Rf field mapping inside a large passenger-aircraft cabin using a refined ray-tracing algorithm

Radio-frequency (RF) field mapping and its analysis inside a large passenger aircraft is a complex EM analysis problem, owing to its inherent concavity. The further hybrid surface modeling required for such concave enclosures leads to ray proliferation, thereby making the problem computationally intractable. In this paper, a large passenger-aircraft cabin is modeled as a single curved elliptical cylindrical cavity having a floorboard and windows. Unlike the available ray-tracing packages that use extensive numerical search methods, a quasi-analytical ray-propagation model is proposed here. This involves uniform ray launching, an intelligent scheme for ray bunching, and an adaptive reception algorithm to obtain the ray-path details inside the concave cabin. Although the image method yields precise point-to-point solutions, it cannot be used for curved concave environments. The developed method is therefore validated with respect to the RF field inside a cuboid. The RF field at the receiver within the cabin is determined using the ray-path descriptions and the constitutive EM parameters of the aircraft's cabin materials. The convergence analysis of the RF field buildup is carried out with respect to the propagation time and the number of bounces.

1. Introduction

Although wireless access is easily available in all public places around the world, this is still not true for air passengers during the flight. The deployment of wireless technology inside aircraft is an important issue, due to uncertainties related to interference. Radio-frequency (RF) field mapping and its analysis inside a large passenger-aircraft cabin is hence of immense interest. Aircraft manufacturers will benefit from this technology by exploiting wireless networks, leading to the reduction of cable complexity, and hence the weight of the aircraft. Moreover, new in-flight services, such as onboard service/meal selection, service requests, and video on demand, could be made available to all passengers.