Modelling and coverage improvement of DVB-T networks

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe necessity of accurate point-to-area and point-to-point prediction tools arises from the enormous demand in designing broadcasting systems for digital TV and cellular communications. Up to now, a considerable number of coverage prediction models for radio coverage has been developed. In electromagnetic wave propagation theory, there are three types of propagation models. Empirical models that are based on a large quantity of measurement data are elementary but not very accurate. Semi-deterministic models that are based on measurement data and electromagnetic theory of propagation, which are more precise. Finally, deterministic models based on theoretical physics, like diffraction theory and Fresnel theory, that require a significant amount of geometrical data about the propagation terrain profile but are the most accurate. The primary outcomes of this research are the comparative study and improvement of several propagation models, using a significant quantity of measurements and simulations and the deduction of useful conclusions to be used by engineers to improve propagation predictions further. In this research, the Longley-Rice (ITM) Irregular Terrain Model model was used, a classic model used for TV coverage prediction, which model is to date the preferred model of the FCC (Federal Communications Commission) in the US for FM-TV coverage calculations. To run the model, the Radio Mobile program (Radio Propagation and Virtual Mapping Freeware) was used based on the Longley-Rice Model ITM, including the 3-arc-second Satellite Radar Terrain Mission (SRTM) maps and the SPLAT! program (an RF Signal Propagation, Loss, And Terrain analysis tool), which also relies on the Longley-Rice ITM model and makes use of SRTM maps. Both programs work in Windows operating system (Windows7 Professional, 64 bits). Another model used in this research was SPLAT! with ITWOM (Irregular Terrain with Obstructions Model) which combines empirical data from the ITU-R P.1546 model and other ITU recommendations in conjunction with Beer's and Snell's laws. The ITU-R Recommendation P.1546 model and the empirical Hata-Davidson model using HAAT were also utilized in this research. The Single Knife-Edge (SKE) model was coded in MATLAB and utilized in this research as a simple reference model, where only one main obstacle is considered. Other well-known multiple knife-edge diffraction models employed in this study are the Epstein-Peterson, Deygout, and Giovaneli models. For these deterministic models, individual MATLAB programs were written. Simulations produced by the models were limited to the main two knife-edges of the propagation path for immediate comparison with the Longley-Rice model which uses the “double knife-edge” approach. All measurement campaigns took place in Northern Greece and Southern (F.Y.R.O.M) Former Yugoslav Republic of Macedonia using a Rohde & Schwarz FSH-3 portable spectrum analyser and precision calibrated antennas

Evaluation of prediction accuracy for the Longley-Rice model in the FM and TV bands

Accurate geographical coverage predictions maps for FM and TV are needed for channel and frequency allocations and in order to avoid unwanted interferences. The Longley-Rice model has been used for this purpose over the last four decades and still being used almost exclusively by the FCC in the United States. In this work a comparison is presented between the relative accuracy of this model in the VHF-FM and UHF-TV frequency bands. Simulations were made with accurate and up to date input data (antenna height, location, gain, transmit power, etc.) for the FM-TV stations provided by the ERT S.A. public broadcaster in the region of Thessaloniki – Greece. Finally, the calculated – simulated results were confronted to field measurements using a Rohde & Schwarz FSH3 portable spectrum analyzer and high precision calibrated biconical and log-periodic antennas, and the errors between predictions and measurements were statistically analyzed in the two frequency bands. It has been found in this study that the Longley-Rice model, in general, overestimates field-strength values, but this overestimation is much higher in the VHF – FM radio band (88-108 MHz) than in the UHF-TV band (470-790 MHz)

Comparative study of Radio Mobile and ICS Telecom propagation prediction models for DVB-T

In this paper, a comparative study between the results of a measurement campaign conducted in northern Greece and simulations performed with Radio Mobile and ICS Telecom radio planning tools is performed. The DVB-T coverage of a transmitting station located near the city of Thessaloniki is estimated using three empirical propagation models (NTIA-ITS Longley Rice, ITU-R P.1546 and Okumura-Hata-Davidson) and one deterministic model (ITU-R 525/526). The best results in terms of minimum average error and standard deviation are obtained using the deterministic model and the NTIA-ITS Longley Rice empirical model. In order to improve the results, the tuning options available in the ICS Telecom software are used on the Okumura-Hata-Davidson model, leading to a significant increase in accuracy

RURAL BROADBAND MOBILE COMMUNICATIONS: SPECTRUM OCCUPANCY AND PROPAGATION MODELING IN WESTERN MONTANA

Fixed and mobile spectrum monitoring stations were implemented to study the spectrum range from 174 to 1000 MHz in rural and remote locations within the mountains of western Montana, USA. The measurements show that the majority of this spectrum range is underused and suitable for spectrum sharing. This work identifies available channels of 5-MHz bandwidth to test a remote mobile broadband network. Both TV broadcast stations and a cellular base station were modelled to test signal propagation and interference scenarios

