Cluster-head based feedback for simplified time reversal prefiltering in ultra-wideband systems

Hossein Soleimani; Stefano Tomasin; Tohid Alizadeh; Mohammad Shojafar

doi:10.1016/j.phycom.2017.09.005

Cluster-head based feedback for simplified time reversal prefiltering in ultra-wideband systems

Hossein Soleimani
, Stefano Tomasin
, Tohid Alizadeh
, Mohammad Shojafar

School of Engineering and Digital Sciences

University of Padua
University of Rome La Sapienza

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

Time-reversal prefiltering (TRP) technique for impulse radio (IR) ultra wide-band (UWB) systems requires a large amount of feedback to transmit the channel impulse response from the receiver to the transmitter. In this paper, we propose a new feedback design based on vector quantization. We use a machine learning algorithm to cluster the estimated channels into several groups and to select the channel cluster heads (CCHs) for feedback. In particular, CCHs and their labels are recorded at both side of the UWB transceivers and the label of the most similar CCH to the estimated channel is fed back to the transmitter. Finally, the TRP is applied using the feedback CCH. The proposed digital feedback provides three main advantages: (1) it significantly reduces the dedicated bandwidth required for feedback; (2) it considerably improves the speed of transceivers; and, (3) it is robust to noise in the feedback channel since few bytes are required to send the codes that can be heavily error protected. Numerical results on standard UWB channel models are discussed, showing the advantage of the proposed solution.

Original language	English
Pages (from-to)	100-109
Number of pages	10
Journal	Physical Communication
Volume	25
DOIs	https://doi.org/10.1016/j.phycom.2017.09.005
Publication status	Published - Dec 2017

Funding

Mohammad Shojafar is currently is a CNIT senior researcher at the University of Rome Tor Vergata to work on European H2020 Superfluidity project. Recently, he completed an Italian project named SAMMClouds project aims to address some of the open issues related to the Software as a Service (SaaS) and Infrastructure as a Service (IaaS) systems which is supported by the University of Modena and Reggio Emilia, Modena, Italy. He completed his Ph.D. in ICT at the Sapienza University of Rome in May 2016. He received his M.Sc. in software engineering in Qazvin Islamic Azad University, Qazvin, Iran in 2010. Also, he received his B.Sc. in computer engineering-software major in Iran university science and technology, Tehran, Iran in 2006. His current research focuses on 5G Cloud, distributed computing, wireless communications, and mathematical/AI optimization.

Keywords

Clustering channels
Digital feedback
IEEE 802.15.SG3 channel model
Machine learning
Prefiltering
Ultra wide-band (UWB)

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1016/j.phycom.2017.09.005

Cite this

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title = "Cluster-head based feedback for simplified time reversal prefiltering in ultra-wideband systems",

abstract = "Time-reversal prefiltering (TRP) technique for impulse radio (IR) ultra wide-band (UWB) systems requires a large amount of feedback to transmit the channel impulse response from the receiver to the transmitter. In this paper, we propose a new feedback design based on vector quantization. We use a machine learning algorithm to cluster the estimated channels into several groups and to select the channel cluster heads (CCHs) for feedback. In particular, CCHs and their labels are recorded at both side of the UWB transceivers and the label of the most similar CCH to the estimated channel is fed back to the transmitter. Finally, the TRP is applied using the feedback CCH. The proposed digital feedback provides three main advantages: (1) it significantly reduces the dedicated bandwidth required for feedback; (2) it considerably improves the speed of transceivers; and, (3) it is robust to noise in the feedback channel since few bytes are required to send the codes that can be heavily error protected. Numerical results on standard UWB channel models are discussed, showing the advantage of the proposed solution.",

keywords = "Clustering channels, Digital feedback, IEEE 802.15.SG3 channel model, Machine learning, Prefiltering, Ultra wide-band (UWB)",

author = "Hossein Soleimani and Stefano Tomasin and Tohid Alizadeh and Mohammad Shojafar",

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doi = "10.1016/j.phycom.2017.09.005",

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AU - Tomasin, Stefano

AU - Alizadeh, Tohid

AU - Shojafar, Mohammad

PY - 2017/12

Y1 - 2017/12

N2 - Time-reversal prefiltering (TRP) technique for impulse radio (IR) ultra wide-band (UWB) systems requires a large amount of feedback to transmit the channel impulse response from the receiver to the transmitter. In this paper, we propose a new feedback design based on vector quantization. We use a machine learning algorithm to cluster the estimated channels into several groups and to select the channel cluster heads (CCHs) for feedback. In particular, CCHs and their labels are recorded at both side of the UWB transceivers and the label of the most similar CCH to the estimated channel is fed back to the transmitter. Finally, the TRP is applied using the feedback CCH. The proposed digital feedback provides three main advantages: (1) it significantly reduces the dedicated bandwidth required for feedback; (2) it considerably improves the speed of transceivers; and, (3) it is robust to noise in the feedback channel since few bytes are required to send the codes that can be heavily error protected. Numerical results on standard UWB channel models are discussed, showing the advantage of the proposed solution.

AB - Time-reversal prefiltering (TRP) technique for impulse radio (IR) ultra wide-band (UWB) systems requires a large amount of feedback to transmit the channel impulse response from the receiver to the transmitter. In this paper, we propose a new feedback design based on vector quantization. We use a machine learning algorithm to cluster the estimated channels into several groups and to select the channel cluster heads (CCHs) for feedback. In particular, CCHs and their labels are recorded at both side of the UWB transceivers and the label of the most similar CCH to the estimated channel is fed back to the transmitter. Finally, the TRP is applied using the feedback CCH. The proposed digital feedback provides three main advantages: (1) it significantly reduces the dedicated bandwidth required for feedback; (2) it considerably improves the speed of transceivers; and, (3) it is robust to noise in the feedback channel since few bytes are required to send the codes that can be heavily error protected. Numerical results on standard UWB channel models are discussed, showing the advantage of the proposed solution.

KW - Clustering channels

KW - Digital feedback

KW - IEEE 802.15.SG3 channel model

KW - Machine learning

KW - Prefiltering

KW - Ultra wide-band (UWB)

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Cluster-head based feedback for simplified time reversal prefiltering in ultra-wideband systems

Abstract

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Keywords

ASJC Scopus subject areas

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