Electromagnetic Propagation Prediction Inside Aircraft Cabins

Electromagnetic propagation models for signal strength prediction within aircraft cabins are essential for evaluating and designing a wireless communication system to be implemented onboard aircraft. There are many commercially available software packages for predicting wireless system performance in conventional indoor environments. It is of interest to examine the available software to determine if the aircraft\u27s electromagnetic environment (EME) can be modeled successfully without developing an aircraft specific prediction tool. EnterprisePlanner ®, a registered product of Wireless Valley Communications, Incorporated, was selected for the present effort. The performance of the prediction model was evaluated through a comparison with field measurements taken on the aircraft. It was concluded that the prediction model can accurately predict power propagation throughout the cabin. This prediction tool can enhance researchers\u27 understanding of power propagation within aircraft cabins and will aid in future research

Modeling electromagnetic interference generated by a WLAN system onboard commercial aircraft

This work forms part of the project HIRF SE which is financially supported under the European Union 7th Framework Programme (FP7). The authors are solely responsible for the contents of the paper which does not represent the opinion of the European Commission.The growing demand for the utilization of personal electronic communication devices onboard commercial aircraft necessitates the assurance of safety by airline operators and regulators. This implies that the potential risks posed by the deployment of wireless communication systems on critical aircraft equipment must be carefully assessed and countermeasures taken when required. In this paper, a model based on a ray-tracing algorithm is developed to calculate the electromagnetic interference incident on the fuselage structure of a commercial airline. The source of interference is a 2.4 GHz data communications network. Two scenarios are considered; the first assumes a base station in the centre of the cabin while the second considers four base stations, transmitting at a lower power, distributed along the cabin. The model first determines the propagation map generated by the base stations. These results are used to establish the transmission power required by the personal mobile devices which is then employed to determine the propagation map of each device. The overall electromagnetic interference map incident on the fuselage resulting from the onboard wireless network is generated by vectorially combining the resulting propagation maps. Results for the two scenarios are presented.peer-reviewe

Electromagnetic Interference to Flight Navigation and Communication Systems: New Strategies in the Age of Wireless

Electromagnetic interference (EMI) promises to be an ever-evolving concern for flight electronic systems. This paper introduces EMI and identifies its impact upon civil aviation radio systems. New wireless services, like mobile phones, text messaging, email, web browsing, radio frequency identification (RFID), and mobile audio/video services are now being introduced into passenger airplanes. FCC and FAA rules governing the use of mobile phones and other portable electronic devices (PEDs) on board airplanes are presented along with a perspective of how these rules are now being rewritten to better facilitate in-flight wireless services. This paper provides a comprehensive overview of NASA cooperative research with the FAA, RTCA, airlines and universities to obtain laboratory radiated emission data for numerous PED types, aircraft radio frequency (RF) coupling measurements, estimated aircraft radio interference thresholds, and direct-effects EMI testing. These elements are combined together to provide high-confidence answers regarding the EMI potential of new wireless products being used on passenger airplanes. This paper presents a vision for harmonizing new wireless services with aeronautical radio services by detecting, assessing, controlling and mitigating the effects of EMI

Doctor of Philosophy

dissertationWireless communication has become an essential part of everyday life. The hunger for more data, more phone calls, more video, and more access in more places, including vehicles, is growing massively. Communication in vehicles is particularly challenging because of their extremely high multipath environment. In addition, there is significant interest in reducing the number of wires in vehicles to reduce weight, complexity, maintenance, etc. and replace them with wireless systems. Preliminary research shows that MIMO systems take advantage of the extreme multipath environment found in aircraft and other vehicles and also provides more consistent channel capacity than SISO systems. The purpose of this research was to quantify complex channels (including the aircraft/vehicle environment) and their relation to other environments, evaluate MIMO in aircraft, provide design constraints for accurately modeling complex channels, and provide information to predict optimum antenna type and location to enable communication in aircraft/cars/buses/ships/trains/etc. and other extreme channels. The ability to evaluate and design MIMO technologies from the guidelines in this paper is potentially transformative for aircraft safety - enabling a new generation of location specific monitoring and maintenance. Average measured capacity was found to be between 18 and 21 bits/s/Hz using a 4x4 array of antennas, and had no direct relation to the size of the channel. Site-specific capacity showed a multipath rich channel, varying between 15 to 23 bits/s/Hz. The capacity decreased for increasing measurement distance, with exceptions near reflective objects that increase multipath. Due to these special circumstances for site-specific locations within complex channels, it is recommended that 3D ray tracing be used for modeling as it is more accurate than commonly used statistical models, within 1.1 bits/s/Hz. This showed that our 3D ray tracing is adaptable to various environments and gives a more accurate depiction than statistical models that average channel variations. This comes at the cost of greater model complexity. If increased complexity is not desirable, Nakagami 1.4 could be used as the next most accurate model. Design requirements for modeling different complex channels involve a detailed depiction of channel geometry, including height, width, length, shape (square, cylindrical, slanted walls, etc.), large windows, and reflective objects inside the channel space, especially those near the transmitter. Overall, the multipath rich channel found in vehicles is an excellent environment for MIMO systems. These complex channels can be simulated accurately without measurement and before they are even built using our sitespecific 3D ray tracing software combined with a detailed signal model to incorporate antenna effects

Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments

This paper presents a novel approach to improving wireless communications in harsh propagation environments to achieve higher overall reliability and durability of wireless battery powered sensor systems in the context of in-vehicle communication. The goal is to investigate the physical layer and establish an antenna recommendation system for a specific harsh environment, i.e., an engine compartment of a vehicle. We propose the usage of electromagnetic (EM) and ray tracing simulations as a computationally cost-effective method to establish such a recommendation system, which we test by means of an experimental testbed—or test environment—that consists of both a physical, as well as its identical simulation, model. A pool of antennas is evaluated to identify and verify antenna behavior and properties at specified positions in the harsh environment. We use a vector network analyzer (VNA) for accurate measurements and a received signal strength indicator (RSSI) for a first estimation of system performance. Our analysis of the experimental measurements and its EM simulation counterparts shows that both types of data lead to equivalent antenna recommendations at each of the defined positions and experimental conditions. This evaluation and verification process by measurements on an experimental testbed is important to validate the antenna recommendation process. Our results indicate that—with properly characterized antennas—such measurements can be substituted with EM simulations on an accurate EM model, which can contribute to dramatically speeding up the antenna positioning and selection process

Measurement-Based Analysis of Transmit Antenna Selection for In-Cabin Distributed MIMO System

Aircraft seems to be the last isolated island where the wireless access is still not available. In this paper, we consider the distributed multiple-input multiple-output (D-MIMO) system application based on measurements in aircraft cabin. The channel response matrices of in-cabin D-MIMO system are collected by using a wideband channel sounder. Channel capacities with optimum transmit antenna selections (TASs) are calculated from the measured data at different receiver positions. Then the optimum capacity results are compared to those without selection in different transmit SNR. It is shown that the TAS can lead obvious capacity gain, especially in the front and back of cabin. The capacity gain represents a decreasing trend with the transmit SNR increasing. The optimal transmit antenna subset is closely related to the transmit SNR. With the SNR increasing, more transmit antennas will be chosen for higher performance. The subset of those transmit antennas near the receiver is a reasonable choice in practical application of D-MIMO system