Cognitive Radio and TV White Space (TVWS) Applications

As more user applications emerge for wireless devices, the corresponding amount of traffic is rapidly expanding, with the corollary that ever-greater spectrum capacity is required. Service providers are experiencing deployment blockages due to insufficient bandwidth being available to accommodate such devices. TV White Space (TVWS) represents an opportunity to supplement existing licensed spectrum by exploiting unlicensed resources. TVWS spectrum has materialised from the unused TV channels in the switchover from analogue to digital platforms. The main obstacles to TVWS adoption are reliable detection of primary users (PU) i.e., TV operators and consumers, allied with specifically, the hidden node problem. This chapter presents a new Generalised Enhanced Detection Algorithm (GEDA) that exploits the unique way Digital Terrestrial TV (DTT) channels are deployed in different geographical areas. GEDA effectively transforms an energy detector into a feature sensor to achieve significant improvements in detection probability of a DTT PU. Furthermore, by framing a novel margin strategy utilising a keep out contour, the hidden node issue is resolved, and a viable secondary user sensing solution formulated. Experimental results for a cognitive radio TVWS model have formalised both the bandwidth and throughput gains secured by TVWS users with this new paradigm

A survey of digital television broadcast transmission techniques

This paper is a survey of the transmission techniques used in digital television (TV) standards worldwide. With the increase in the demand for High-Definition (HD) TV, video-on-demand and mobile TV services, there was a real need for more bandwidth-efficient, flawless and crisp video quality, which motivated the migration from analogue to digital broadcasting. In this paper we present a brief history of the development of TV and then we survey the transmission technology used in different digital terrestrial, satellite, cable and mobile TV standards in different parts of the world. First, we present the Digital Video Broadcasting standards developed in Europe for terrestrial (DVB-T/T2), for satellite (DVB-S/S2), for cable (DVB-C) and for hand-held transmission (DVB-H). We then describe the Advanced Television System Committee standards developed in the USA both for terrestrial (ATSC) and for hand-held transmission (ATSC-M/H). We continue by describing the Integrated Services Digital Broadcasting standards developed in Japan for Terrestrial (ISDB-T) and Satellite (ISDB-S) transmission and then present the International System for Digital Television (ISDTV), which was developed in Brazil by adopteding the ISDB-T physical layer architecture. Following the ISDTV, we describe the Digital Terrestrial television Multimedia Broadcast (DTMB) standard developed in China. Finally, as a design example, we highlight the physical layer implementation of the DVB-T2 standar

IoT-based management platform for real-time spectrum and energy optimization of broadcasting networks

We investigate the feasibility of Internet of Things (IoT) technology to monitor and improve the energy efficiency and spectrum usage efficiency of broadcasting networks in the Ultra-High Frequency (UHF) band. Traditional broadcasting networks are designed with a fixed radiated power to guarantee a certain service availability. However, excessive fading margins often lead to inefficient spectrum usage, higher interference, and power consumption. We present an IoT-based management platform capable of dynamically adjusting the broadcasting network radiated power according to the current propagation conditions. We assess the performance and benchmark two IoT solutions (i.e., LoRa and NB-IoT). By means of the IoT management platform the broadcasting network with adaptive radiated power reduces the power consumption by 15% to 16.3% and increases the spectrum usage efficiency by 32% to 35% (depending on the IoT platform). The IoT feedback loop power consumption represents less than 2% of the system power consumption. In addition, white space spectrum availability for secondary wireless telecommunications services is increased by 34% during 90% of the time

The Specialist Committee on Detailed Flow Measurements. Final Report and Recommendations to the 26th ITTC

The scope of this report is to review up-todate measurement systems and methods available for flow-field and wave-field measurements and describe applications of Particle Image Velocimetry (PIV), stereoscopic PIV (SPIV), Laser Doppler Velocimetry (LDV),Particle Tracking Velocimetry (PTV),holography, and other emergent methods, for the measurements of flow separation, wake,vortex strength, etc, for ship hydrodynamics problems. Furthermore, practical issues related to the application of these measurement techniques, especially PIV and SPIV, in largescale tow tank facilities and cavitation tunnels will be discussed, with recommendations for future work for the ITTC in these areas