A Platform for Large-Scale Regional IoT Networks

The Internet of Things (IoT) promises to allow everyday objects to connect to the Internet and interact with users and other machines ubiquitously. Central to this vision is a pervasive wireless communication network connecting each end device. For individual IoT applications it is costly to deploy a dedicated network or connect to an existing cellular network, especially as these applications do not fully utilize the bandwidth provided by modern high speeds networks (e.g., WiFi, 4G LTE). On the other hand, decades of wireless research have produced numerous low-cost chip radios and effective networking stacks designed for short-range communication in the Industrial, Scientific and Medical Radio band (ISM band). In this thesis, we consider adapting this existing technology to construct shared regional low-powered networks using commercially available ISM band transceivers. To maximize network coverage, we focus on low-power wide-area wireless communication which enables links to reliably cover 10 km or more depending on terrain transmitting up to 1 Watt Equivalent Isotropically Radiated Power (EIRP). With potentially thousands of energy constrained IoT devices vying for extremely limited bandwidth, minimizing network coordination overhead and maximizing channel utility is essential. To address these challenges, we propose a distributed queueing (DQ) based MAC protocol, DQ-N. DQ-N exhibits excellent performance, supporting thousands of IoT devices from a single base station. In the future, these networks could accommodate a heterogeneous set of IoT applications, simplifying the IoT application development cycle, reducing total system cost, improving application reliability, and greatly enhancing the user experience

Weather-Based Nonlinear Regressions for Digital TV Received Signal Strength Prediction

In this research, the impact of various weather conditions on digital television signals is investigated. Machine learning and nonlinear regression models were used to estimate the strength of the received signal. The received signal strength might vary significantly depending on the weather condition, especially in higher frequency ranges or millimetre wavelengths. Predictive analysis was performed for the radio-relay link Aval Tower-Vršac Hill, which is used for the distribution of television and radio programmes by the public company Broadcasting Technology and Connections in Serbia. The prediction was made using temperature, temperature index, relative humidity, and received signal strength data for the months of June, July, and August in 2022. The best results were obtained using the RandomForest model. Extreme variations in the strength of the received signal can be predicted by using the model mentioned above. More effective management of the broadcasting infrastructure can be done with the ability to predict sudden falls and fluctuations in received signal strength

ending civil conflict through rebel demobilization

We examine the role of FM radio in mitigating violent conflict. We collect original data on radio broadcasts encouraging defections during the Lord's Resistance Army (LRA) insurgency. This constitutes the first quantitative evaluation of an active counterinsurgency policy that encourages defections through radio messages. Exploiting random topography-driven variation in radio coverage along with panel variation at the grid-cell level, we identify the causal effect of messaging on violence. Broadcasting defection messages increases defections and reduces fatalities, violence against civilians, and clashes with security forces. Income shocks have opposing effects on both the conflict and the effectiveness of messaging.publishersversionpublishe

Propaganda and Conflict: Evidence from the Rwandan Genocide

This paper investigates the role of mass media in times of conflict and state-sponsored mass violence against civilians. We use a unique village-level dataset from the Rwandan Genocide to estimate the impact of a popular radio station that encouraged violence against the Tutsi minority population. The results show that the broadcasts had a significant impact on participation in killings by both militia groups and ordinary civilians. An estimated 51,000 perpetrators, or approximately 10 percent of the overall violence, can be attributed to the station. The broadcasts increased militia violence not only directly by influencing behavior in villages with radio reception, but also indirectly by increasing participation in neighboring villages. In fact, spillovers are estimated to have caused more militia violence than the direct effects. Thus, the paper provides evidence that mass media can affect participation in violence directly due to exposure, and indirectly due to social interactions

