Enabling wireless communication in aircraft using multipe antenna systems

Journal ArticleSensor technology is advancing to provide the robust, miniaturized sensors needed for aircraft prognostics health management (PHM). Aircraft maintainers would like to add numerous pressure, temperature, vibration, fuel quantity, moisture/chemical sensors, but a major challenge of retrofitting old aircraft with them is how to collect the data. Wireless data transfer in aircraft has been identified as a 'transformative' technology for aviation. The industry is pursuing wireless prospects, but so far all are limited by the extreme multipath channels in aircraft. Spread spectrum communication is extremely limited in aircraft because of the multipath channels[l], and [2] found problems with ultrawideband interfering with aircraft radios, even when operated at approved, 'safe' levels. This paper explores multiple input multiple output (MIMO) communication in aircraft because of its high capacity in rich multipath environments. In addition to the multipath that raises MIMO capacity, the aircraft channel is also rich in noise, interference, and channel correlation that decreases its capacity. This paper presents a complete channel model for MIMO in aircraft that includes the effects of noise, interference and channel correlation. The capacity obtained from this detailed system model is used as a metric for antenna selection and system evaluation

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

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

Measurement and modeling of multiuser multiantenna system in aircraft in the presence of electromagnetic noise and interference

ManuscriptThis paper evaluates the accuracy with which the performance of a multi-user multi-antenna system can be predicted with and without considering co-channel interference and noise (Gaussian, α- stable and Cauchy) using a site-specific 3D ray-tracing algorithm as well as with statistical models with Gaussian and Nakagami-m channel models in small to medium sized aircraft. These models expand on previous statistical channel models such as the hyper-Rayleigh model by including the simultaneous effects of co- and adjacent channel interference, antenna matching, efficiency, directivity and polarization as well as (for the 3D model) site-specific multipath effects. Measurements and comparisons are made in a metallic-bodied Beech Baron BE 58P and a composite structure Rockwell T-39 Sabreliner. It was found that the 3D ray tracing model provides a mean capacity within 1 % of those measured in the two aircraft in the presence of interference and noise. This was closely followed by the Nakagami-m distribution (m=1.4) which was within 1-3% of measured capacity in the presence of interference and within 6% for a combination of interference and noise and the Gaussian model which was within 6% of measured capacity in the presence of interference and within 11% for a combination of interference and noise . The Cauchy noise degraded the capacity more than the other types of noise in the aircraft, providing a lower bound for capacity in an aircraft system

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

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial

Channel Capacity Analysis of Distributed MIMO Systems in Cabin

采用自主搭建的信道测量平台测得了机舱环境下分布式MIMO系统的信道冲击响应矩阵。根据实测的信道矩阵分别计算了4种具有不同收发天线数目的分布式MIMO系统的信道容量。为了便于比较,SISO系统的信道容量也通过实测数据进行了计算。计算结果表明:在机舱环境下,采用分布式MIMO系统和采用SISO系统相比能够显著提高系统信道容量,说明分布式MIMO系统可以充分满足未来机舱内无线通信高速率数据传输的需求。With the self-built channel measurement platform,the channel matrix of in-cabin distributed MIMO system is measured.The channel capacity of 4 different distributed MIMO systems and also the channel capacity of one SISO system are calculated from the measured data.The calculation results show that as compared with one SISO system,the distributed MIMO system could significantly raise the capacity gain in the aircraft cabin environment,and thus could fully satisfy the requirements of high data-rate delivery for future in-cabin wireless communication.国家科技重大专项课题(No.2009ZX03002-002);国家重点基础研究发展规划项目资助(No.2007CB310608);国家863项目资助(No.2009AA011501);国家科技合作项目(No.2010DFB10410);清华-高通联合研究计划资助项目;长江学者和创新团队发展计划资助项目;中国博士后科学基

High-Throughput Air-to-Ground Connectivity for Aircraft

Permanent connectivity to the Internet has become the defacto standard in the second decade of the 21st century. However, on-board aircraft connectivity is still limited. While the number of airlines offering in-flight connectivity increases, the current performance is insufficient to satisfy several hundreds of passengers simultaneously. There are several options to connect aircraft to the ground, i.e. direct air-to-ground, satellites and relaying via air-to-air links. However, each single solution is insufficient. The direct air-to-ground coverage is limited to the continent and coastal regions, while the satellite links are limited in the minimum size of the spot beams and air-to-air links need to be combined with a link to the ground. Moreover, even if a direct air-to-ground or satellite link is available, the peak throughput offered on each link is rarely achieved, as the capacity needs to be shared with other aircraft flying in the same coverage area. The main challenge in achieving a high throughput per aircraft lies in the throughput allocation. All aircraft should receive a fair share of the available throughput. More specifically, as an aircraft contains a network itself, a weighted share according to the aircraft size should be provided. To address this problem, an integrated air-to-ground network, which is able to provide a high throughput to aircraft, is proposed here. Therefore, this work introduces a weighted-fair throughput allocation scheme to provide such a desired allocation. While various aspects of aircraft connectivity are studied in literature, this work is the first to address an integrated air-to-ground network to provide high-throughput connectivity to aircraft. This work models the problem of throughput allocation as a mixed integer linear program. Two throughput allocation schemes are proposed, a centralized optimal solution and a distributed heuristic solution. For the optimal solution, two different objectives are introduced, a max-min-based and a threshold-based objective. The optimal solution is utilized as a benchmark for the achievable throughput for small scenarios, while the heuristic solution offers a distributed approach and can process scenarios with a higher number of aircraft. Additionally, an option for weighted-fair throughput allocation is included. Hence, large aircraft obtain a larger share of the throughput than smaller ones. This leads to fair throughput allocation with respect to the size of the aircraft. To analyze the performance of throughput allocation in the air-to-ground network, this work introduces an air-to-ground network model. It models the network realistically, but independent from specific network implementations, such as 5G or WiFi. It is also adaptable to different scenarios. The aircraft network is studied based on captured flight traces. Extensive and representative parameter studies are conducted, including, among others, different link setups, geographic scenarios, aircraft capabilities, link distances and link capacities. The results show that the throughput can be distributed optimally during high-aircraft-density times using the optimal solution and close to optimal using the heuristic solution. The mean throughput during these times in the optimal reference scenario with low Earth orbit satellites is 20 Mbps via direct air-to-ground links and 4 Mbps via satellite links, which corresponds to 10.7% and 1.9% of the maximum link throughput, respectively. Nevertheless, during low-aircraft-density times, which are less challenging, the throughput can reach more than 200 Mbps. Therefore, the challenge is on providing a high throughput during high-aircraft-density times. In the larger central European scenario, using the heuristic scheme, a minimum of 22.9 Mbps, i.e. 3.2% of the maximum capacity, can be provided to all aircraft during high-aircraft-density times. Moreover, the critical parameters to obtain a high throughput are presented. For instance, this work shows that multi-hop air-to-air links are dispensable for aircraft within direct air-to-ground coverage. While the computation time of the optimal solution limits the number of aircraft in the scenario, larger scenarios can be studied using the heuristic scheme. The results using the weighted-fair throughput allocation show that the introduction of weights enables a user-fair throughput allocation instead of an aircraft-fair throughput allocation. As a conclusion, using the air-to-ground model and the two introduced throughput allocation schemes, the achievable weighted-fair throughput per aircraft and the respective link choices can be quantified