# Rapid Estimation of TVWS: A Probabilistic Approach Based on Sensed Signal Parameters
## 1 Introduction  
Smart sharing of the electromagnetic spectrum to exploit unused television channels or Television White Spaces (TVWS) is a relatively new and promising concept for wireless connectivity. TVWS are present in TV-UHF bands from channel 14 to channel 51, each of its channels having a bandwidth of 6 MHz, 7 MHz, or 8 MHz depending on the ITU region [1]. Information and Communication Technologies (ICT) have experienced remarkable development during the last years. According to this tendency, Internet of Things (IoT) devices and related applications are expected to use wireless technologies to transmit information. All these facts increase the demand on the electromagnetic spectrum for those purposes. It is well known that there are two types of spectrum bands in this setting, namely very crowded and underused bands. An example of an underused band is the TV-UHF, where we often can find idle channels in different time-periods and geographical zones. Smart sharing of the radio electrical spectrum appears as a viable solution to this apparent spectrum scarcity [2, 3]. As a practical solution to this problem, the use of Cognitive Radio (CR) has been proposed and complemented with different sensing techniques to detect TVWS. The goal in this scenario is to find idle channels to allow opportunistic usage by Secondary Users (SUs) without affecting Primary User (PU) broadcast, a process that is known as Dynamic Spectrum Access (DSA) [4]. The initiative of TVWS sharing with SU is gaining special interest due to the considerable existence of unused channels in TV bands, after it was demonstrated that not all channels are being used by a PU [5], which may be a realistic solution to the apparent spectrum scarcity. In this article, we propose a rapid method to process the statistical information of spectrum sensing, and based on it, the presence of TVWS is estimated in order to exploit them for wireless communications. By using a Mobile Spectrum Sensing Station (MSSS), information on the TV-UHF spectrum (500 MHz to 698 MHz) is collected and analyzed. This station is mounted on a vehicle, and it allowed for sensing of a wide area across the city of Windsor in Canada [6]. The MSSS uses two Radio Frequency Explorer (RFE) devices [7] connected in parallel to sense the noise of PU signal \(W(p)\) and of composite signal \(Xo(p)\), which has noise and \(PU\) signals combined. The rapid estimation method block diagram is shown in Figure 1. As observed, the first block collects all information related to \(W(p)\) and \(Xo(p)\) as well as Global Positioning System (GPS) information. In the second block, collected signals are analyzed in terms of energy detection, so that stochastic and mathematical information and Receiver Operation Characteristics (ROC) can be plotted. The third block receives this information, calculates auxiliary parameters, and applies the rapid method to estimate TVWS in the sensed spectrum. The importance of undertaking this research endeavour is the fact that CR and TVWS have huge potentials in many diverse wireless services and applications. Nowadays, the United States of America is the only country that has released a TVWS spectrum for cognitive access in rural areas. The Federal Communications Commission (FCC) regulates its operation by using a data-based method. This approach consists of remote access to a database to know the transmitters and their characteristics in terms of location, antenna, transmit power, height, operation times, and others in order to ensure that there is no interference with PUs [8]. This fact can be seen as a good indicator, in the sense that probably other countries will consider releasing a spectrum according to their local regulations and needs. The first application considered for TVWS was broadband access in sparsely populated areas by using cognitive radio techniques. With this purpose, the standard Institute of Electrical and Electronics Engineers 802.22 (IEEE 802.22) was approved in 2011 [9].