Abstract
Smart cities and smart buildings must provide their customers with many services, including those associated with health, productivity, and energy efficiency, among others. Short-range wireless systems can provide all of these services, but the significant growth of wireless networks operating within a smart building (SB) can produce the phenomenon of spectrum shortages. Spectrum shortages could be resolved using Cognitive Radio (CR)-based systems to improve the efficiency of electromagnetic spectrum use by taking advantage of the reusable spectrum available in the building’s interior. This study proposes a mechanism using two interference conditions to quickly estimate the minimum amount of effective spectrum availability (ESA) inside an SB. The results show that an SB contains ESA distributed across 36% to 98% of the building’s area for reuse, as a function of the height of the building and of the distance from the base station (BS) of the primary system.
Highlights
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].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]
The second condition, called Condition 2 (C2), allows the determination of the apartments from which an SR-CRWS would not cause interference to the Primary System (PS) receiver located on the rooftop of the building
The Multi-Wall Model (MWM) model considers a free space loss L f s between the PS receiver of the building and the SS, while the LC constant is a parameter that is used to compensate losses, which are usually negligible; LWi represents the losses in each internal wall, the number of walls of i type that cross the inner path is kWi, L f represents the slab loss, and k f represents the number of slabs that are traversed and is complemented by an empirical factor b
Summary
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]. 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]. Determining the ESA would have the benefit of allowing the operation of a private wireless service or system that could be planned in the interior of an SB without the need to use new spectrum bands Such interior systems could be SR_CRWS, such as cognitive wireless networks and cognitive wireless home networks, using any current technology (e.g., Wi-Fi, GSM, or LTE) [9]. Considering that, this article proposes a validated measuring mechanism that allows the estimation of the lower available amount of ESA inside an SB located in a smart city dense urban area with an appropriate inner deployment of incumbent users
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