Coexistence of digital terrestrial television and next generation cellular networks in the 700 MHz band

"(c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."With the spectrum liberation obtained by the deployment of digital terrestrial television and the analog TV switch-off, new bands are being assigned to IMT LTE. In the first cellular deployments in the digital dividend at the 800 MHz band, problems emerged due to the interference cellular networks can cause to DTT signals. Possible solutions imply either an inefficient use of the spectrum (increasing the guard band and reducing the number of DTT channels) or a high cost (using anti-LTE filters for DTT receivers). The new spectrum allocated to mobile communications is the 700 MHz band, also known as the second digital dividend. In this new IMT band, the LTE uplink is placed in the lower part of the band. Hence, the ITU-R invited several studies to be performed and reported the results to WRC-15. In this article, we analyze the coexistence problem in the 700 MHz band and evaluate the interference of LTE signals to DTT services. Several coexistence scenarios have been considered, and laboratory tests have been performed to measure interference protection ratios.Fuentes, M.; García Pardo, C.; Garro Crevillen, E.; Gómez Barquero, D.; Cardona Marcet, N. (2014). Coexistence of digital terrestrial television and next generation cellular networks in the 700 MHz band. IEEE Wireless Communications. 21(6):63-69. doi:10.1109/MWC.2014.7000973S636921

A Linearized Free-Surface Method for Prediction of Unsteady Ship Maneuvering.

Maneuvering prediction tools are valuable resources for naval and commercial ship designers. They estimate the ability of a ship to maintain or alter course. This enables designers to characterize the maneuvering performance of multiple conceptual hull forms and select an optimal design. A novel maneuvering prediction method is presented in this thesis. It is an unsteady Reynolds-averaged Navier-Stokes (URANS) approach that includes wave effects with linear free-surface boundary conditions. Therefore, it is a single-phase approach to solving multiphase problems. The solution of the URANS equations captures the viscous effects that are highly important in maneuvering due to the complex fluid interactions between the hull, propellers, and rudders. The linearized free-surface approximation accounts for first-order wave effects while reducing the necessary extents of the computational domain and the level of grid refinement required by nonlinear computational fluid dynamics (CFD) solvers. These simplifications lead to a substantial improvement in computational efficiency with respect to nonlinear methods, while retaining accuracy and empowering naval architects to obtain results earlier in the design cycle.PhDNaval Architecture and Marine EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113426/1/mowoolli_1.pd

Interference Analysis Between Digital Terrestrial Television (DTT) and 4G LTE Mobile Networks in the Digital Dividend Bands

With the introduction of digital terrestrial television (DTT) and the analogue television switch-off, terrestrial broadcast spectrum in the UHF band is being released for mobile communications, in particular for fourth generation (4G) long term evolution (LTE) mobile services. This spectrum is known as digital dividend. An impending problem when deploying 4G LTE mobile networks in the digital dividend bands is that interferences may appear in the adjacent radio frequency channels used for DTT. In this paper, we analyze the adjacent coexistence of DTT and 4G LTE networks in the digital dividend bands at 700 MHz and 800 MHz. A generic framework is adopted such that results can be easily extrapolated to different scenarios and bands. Results are presented as a function of the guard band between technologies, for both LTE uplink and downlink adjacent to the DTT signals, and for fixed outdoor and portable indoor DTT reception. Also, the effect of using anti-LTE filters is studied.This work was supported by the Spectrum Regulator of Colombia ANE (Agencia Nacional del Espectro).Ribadeneira Ramírez, JA.; Martínez, G.; Gómez Barquero, D.; Cardona, N. (2016). Interference Analysis Between Digital Terrestrial Television (DTT) and 4G LTE Mobile Networks in the Digital Dividend Bands. IEEE Transactions on Broadcasting. 62(1):24-34. doi:10.1109/TBC.2015.2492465S243462

