# Mechanism to Estimate Effective Spectrum Availability Inside Smart Buildings
## 1 Introduction  
The world's urban population has tended to increase at the expense of migration from rural areas [1], with the current urban population being approximately 55.7% of the world's population [2]. Furthermore, predictions say that by 2030, 60.4% of the world's population will be living in urban areas and will be concentrated in the most developed countries, where they will represent 81.4% of the population [3]. Therefore, large human concentrations will be present in megacities, which must be planned so that they can provide their services intelligently and efficiently. Usually, these services are based on the deployment of systems, mainly wireless systems (e.g., Internet-of-Things (IoT), 5G, and Wireless Sensor Networks (WSN)) [4], because these systems can connect mobile users at any time and any point inside a megacity. Therefore, the implementation of a smart city (SC) is necessary, requiring the cooperation of cities and city authorities, investors and funding agencies, researchers, and citizens [5]. In this context, SCs must be designed as megacity projects focused on a technologically structured perspective [6]. Because the demand for spaces and services is high, the construction of very tall buildings, such as so-called skyscrapers, is necessary. The technological development of those buildings includes the incorporation of intelligence (e.g., smart buildings (SBs)) so that they can provide services efficiently, considering horizontal and vertical integration models in the building inside [6]. For successful improvements in the services provided, building users prefer wireless communication technologies over wired networks. The building communication service providersprefer to use inner short-range systems (e.g., Internet-of-Things (IoT) technology), since they are straightforward to deploy while, at the same time, offering flexibility, portability, and scalability [7]. This means that inside SBs located in an SC, many short-range systems will be operating and providing mobile services to their users (e.g., Bluetooth, Wi-Fi, Long-Term Evolution (LTE)/ Global System for Mobile communications (GSM) femtocells, Wireless Sensor Networks (WSN), ZigBee, and Radio-Frequency Identification (RFID)) [8]. These futuristic scenarios are rapidly developing throughout the world. A forecast announced that by 2022, the increase in wireless connectivity would bring wireless traffic close to 84% of the total Internet traffic and the total amount of Internet traffic would be approximately 11 times the mobile traffic generated in 2017 [4]. As a result, there could be a high quantity of connected devices that increase wireless traffic. This could lead to interference, especially if they work in the same frequencies (e.g., the Industrial, Scientific and Medical (ISM) Band). There are at least two ways to avoid interference due to spectrum congestion; one of them is requiring new frequency bands, and the other is dynamically reusing the spectrum of any incumbent operator (i.e., Dynamic Spectrum Access (DSA)) to improve the current efficiency in the use of the spectrum [9]. This last method requires the spectrum to be managed on a DSA basis [10] instead of using the traditional Command and Control [11] model. The changing trend in spectrum management is based on some studies showing that the spectrum segments assigned to wireless telecommunication service operators have relatively low average use in both rural and urban areas [11; 12]. In other words, these studies have proved that there is spatial and temporary availability of the licensed spectrum, which could be used dynamically for the same or different services provided by the incumbent operators themselves or by a new operator [10].