in sparse signal processing such as compressed sensing have facilitated the use of sparsity in estimation, which improves…

信息论 · 计算机科学 2009-01-27 Mahdi Soltanolkotabi , Arash Amini , Farokh Marvasti

Time delay estimation arises in many applications in which a multipath medium has to be identified from pulses transmitted through the channel. Various approaches have been proposed in the literature to identify time delays introduced by…

信息论 · 计算机科学 2011-01-05 Kfir Gedalyahu , Yonina C. Eldar

Hybrid analog and digital precoding allows millimeter wave (mmWave) systems to achieve both array and multiplexing gain. The design of the hybrid precoders and combiners, though, is usually based on knowledge of the channel. Prior work on…

信息论 · 计算机科学 2016-11-15 Kiran Venugopal , Ahmed Alkhateeb , Nuria González Prelcic , Robert W. Heath

Broadband wireless channel is a time dispersive and becomes strongly frequency selective. In most cases, the channel is composed of a few dominant coefficients and a large part of coefficients is approximately zero or zero. To exploit the…

信息论 · 计算机科学 2010-05-14 Guan Gui , Wei Peng , Qun Wan , Fumiyuki Adachi

This paper proposes an off-grid channel estimation scheme for orthogonal time-frequency space (OTFS) systems adopting the sparse Bayesian learning (SBL) framework. To avoid channel spreading caused by the fractional delay and Doppler shifts…

信息论 · 计算机科学 2021-01-15 Zhiqiang Wei , Weijie Yuan , Shuangyang Li , Jinhong Yuan , Derrick Wing Kwan Ng

It is now well understood that (1) it is possible to reconstruct sparse signals exactly from what appear to be highly incomplete sets of linear measurements and (2) that this can be done by constrained L1 minimization. In this paper, we…

统计方法学 · 统计学 2007-11-13 Emmanuel J. Candes , Michael B. Wakin , Stephen P. Boyd

This paper investigates the uplink channel estimation of the millimeter-wave (mmWave) extremely large-scale multiple-input-multiple-output (XL-MIMO) communication system in the beam-delay domain, taking into account the near-field and…

信号处理 · 电气工程与系统科学 2024-10-28 Hongwei Hou , Xuan He , Tianhao Fang , Xinping Yi , Wenjin Wang , Shi Jin

This paper develops a channel estimation technique for millimeter wave (mmWave) communication systems. Our method exploits the sparse structure in mmWave channels for low training overhead and accounts for the phase errors in the channel…

信号处理 · 电气工程与系统科学 2023-10-12 Weijia Yi , Nitin Jonathan Myers , Geethu Joseph

The multipath radio channel is considered to have a non-bandlimited channel impulse response. Therefore, it is challenging to achieve high resolution time-delay (TD) estimation of multipath components (MPCs) from bandlimited observations of…

信号处理 · 电气工程与系统科学 2019-12-11 Tarik Kazaz , Gerard J. M. Janssen , Alle-Jan van der Veen

Multiple wireless sensing tasks, e.g., radar detection for driver safety, involve estimating the "channel" or relationship between signal transmitted and received. In this work, we focus on a certain channel model known as the delay-doppler…

信息论 · 计算机科学 2020-11-24 Alisha Zachariah

Orthogonal time frequency space (OTFS) modulation outperforms orthogonal frequency division multiplexing (OFDM) in high-mobility scenarios. One challenge for OTFS massive MIMO is downlink channel estimation due to the large number of base…

信息论 · 计算机科学 2019-06-26 Wenqian Shen , Linglong Dai , Jianping An , Pingzhi Fan , Robert W. Heath,

Existing methods for sparse channel estimation typically provide an estimate computed as the solution maximizing an objective function defined as the sum of the log-likelihood function and a penalization term proportional to the l1-norm of…