From MFN to SFN: Performance Prediction Through Machine Learning

In the last decade, the transition of digital terrestrial television (DTT) systems from multi-frequency networks (MFNs) to single-frequency networks (SFNs) has become a reality. SFN offers multiple advantages concerning MFN, such as more efficient management of the radioelectric spectrum, homogenizing the network parameters, and a potential SFN gain. However, the transition process can be cumbersome for operators due to the multiple measurement campaigns and required finetuning of the final SFN system to ensure the desired quality of service. To avoid time-consuming field measurements and reduce the costs associated with the SFN implementation, this paper aims to predict the performance of an SFN system from the legacy MFN and position data through machine learning (ML) algorithms. It is proposed a ML concatenated structure based on classification and regression to predict SFN electric-field strength, modulation error ratio, and gain. The model's training and test process are performed with a dataset from an SFN/MFN trial in Ghent, Belgium. Multiple algorithms have been tuned and compared to extract the data patterns and select the most accurate algorithms. The best performance to predict the SFN electric-field strength is obtained with a coefficient of determination (R2) of 0.93, modulation error ratio of 0.98, and SFN gain of 0.89 starting from MFN parameters and position data. The proposed method allows classifying the data points according to positive or negative SFN gain with an accuracy of 0.97

A Cognitive TV White Space Access Framework

Given the current boom in applications and services for mobile devices, data traffic is rapidly expanding, with the consequence that increasing spectrum capacity is being mandated. Following the switchover from analogue to digital platforms, Television White Space (TVWS) affords a fertile opportunity to supplement existing licensed spectrum to ease this scarcity. There are however, a number of obstacles to wide-scale TVWS adoption, including the accurate detection of primary users (PU), the hidden node problem and bandwidth availability for unlicensed secondary users (SU). Regulatory and industry bodies have sought to address some of these issues using a static database for spectrum access decisions, though this involves manual maintenance and accuracy can be compromised due to a lack of real-time information. While the new IEEE802.11af wireless local area network (WLAN) standard attempts to resolve some SU access issues, there remain many challenges, such as the critical asymmetry between mobile and base station power resources. This thesis presents a new cognitive TVWS access framework encompassing a real-time sensing paradigm for TVWS deployment that uses a spectrum-efficient scheme to uphold quality-of-service (QoS) for both PU and SU. A novel dynamic spectrum allocation (DSA) model has been formulated allied with a resilient interference management system which exploits the unique way digital terrestrial TV channels are allocated in different geographical areas. A margin strategy has been framed to support efficient TVWS channel reuse, with an exclusion zone established to overcome the hidden node problem, while an innovative routing algorithm using cross-layer information, both extends coverage capacity and maximises QoS provision by ensuring a more balanced resource allocation. Critical evaluation of the new access framework confirms that significant QoS improvements for SU are achieved compared to existing TVWS techniques. It importantly embodies a generic, practical, resource-efficient solution for TVWS deployment, which is compliant with current PU regulatory requirements

Cognitive radio for TVWS usage

Spectrum scarcity is an emerging issue in wireless communication systems due to the increasing demand of broadband services like mobile communications, wireless internet access, IoT applications, among others. The migration of analog TV to digital systems (a.k.a. digital TV switchover) has led to the release of a significant spectrum share that can be used to support said additional services. Likewise, TV white spaces emerge as spectral opportunities that can also be explored. Hence, cognitive radio (CR) presents itself as a feasible approach to efficiently use resources and exploit gaps within the spectrum. The goal of this paper is to unveil the state of the art revolving around the usage of TV white spaces, including some of the most important methods developed to exploit such spaces, upcoming opportunities, challenges for future research projects, and suggestions to improve current models