# Spectrum Demand Forecasting for IoT Services
###### Abstract  
The evolution of IoT has come with the challenge of connecting not only a massive number of devices, but also providing an always wider variety of services. In the next few years, a big increase in the number of connected devices is expected, together with an important increase in the amount of traffic generated. Never before have wireless communications permeated so deeply in all industries and economic sectors. Therefore, it is crucial to correctly forecast the spectrum needs, which bands should be used for which services, and the economic potential of its utilization. This paper proposes a methodology for spectrum forecasting consisting of two phases: a market study and a spectrum forecasting model. The market study determines the main drivers of the IoT industry for any country: services, technologies, frequency bands, and the number of devices that will require IoT connectivity. The forecasting model takes the market study as the input and calculates the spectrum demand in 5 steps: Defining scenarios for spectrum contention, calculating the offered traffic load, calculating a capacity for some QoS requirements, finding the spectrum required, and adjusting according to key spectral efficiency determinants. This methodology is applied for Colombia's IoT spectrum forecast. We provide a complete step-by-step implementation in fourteen independent spectrum contention scenarios, calculating offered traffic, required capacity, and spectrum for cellular licensed bands and non-cellular unlicensed bands in a 10-year period. Detailed results are presented specifying coverage area requirements per economic sector, frequency band, and service. The need for higher teledensity and higher spectral efficiency turns out to be a determining factor for spectrum savings. Internet of Things (IoT); Machine to Machine (M2M); radio spectrum; spectrum requirements; spectrum calculation; traffic prediction +
Footnote †: journal: _Future Internet_  
networks designed to deal with interference in shared (unlicensed) bands, while others will be carried by networks designed for high spectral efficiency in licensed bands. However, not all services require spectrum with the same coverage; they vary from body, personal, local, metropolitan to wide area networks (BAN, PAN, LAN, MAN, WAN). This implies that many services provided in very different locations (e.g., a hospital and an airport) may use the same band without interference. In the machine-to-machine (M2M) market, 72% of the devices use short-range unlicensed connections [8]. A huge market of digital services has already given birth to new technologies and networks. Their most prominent example is the Low-Power Wide Area Networks (LPWANs), working normally over unlicensed bands, providing connectivity to many things (generally sensors) at very low transmission rates. In the LPWAN sector, many spin-off companies have already presented networks with different PHY-MAC layer design (SIGFox, LoRa, Weighless, etc.) working mainly in the 800 and 900 MHz Industrial, Scientific and Medical (ISM) bands. Additionally, and for the first time, the 3 GPP has made cellular technology available to work on unlicensed spectrum (the so-called LTE-U version) creating yet another possibility for new services on many unlicensed bands. These networks will be supported by the reliability of 3 GPP's industrial muscle and the versatility of having a private network without depending on a telecommunications operator. On the other hand, 3 GPP standardization is working towards grabbing a share on this market, with standards such as EC-GSM-IoT, NB-IoT, or LTE-M, [9; 10; 11]. After completion of the first releases of the 5G standards (Rel. 15 and 16) where the main focus was the NR interface for eMBB and providing alternatives for easier 5G deployment using pre-existing 4G infrastructure (non-stand alone architecture); a final version of Release 17 has now been delayed for 2022, and Release 18 working items have started to emerge. In Rel.