Experimental Characterization and Correlation Analysis of Indoor Channels at 15 GHz

Zhou, Xin; Zhang, Zhong; Zhang, Bei; He, Ruisi; Guan, Ke; Wang, Qi; Matolak, David W.

doi:10.1155/2015/601835

Cited by 15 publications

(3 citation statements)

References 33 publications

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“…Afterwards, signals x [ n ] and y [ n ] are time‐aligned and truncated for the same length, as presented in Figure 3c. Next, the correlation coefficient between aligned signal values is evaluated [34]. In the particular example, the resulting correlation is about 0.74.…”

Section: Technical Detailsmentioning

confidence: 99%

Teaching wireless channel modeling with software‐defined radio

Bykhovsky

2020

Comp Applic In Engineering

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One of the important aspects in the study of wireless communication is channel modeling that is based on wave propagation theory and empirical measurements models. Most of the common undergraduate curricula address only theoretical aspects of wireless channels, while the related laboratory experiments concentrate on advanced digital modulation techniques and deal with topics such as pilot‐based channel estimation and equalization in orthogonal frequency division multiplexing modulation. In this paper, it is shown that some fundamental channel properties may be reproduced with laboratory experiments that require only a basic knowledge of communication principles, such as baseband and bandpass notation. These experiments can be carried out with affordable software‐defined radios, which have recently become extremely popular in the teaching of communication. Such experiments may enhance the teaching with hands‐on measurements of practical channels, while reinforcing the understanding of probability and random processes theory.

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Section: Technical Detailsmentioning

confidence: 99%

Teaching wireless channel modeling with software‐defined radio

Bykhovsky

2020

Comp Applic In Engineering

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“…For the large one, each piece is with 81 cones in a 9×9 array, the cone width is 6.8 cm, and the cone height is 17.8 cm. Measurements were conducted in the frequency domain by measuring the channel transfer function (CTF) over a frequency ranging from 4.9 GHz to 5.1 GHz, using the vector network analyzer-(VNA-) based measurement system as shown in Figure 1 [17]. We can get the empirical channel impulse responses (CIRs), ℎ( ), by performing an inverse fast Fourier transform algorithm (IFFT) of the measured CTF, ( ), as [17] ℎ ( ) = IFFT ( ( ))…”

Section: Impact On Rms Delay Spreadmentioning

confidence: 99%

Impacts of Absorber Loadings on Simulating the Multipath Channel in a Reverberation Chamber

Zhou

Zhang

Bian

et al. 2017

International Journal of Antennas and Propagation

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In reverberation chambers, the multipath channels with different delay characteristics can be generated by loading the chamber with different amounts of absorbers. This paper investigates the impacts of absorber loadings on the delay characteristics based on realistic measurements. An efficient method for estimating the root-mean-square (rms) delay spread in the chamber is presented. Furthermore, it is found that the chamber loadings also significantly affect the quality of a digitally modulated signal and the corresponding modulation quality measurements are performed.

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“…Accordingly, the system capability of the 5G cellular communication system will be enhanced. Consequently, the cellular devices functioned through the base station provided with an enhanced service setting with high-speed broadband transmission with low latency compared to the existing cellular communication systems [23]. Hence, the utilization of millimeter wave bands for the 5G cellular communication system will lead to innovative multimedia facilities.…”

Section: Introductionmentioning

confidence: 99%

Channel Characterization and Path Loss Modeling in Indoor Environment at 4.5, 28, and 38 GHz for 5G Cellular Networks

Majed

Rahman

Aziz

et al. 2018

International Journal of Antennas and Propagation

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The current propagation models used for frequency bands less than 6 GHz are not appropriate and cannot be applied for path loss modeling and channel characteristics for frequency bands above 6 GHz millimeter wave (mmWave) bands, due to the difference of signal propagation characteristics between existing frequency bands and mmWave frequency bands. Thus, extensive studies on channel characterization and path loss modeling are required to develop a general and appropriate channel model that can be suitable for a wide range of mmWave frequency bands in its modeling parameter. This paper presents a study of well-known channel models for an indoor environment on the 4.5, 28, and 38 GHz frequency bands. A new path loss model is proposed for the 28 GHz and 38 GHz frequency bands. Measurements for the indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios were taken every meter over a separation distance of 23 m between the TX and RX antenna locations to compare the well-known and the new large-scale generic path loss models. This measurement was conducted in a new wireless communication center WCC block P15a at Universiti Teknologi Malaysia UTM Johor, Malaysia, and the results were analyzed based on the well-known and proposed path loss models for single-frequency and multifrequency models and for directional and omnidirectional path loss models. Results show that the large-scale path loss over distance could be modeled better with good accuracy by using the simple proposed model with one parameter path loss exponent PLE (n) that is physically based to the transmitter power, rather than using the well-known models that have no physical base to the transmitted power, more complications (require more parameters), and lack of anticipation when explaining model parameters.The PLE values for the LOS scenario were 0.92, 0.90, and 1.07 for the V-V, V-H, and V-Omni antenna polarizations, respectively, at the 28 GHz frequency and were 2.30, 2.24, and 2.40 for the V-V, V-H, and V-Omni antenna polarizations, respectively, at the 38 GHz frequency.

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Experimental Characterization and Correlation Analysis of Indoor Channels at 15 GHz

Cited by 15 publications

References 33 publications

Teaching wireless channel modeling with software‐defined radio

Teaching wireless channel modeling with software‐defined radio

Impacts of Absorber Loadings on Simulating the Multipath Channel in a Reverberation Chamber

Channel Characterization and Path Loss Modeling in Indoor Environment at 4.5, 28, and 38 GHz for 5G Cellular Networks

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