Estudio para la planificación de redes de difusión según el estándar ATSC 3.0

Abstract: In this BsC final degree project, different configuration and network architecture settings for the standard ATSC 3.0 are studied. The work analyzes bitrate requirements, associated ATSC 3.0 modes and several network architecture options. Both calculations and minimum requirements of SNR have been analyzed and simulations in selected environments have been carried out. The field strength distribution of each transmitter have been obtained using SPLAT!. Afterwards, to estimate the coverage probability for each service, a toolbox coded on Python has been applied. By means of these simulations, some implementation guidelines for deploying ATSC 3.0 services are given for each selected scenario.Resumen: En este Trabajo de Fin de Grado (TFG) se estudiarán las posibles configuraciones del sistema y arquitectura de red para el estándar de ATSC 3.0. Se analizarán los requisitos de bitrate para la emisión de cada servicio (UHD, HD,…) además de las posibles planificaciones de redes. Una vez realizados los cálculos y obtenidos los valores de SNR mínimo necesarios, se empezará con las simulaciones en los diferentes entornos seleccionados. En primer lugar, se usará SPLAT! para obtener los valores de campo eléctrico de cada transmisor. Posteriormente, usando una herramienta codificada en Python, se obtendrán las estimaciones de cobertura para cada servicio. Mediante estas simulaciones se ofrecerán unas recomendaciones para la implantación del sistema ATSC 3.0 en los escenarios seleccionados.Laburpena: Gradu Amaierako Lan (GrAL) honetan, ATSC 3.0 estandarrak barruan har ditzakeen konfigurazio ezberdinak eta sare arkitektura aztertzen dira. Igorri ahalko diren zerbitzurentzako (UHD, HD, …) bitrate betekizunak eta sare-plangintza ezberdinak ikertuko dira. Behin eragiketak eta beharrezko SNR minimoak lortuta, hautatutako ingurune bakoitzerako simulazioekin hasiko da. Lehenengo eta behin, transmisore bakoitzak igorritako eremu elektrikoaren balioak lortzeko, SPLAT! softwarea erabiliko da. Ondoren, zerbitzu bakoitzerako estaldura zenbatespenak lortuko dira Pythonen kodetutako erreminta baten bidez. Simulazio hauen bitartez, ATSC 3.0 sistemaren ezarpenerako hainbat gomendio eskainiko dira

Adaptive averaging channel estimation for DVB-T2 systems

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIn modern communication systems, the rate of transmitted data is growing rapidly. This leads to the need for more sophisticated methods and techniques of implementation in every block of the transmitter-receiver chain. The weakest link in radio communications is the transmission channel. The signal, which is passed through it, suffers from many degrading factors like noise, attenuation, diffraction, scattering etc. In the receiver side, the modulated signal has to be restored to its initial state in order to extract the useful information. Assuming that the channel acts like a filter with finite impulse, one has to know its coefficients in order to apply the inverse function, which will restore the signal back to its initial state. The techniques which deal with this problem are called channel estimation. Noise is one of the causes that degrade the quality of the received signal. If it could be discarded, then the process of channel estimation would be easier. Transmitting special symbols, called pilots with known amplitude, phase and position to the receiver and assuming that the noise has zero mean, an averaging process could reduce the noise impact to the pilot amplitudes and thus simplify the channel estimation process. In this thesis, a novel channel estimation method based on noise rejection is introduced. The estimator takes into account the time variations of the channel and adapts its buffer size in order to achieve the best performance. Many configurations of the estimator were tested and at the beginning of the research fixed size estimators were tested. The fixed estimator has a very good performance for channels which could be considered as stationary in the time domain, like Additive White Gaussian Noise (AWGN) channels or slowly time-varying channels. AWGN channel is a channel model where the only distorting factor is the noise, where noise is every unwanted signal interfering with the useful signal. The properties of the noise are that it is additive, which means that the noise is superimposed on the transmitted signal, it is white so the power density is constant for all frequencies, and it has a Gaussian distribution in the time domain with zero mean and variance σ2=N. A slowly time varying channel refers to channel with coherence time larger than the transmitted symbol duration. The performance of a fixed size averaging estimator in case of fast time-varying channels is subject to the buffering time. When the buffering time is smaller or equal to a portion of the coherence time the averaging process offers better performance than the conventional estimation, but when the buffering time exceeds this portion of the coherence time the performance of the averaging process degrades fast. So, an extension has been made to the averaging estimator that estimates the Doppler shift and thus the coherence time, where the channel could be assumed as stationary. The improved estimator called Adaptive Averaging Channel Estimator (AACE) is capable to adjust its buffer size and thus to average only successive Orthogonal Frequency Division Multiplexing (OFDM) symbols that have the same channel distortions. The OFDM is a transmission method where instead of transmitting the data stream using only on carrier, the stream is divided into parallel sub-streams where the subcarriers conveying the sub-streams are orthogonal to each other. The use of the OFDM increases the symbol duration making it more robust against Inter-Symbol Interference (ISI), which the interference among successive transmitted symbols, and also divides the channel bandwidth into small sub-bandwidths preventing frequency selectivity because of the multipath nature of the radio channel. Simulations using the Rayleigh channel model were performed and the results clearly demonstrate the benefits of the AACE in the channel estimation process. The performance of the combination of AACE with Least Square estimation (AACE-LS) is superior to the conventional Least Square estimation especially for low Doppler shifts and it is close to the Linear Minimum Mean Square Error (LMMSE) estimation performance. Consequently, if the receiver has low computational resources and/or the channel statistics are unknown, then the AACE-LS estimator is a valid choice for modern radio receivers. Moreover, the proposed adaptive averaging process could be used in any OFDM system based on pilot aided channel estimation. In order to verify the superiority of the AACE algorithm, quantitative results are provided in terms of BER vs SNR. It is demonstrated that AACE-LS is 7dB more sensitive than the LS estimator