A General Coupling-Based Model Framework for Wideband MIMO Channels

Zhang, Yan; Edfors, Ove; Hammarberg, Peter; Hult, Tommy; Chen, Xiang; Zhou, Shidong; Xiao, Limin; Wang, Jing

doi:10.1109/tap.2011.2173436

Cited by 16 publications

(12 citation statements)

References 21 publications

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“…in the time-domain. Identical eigenspace formulation has been applied in the frequency-domain for CSI instead [18], and also validated with empirical capacity measurements. Since our subspace trackers are differential in nature, tracking is insensitive to the representation of the channel be it time-or frequencydomain.…”

Section: B Differential Subspace Evolutionmentioning

confidence: 99%

On Tracking the Physicality of Wi-Fi: A Subspace Approach

et al. 2019

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Wi-Fi channel state information (CSI) has emerged as a plausible modality for sensing different human activities as a function of modulations in the wireless signal that travels between wireless devices. Until now, most research has taken a statistical approach and/or purpose-built inference pipeline. Although interesting, these approaches struggle to sustain sensing performances beyond experimental conditions. As such, the full potential of CSI as a general-purpose sensing modality is yet to be realised. We argue a universal approach with well-grounded formalisation is necessary to characterise the relationship between wireless channel modulations (spatial and temporal) and human movement. To this end, we present a formalism for quantifying the changing part of the wireless signal modulated by human motion. Grounded in this formalisation, we then present a new subspace tracking technique to describe the channel statistics in an interpretable way, which succinctly contains the human modulated part of the channel. We characterise the signal and noise subspaces for the case of uncontrolled human movement, and show that these subspaces are dynamic. Our results demonstrate that proposed channel statistics alone can robustly reproduce state-of-the-art application-specific feature engineering baseline, however, across multiple usage scenarios. We expect, our universal channel statistics will yield an effective general-purpose featurisation of wireless channel measurements and will uncover opportunities for applying CSI for a variety of human sensing applications in a robust way.Index Terms-Channel sensing, interpretable dimensionality reduction, machine learning, multiple-input multiple-output (MIMO).

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Section: B Differential Subspace Evolutionmentioning

confidence: 99%

On Tracking the Physicality of Wi-Fi: A Subspace Approach

et al. 2019

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“…Tsinghua University (THU) channel sounder [20] was used to collect raw measured data. During the measurement campaigns, it worked at 2.4 GHz central frequency with 40 MHz bandwidth.…”

Section: Channel Measurementsmentioning

confidence: 99%

Measurement-Based Delay and Doppler Characterizations for High-Speed Railway Hilly Scenario

Zhang

et al. 2014

International Journal of Antennas and Propagation

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This paper presents results for delay and Doppler spread characterization in high-speed railway (HSR) hilly scenario. To investigate the propagation characteristics in this specific terrain, a measurement campaign is conducted along the "Guangzhou-Shenzhen" HSR in China. A wideband channel sounder with 40 MHz bandwidth is used to collect raw data at 2.4 GHz band. The delay spread and Doppler frequency features are analyzed based on measured data. It is found that there are abundant multipath components (MPCs) in this scenario. We present the relationship between the delay spreads and the transceiver distances. The measured route can be divided into four areas with different delay and Doppler characteristics. Finally, a tapped delay line (TDL) model is proposed to parameterize the channel responses in the HSR hilly environment, which is supposed to provide criterions for evaluations of the radio interface and development of wireless communication system.

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“…MIMO channel sounder [12,13] was used to collect raw measured data, which supported both centralized and distributed MIMO channel tests. It worked at the 3.52 GHz central frequency with 40 MHz bandwidth.…”

Section: Thu Channel Sounder Tsinghua University (Thu)mentioning

confidence: 99%

“…In postprocessing, CIR samples at this region are considered as spatial realizations. The large scale parameter can be viewed as constant in this small region [13]. Consequently, only the small scale correlations among distributed Tx antennas are involved.…”

Section: Transmitting Spatial Correlationmentioning

confidence: 99%

Measurement-Based Spatial Correlation and Capacity of Indoor Distributed MIMO System

Zhang

Xiao

Zhou

et al. 2013

International Journal of Antennas and Propagation

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Distributed MIMO (D-MIMO) system is one of the candidates for future wireless access networks. In this study, the spatial correlation and capacity in indoor D-MIMO system are presented. All results are from the actual channel measurements in typical indoor scenarios, including office and corridor. Based on measured data, spatial correlation coefficients between distributed transmitting antennas are analyzed. Although the literature about D-MIMO system assumes the small scale fading between distributed antennas is independent, we find that spatial correlation may still exist in specific propagation scenario. This correlation can also degrade the performance of D-MIMO system. To mitigate the impact of spatial correlation, one efficient method is to use transmitting antenna selection technique.

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A General Coupling-Based Model Framework for Wideband MIMO Channels

Cited by 16 publications

References 21 publications

On Tracking the Physicality of Wi-Fi: A Subspace Approach

On Tracking the Physicality of Wi-Fi: A Subspace Approach

Measurement-Based Delay and Doppler Characterizations for High-Speed Railway Hilly Scenario

Measurement-Based Spatial Correlation and Capacity of Indoor Distributed MIMO System

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