A 2D ray-tracing based model for wave propagation through forests at micro-and millimeter wave frequencies

This paper proposes the extension of a 2-D ray-tracing-based model for radiowave propagation in the presence of trees and vegetation areas to include real-sized trees and outdoor forest scenarios. The original propagation model proved to be suitable to characterize the electromagnetic behavior in the presence of indoor tree formation scenarios, despite some limitations found when applied to real-sized trees. In addition, the original propagation model requires the prior knowledge of the trees’ re-radiation function to extract the relevant propagation input parameters, which is not always possible to obtain in outdoor scenarios. Therefore, an empirical method to extract the relevant input propagation parameters based on simple measurements is proposed. The performance of the proposed propagation model extension is extensively assessed in both the line-of-trees and tree formation scenarios, including various (and mixed) species, both in- and out-of-leaf foliation states, and at three signal frequencies. Finally, depending on the type of scenario, a benchmark between the proposed propagation model and both the radiative energy transfer (RET) and discrete RET (dRET) models, for line-of-trees and tree formation, respectively, is presented.info:eu-repo/semantics/publishedVersio

Wireless Channel Path-Loss Modelling for Agricultural and Vegetation Environments: A Survey

This work undertakes an extensive survey of the channel modelling methods and path-loss characterization carried out in agricultural fields and vegetation environments in an attempt to study the state-of-the-art in this field, which, though vastly explored, still presents extremely diverse opportunities and challenges. The interface for communication between nodes in a typical agricultural field is the wireless channel or air interface, making it imperative to address the impairments that are exclusive to such a communication scenario by studying the characteristics of the medium. The performance of the channel is a direct indicator of the quality of communication. It is required to have a lucid understanding of the channel to ensure quality in transmission of the required information, while simultaneously ensuring maximum capacity by employing limited resources. The impairments that are the very nature of a typical wireless channel are treated in an explicit manner covering the theoretical and mathematical models, analytical aspects and empirical models. Although there are several propagation models characterized for generic indoor and outdoor environments, these cannot be applied to agricultural, vegetation, forest and foliage scenarios due to the various additional factors that are specific to these environments. Owing to the wide variety, size, properties and span of the foliage, it also becomes extremely challenging to develop a generic predictive model for all kinds of crops or vegetation. The survey is categorized into fields containing specific crops, greenhouse environment and forest/foliage scenarios and the key findings are presented

Propagation studies at 5.8 GHZ within vegetated environment for point-to-multipoint applications

This thesis presents an empirical study for fixed wireless links based on IEEE802.16 standard in vegetated residential environment. Simulation and field measurements were conducted for suburban microcell channel by utilising 5.8 GHz of Unlicensed National Information Infrastructure (UNII). A set of comprehensive measurement that covered 13 point-to-multipoint links surrounding Universiti Teknologi Malaysia were selected to investigate the impact of vegetation on propagating radio waves. The aim of this study is to develop a path loss model that incorporates vegetation effect. Received Signal Strength (RSS), Signal-to-Noise Ratio (SNR) and factors influencing performance of the signal strength are highlighted here. Performance of RSS during daytime and night is also evaluated. The accuracy of proposed prediction model is analysed which quantifies that path loss is proportional to the distance of tree to the receiver, size, density and number of trees within the vicinity of transmitting and receiving antennas. Observation found that terrain and external effect, such as wind will significantly affect the signal performance too. Depending on the dynamic characteristics of trees presence between the communication links, the measurement results show that the path loss is increased from 5.69 dB to 33.67 dB. The results obtained are compared to Free Space Loss model, Weissberger model, and ITU-R model. Those established models are used to validate the applicability result obtained by means of Root Mean Square Error (RMSE). In view of this research work, a good agreement of the proposed excess loss model achieves the smallest RMSE for links obstructed by a single tree, row of trees, row of trees and road as well as row of trees, road and building

