Measurement-based characterization of LOS and NLOS drone-to-ground channels

Shi, Yan; Enami, Rita; Wensowitch, John; Camp, Joseph

doi:10.1109/wcnc.2018.8377104

Cited by 43 publications

(24 citation statements)

References 16 publications

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“…from (13), the ∇θ is related proportionally to the S and T. Also, it is inversely proportional to R. Figure 6. Air to ground scenario of the misalignment angle derivation…”

Section: Misalignment Angle Analysismentioning

confidence: 95%

“…Where R the range and r is the distance between the estimated and the current position. Therefore, it can be driven the ∇θ and S by (12)(13)(14).…”

Section: Misalignment Angle Analysismentioning

confidence: 99%

“…John C. Porcello, in 2013, builds a smart antenna for high bandwidth UAV communication based on Lagrange Interpolation using FPGA [12]. Yan Shi et al in 2018 used the Software Define Radio platform on UAVs to obtain air to ground wireless characteristics at different scenario and frequencies [13]. Lei Shi et al in 2013 used AA at the receiver side to detect the Angle of Arrival (AoA) to the target [14].…”

Section: Introductionmentioning

confidence: 99%

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Performance assessment of antenna array for an unmanned air vehicle

Ali

Al-Ja'afari

Abdulwahed

2020

IJECE

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In this paper, the performance of Linear Antenna Array Element (LAAE) has been evaluated at the Base Station (BS) with a different number of elements for Unmanned Air Vehicle UAV application. The Switched Beam (SB) and Phase Array (PA) have been used as a steering beam mechanism. The beam steering tracker is based on the GPS points of the UAV and the BS. In addition, the Misalignment angle has been analyzed for SB and PA corresponding to the maximum speed of the UAV. The compression between SB and PA in term of Bit Error Rate (BER) vs. Signal to Noise Ratio (SNR) and BER vs. Misalignment angle have been examined by using Matlab. The results show that the PA has better performance than SB in both terms under Additive White Gaussian Noise (AWGN) channel with an interference signal. When the number of the elements is eight provides longer distance than four by the factor (1.5 in SB case and 2 in PA case) and wider Misalignment angle range than twelve by factor (2 in SW case and 3 in PA case). Therefore, it is becoming a useful option for many applications.

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“…from (13), the ∇θ is related proportionally to the S and T. Also, it is inversely proportional to R. Figure 6. Air to ground scenario of the misalignment angle derivation…”

Section: Misalignment Angle Analysismentioning

confidence: 95%

“…Where R the range and r is the distance between the estimated and the current position. Therefore, it can be driven the ∇θ and S by (12)(13)(14).…”

Section: Misalignment Angle Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance assessment of antenna array for an unmanned air vehicle

Ali

Al-Ja'afari

Abdulwahed

2020

IJECE

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“…Recent studies in AG channel modeling mainly focus on low-frequency bands, such as the bands of IEEE 802.11a/g (2.4 GHz, 5.8 GHz), or L-band (1-2 GHz), C-band (4)(5)(6)(7)(8) which are recommended for UAV communications by International Telecommunication Union (ITU) [4]. However, the higher frequency bands, such as K u -band (12)(13)(14)(15)(16)(17)(18) and K-band (18-26.5 GHz) are rarely involved. It is well known that drones are also used in the middle layer of the space-airground integrated network (SAGIN), which needs to realize connections with ground terminals, as well as with satellites that generally work in the C-band, K u -band, K-band [5].…”

Section: Introductionmentioning

confidence: 99%

“…In our prior work, AG channel measurements are conducted in semiurban environments at L-band and C-band [9], [10], and the ray-tracing simulations are used to validate the multipath propagation [11]. Shi et al conducted measurements for drone-to-ground channels in the line-of-sight (LOS) and non-LOS (NLOS) cases at 900 MHz, 1800 MHz, and 5 GHz, in which log-distance path loss model was used to predict the fading behavior [12]. The four independent altitudes (0 m, 10 m, 20 m, and 30 m) of the UAV were used for comparing the characterizations of AG channel.…”

Section: Introductionmentioning

confidence: 99%

Multi-Frequency Air-to-Ground Channel Measurements and Analysis for UAV Communication Systems

et al. 2020

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In order to implement unmanned aerial vehicle (UAV)-based wireless communications, a better understanding of wireless channels and the corresponding channel characterizations are critical. In this paper, air-to-ground (AG) channel measurements are carried out at some candidate frequencies, i.e., 1 GHz, 4 GHz, 12 GHz, and 24 GHz. With measurement data, the crucial channel parameters are comprehensively analyzed. Firstly, based on the channel model in the 3rd Generation Partnership Project (3GPP), the essential coefficients for modeling path loss, including path loss exponents (PLEs) and heightdependent factors, are obtained for AG channels. Then, a novel autocorrelation model for shadow fading is proposed. Besides, the small-scale fading is statistically analyzed, where the log-logistic distribution is found as the best fit among popular distributions. Moreover, the second-order statistical characteristics, including the level crossing rate (LCR) and average fade duration (AFD), are extracted to describe indepth the fading behavior. Overall, the results and findings in this paper are essential for realizing reliable communications in AG wireless systems. INDEX TERMS Air-to-ground (AG) channel, characterizations, fading behavior, measurements, UAV.

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