Wireless Channel Simulator Testbed for Airborne Receivers

Blandino, Steve; Kaltenberger, Florian; Feilen, Michael

doi:10.1109/glocomw.2015.7413991

Cited by 10 publications

(9 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A similar study was conducted in [91], where BER was measured against SNR for an over sea AG propagation channel with distance measuring equipment (DME) co-channel interference present. In [92], BER versus SNR analysis was performed for different flight route phases for different values of Ricean K-factor. BER versus SNR analysis was performed in [46] for comparing the effect of presence and absence of ICI for an IEEE 802.11a OFDM system in the presence of additive white Gaussian noise (AWGN).…”

Section: E Measured Air Interface Statisticsmentioning

confidence: 99%

“…Apart from measurement campaigns for AG propagation channel modeling, some simulation based channel characterizations are also available in the literature, where the real time environmental scenarios are imitated using computer simulations. Simulations in urban/suburban areas were performed in [45], [85], [87], [92]. The antenna considered in these environments was omni-directional.…”

Section: F Simulations For Channel Characterizationmentioning

confidence: 99%

“…The depth of small scale amplitude fades on a given signal also generally varies inversely with signal bandwidth [114]. Stochastic fading models are obtained through analysis, empirical data, or through geometric analysis and simulations [25]- [27], [41], [84], [92]. As noted in subsection V-A, the GBSCMs can be subdivided into RS-GBSCM and IS-GBSCM.…”

Section: Small Scale Fading Modelsmentioning

confidence: 99%

See 2 more Smart Citations

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

Khawaja

Güvenç

Matolak

et al. 2019

IEEE Commun. Surv. Tutorials

550

206

View full text Add to dashboard Cite

In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios.

show abstract

Section: E Measured Air Interface Statisticsmentioning

confidence: 99%

Section: F Simulations For Channel Characterizationmentioning

confidence: 99%

Section: Small Scale Fading Modelsmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

Khawaja

Güvenç

Matolak

et al. 2019

IEEE Commun. Surv. Tutorials

550

206

View full text Add to dashboard Cite

show abstract

“…For instance, reference [97] proposed the TDL model to capture the small-scale characteristics of multipath components. Furthermore, the stochastic model accommodates multi-antenna system to boost the reliability of MIMO channel in terms of BER in [98] and capacity in [99]. In these works, the stochastic model only provides numerical analysis and lacks in validation by measurement results.…”

Section: B Stochastic Channel Modelmentioning

confidence: 99%

A Survey of Channel Modeling for UAV Communications

Khuwaja

Chen

Zhao

et al. 2018

IEEE Commun. Surv. Tutorials

689

346

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) have gained great interest for rapid deployment in both civil and military applications. UAV communication has its own distinctive channel characteristics compared with widely used cellular and satellite systems. Thus, accurate channel characterization is crucial for the performance optimization and design of efficient UAV communication systems. However, several challenges exist in UAV channel modeling. For example, propagation characteristics of UAV channels are still less explored for spatial and temporal variations in non-stationary channels. Also, airframe shadowing has not yet been investigated for small size rotary UAVs. This paper provides an extensive survey on the measurement campaigns launched for UAV channel modeling using low altitude platforms and discusses various channel characterization efforts. We also review the contemporary perspective of UAV channel modeling approaches and outline some future research challenges in this domain.

show abstract

“…That model considers scatterers uniformly distributed on space and results are based on parallel antenna arrays disposition between Tx and Rx which suggest that different antenna array configuration could not show the same communication link performance. In Blandino [33], a wideband multi-antenna extension of (GAGE) radio channel model is proposed for en-route and takeoff/arrival scenarios channel testbed for communication link. That work presupposes a uniform scatterer distribution in a two dimensional space to model the multipath contribution, neglecting the effect of the scatterer's height on the communication link.…”

Section: Introductionmentioning

confidence: 99%

A Three Dimensional MIMO Channel Model for Unmanned Aerial Vehicle in Urban Environments

Mendoza

Corral-Briones

2021

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

Increasing the availability of Unmanned Aerial Vehicles (UAV's) platforms leads to a variety of applications for aerial exploration, surveillance, and transport. Many of these applications rely on the communication between the UAV and the ground receiver which is subjected to high mobility that may lead to restrictions on link connectivity and throughput. In order to design high throughput and efficient communication schemes for these scenarios, a deep understanding of the communication channel behavior is required, especially taking into account measurement data from flight experiments. Channel propagation in urban environments involves diffraction effects which modify the Line-of-Sight (LoS) contribution of the total received signal, especially when the receiver is located on the ground. This process leads to scenarios where Multiple-Input Multiple-Output (MIMO) signal processing can take advantage from this situation. In this context, the goal of this paper is to study the diffraction effects of the LoS component through spatial correlation metrics of the signal. To accomplish this, we propose the use of a geometric stochastic technique to model the channel behavior which lies between High Altitude Platforms (HAP) and terrestrial link communications.

show abstract

Wireless Channel Simulator Testbed for Airborne Receivers

Cited by 10 publications

References 7 publications

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

A Survey of Channel Modeling for UAV Communications

A Three Dimensional MIMO Channel Model for Unmanned Aerial Vehicle in Urban Environments

Contact Info

Product

Resources

About