Fusion-based impairment modelling for an intelligent radar sensor architecture

An intelligent radar sensor concept has been developed using a modelling approach for prediction of sensor performance, based on application of sensor and environment models. Land clutter significantly impacts on the operation of radar sensors operating at low-grazing angles. The clutter modelling technique developed in this thesis for the prediction of land clutter forms the clutter model for the intelligent radar sensor. Fusion of remote sensing data is integral to the clutter modelling approach and is addressed by considering fusion of radar remote sensing data, and mitigation of speckle noise and data transmission impairments. The advantages of the intelligent sensor approach for predicting radar performance are demonstrated for several applications using measured data. The problem of predicting site-specific land radar performance is an important task which is complicated by the peculiarities and characteristics of the radar sensor, electromagnetic wave propagation, and the environment in which the radar is deployed. Airborne remote sensing data can provide information about the environment and terrain, which can be used to more accurately predict land radar performance. This thesis investigates how fusion of remote sensing data can be used in conjunction with a sensor modelling approach to enable site-specific prediction of land radar performance. The application of a radar sensor model and a priori information about the environment, gives rise to the notion of an intelligent radar sensor which can adapt to dynamically changing environments through intelligent processing of this a priori knowledge. This thesis advances the field of intelligent radar sensor design, through an approach based on fusion of a priori knowledge provided by remote sensing data, and application of a modelling approach to enable prediction of radar sensor performance. Original contributions are made in the areas of intelligent radar sensor development, improved estimation of land surface clutter intensity for site-specific low-grazing angle radar, and fusion and mitigation of sensor and data transmission impairments in radar remote sensing data.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Packet Loss in Terrestrial Wireless and Hybrid Networks

The presence of both a geostationary satellite link and a terrestrial local wireless link on the same path of a given network connection is becoming increasingly common, thanks to the popularity of the IEEE 802.11 protocol. The most common situation where a hybrid network comes into play is having a Wi-Fi link at the network edge and the satellite link somewhere in the network core. Example of scenarios where this can happen are ships or airplanes where Internet connection on board is provided through a Wi-Fi access point and a satellite link with a geostationary satellite; a small office located in remote or isolated area without cabled Internet access; a rescue team using a mobile ad hoc Wi-Fi network connected to the Internet or to a command centre through a mobile gateway using a satellite link. The serialisation of terrestrial and satellite wireless links is problematic from the point of view of a number of applications, be they based on video streaming, interactive audio or TCP. The reason is the combination of high latency, caused by the geostationary satellite link, and frequent, correlated packet losses caused by the local wireless terrestrial link. In fact, GEO satellites are placed in equatorial orbit at 36,000 km altitude, which takes the radio signal about 250 ms to travel up and down. Satellite systems exhibit low packet loss most of the time, with typical project constraints of 10−8 bit error rate 99% of the time, which translates into a packet error rate of 10−4, except for a few days a year. Wi-Fi links, on the other hand, have quite different characteristics. While the delay introduced by the MAC level is in the order of the milliseconds, and is consequently too small to affect most applications, its packet loss characteristics are generally far from negligible. In fact, multipath fading, interference and collisions affect most environments, causing correlated packet losses: this means that often more than one packet at a time is lost for a single fading even

Fusion-based impairment modelling for an intelligent radar sensor architecture

An intelligent radar sensor concept has been developed using a modelling approach for prediction of sensor performance, based on application of sensor and environment models. Land clutter significantly impacts on the operation of radar sensors operating at low-grazing angles. The clutter modelling technique developed in this thesis for the prediction of land clutter forms the clutter model for the intelligent radar sensor. Fusion of remote sensing data is integral to the clutter modelling approach and is addressed by considering fusion of radar remote sensing data, and mitigation of speckle noise and data transmission impairments. The advantages of the intelligent sensor approach for predicting radar performance are demonstrated for several applications using measured data. The problem of predicting site-specific land radar performance is an important task which is complicated by the peculiarities and characteristics of the radar sensor, electromagnetic wave propagation, and the environment in which the radar is deployed. Airborne remote sensing data can provide information about the environment and terrain, which can be used to more accurately predict land radar performance. This thesis investigates how fusion of remote sensing data can be used in conjunction with a sensor modelling approach to enable site-specific prediction of land radar performance. The application of a radar sensor model and a priori information about the environment, gives rise to the notion of an intelligent radar sensor which can adapt to dynamically changing environments through intelligent processing of this a priori knowledge. This thesis advances the field of intelligent radar sensor design, through an approach based on fusion of a priori knowledge provided by remote sensing data, and application of a modelling approach to enable prediction of radar sensor performance. Original contributions are made in the areas of intelligent radar sensor development, improved estimation of land surface clutter intensity for site-specific low-grazing angle radar, and fusion and mitigation of sensor and data transmission impairments in radar remote sensing data