Empirical geometry-based random-cluster model for high-speed-train channels in UMTS networks
(2015) In IEEE Transactions on Intelligent Transportation Systems 16(5). p.2850-2861- Abstract
In this paper, a recently conducted measurement campaign for high-speed-train (HST) channels is introduced, where the downlink signals of an in-service Universal Mobile Terrestrial System (UMTS) deployed along an HST railway between Beijing and Shanghai were acquired. The channel impulse responses (CIRs) are extracted from the data received in the common pilot channels (CPICHs). Within 1318 km, 144 base stations (BSS) were detected. Multipath components (MPCs) estimated from the CIRs are clustered and associated across the time slots. The results show that, limited by the sounding bandwidth of 3.84 MHz, most of the channels contain a single line-of-sight (LoS) cluster, and the rest consists of several LoS clusters due to distributed... (More)
In this paper, a recently conducted measurement campaign for high-speed-train (HST) channels is introduced, where the downlink signals of an in-service Universal Mobile Terrestrial System (UMTS) deployed along an HST railway between Beijing and Shanghai were acquired. The channel impulse responses (CIRs) are extracted from the data received in the common pilot channels (CPICHs). Within 1318 km, 144 base stations (BSS) were detected. Multipath components (MPCs) estimated from the CIRs are clustered and associated across the time slots. The results show that, limited by the sounding bandwidth of 3.84 MHz, most of the channels contain a single line-of-sight (LoS) cluster, and the rest consists of several LoS clusters due to distributed antennas, leaking cable, or neighboring BSS sharing the same CPICH. A new geometry-based random-cluster model is established for the clusters' behavior in delay and Doppler domains. Different from conventional models, the time-evolving behaviors of clusters are characterized by random geometrical parameters, i.e., the relative position of BS to railway, and the train speed. The distributions of these parameters, and the per-cluster path loss, shadowing, delay, and Doppler spreads, are extracted from the measurement data.
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- author
- Yin, Xuefeng ; Cai, Xuesong LU ; Cheng, Xiang ; Chen, Jiajing and Tian, Meng
- publishing date
- 2015-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Geometry-based stochastic model, high speed train, random cluster model, time-variant channel, Universal Mobile Terrestrial System
- in
- IEEE Transactions on Intelligent Transportation Systems
- volume
- 16
- issue
- 5
- article number
- 7110601
- pages
- 12 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:84929832705
- ISSN
- 1524-9050
- DOI
- 10.1109/TITS.2015.2428731
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2000-2011 IEEE.
- id
- 812aaad9-bd3f-448f-8fd7-4a20632b1047
- date added to LUP
- 2021-11-22 22:25:29
- date last changed
- 2022-07-13 20:58:08
@article{812aaad9-bd3f-448f-8fd7-4a20632b1047,
abstract = {{<p>In this paper, a recently conducted measurement campaign for high-speed-train (HST) channels is introduced, where the downlink signals of an in-service Universal Mobile Terrestrial System (UMTS) deployed along an HST railway between Beijing and Shanghai were acquired. The channel impulse responses (CIRs) are extracted from the data received in the common pilot channels (CPICHs). Within 1318 km, 144 base stations (BSS) were detected. Multipath components (MPCs) estimated from the CIRs are clustered and associated across the time slots. The results show that, limited by the sounding bandwidth of 3.84 MHz, most of the channels contain a single line-of-sight (LoS) cluster, and the rest consists of several LoS clusters due to distributed antennas, leaking cable, or neighboring BSS sharing the same CPICH. A new geometry-based random-cluster model is established for the clusters' behavior in delay and Doppler domains. Different from conventional models, the time-evolving behaviors of clusters are characterized by random geometrical parameters, i.e., the relative position of BS to railway, and the train speed. The distributions of these parameters, and the per-cluster path loss, shadowing, delay, and Doppler spreads, are extracted from the measurement data.</p>}},
author = {{Yin, Xuefeng and Cai, Xuesong and Cheng, Xiang and Chen, Jiajing and Tian, Meng}},
issn = {{1524-9050}},
keywords = {{Geometry-based stochastic model; high speed train; random cluster model; time-variant channel; Universal Mobile Terrestrial System}},
language = {{eng}},
number = {{5}},
pages = {{2850--2861}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Intelligent Transportation Systems}},
title = {{Empirical geometry-based random-cluster model for high-speed-train channels in UMTS networks}},
url = {{http://dx.doi.org/10.1109/TITS.2015.2428731}},
doi = {{10.1109/TITS.2015.2428731}},
volume = {{16}},
year = {{2015}},
}