# Dynamic Spectrum Access for Internet of Things Service in Cognitive Radio-Enabled LPWANs
## 2 Related Works
### Cognitive Radio for IoT  
Cognitive radio is a promising technology for IoT. It can help overcome the problems that will arise due to the deployment of several objects connected to infrastructure through radio links. However, there are several issues that need to be addressed before cognitive radio technology can be used for IoT. There have been several studies on cognitive radio for IoT.  
[PERSON] et al. [22] present a comprehensive definition for cognitive IoT (CIoT), which is primarily inspired by the effectiveness of human cognition, and propose an operational framework of CIoT, which mainly characterizes the interactions among five fundamental cognitive tasks: perception action cycle, massive data analytics, semantic derivation and knowledge discovery, intelligent decision-making, and on-demand service provisioning.  
[PERSON] et al. [23] discuss how cognitive radio technology can be helpful for the IoT paradigm. This study mainly mentions that the future would be a world of trillions of IoT objects in need of continuous spectrum functionalities. Hence, traditional communication technologies would not withstand this situation and so, transformation from ordinary IoT objects to cognitive-coupled IoT objects would be inevitable to benefit from spectrum congestion situations. Thus, this study highlights CR functionalities, especially spectrum sensing in conjunction with cloud services to serve as self-reconfigurable IoT solutions for a number of applications.  
[PERSON] et al. [24] survey novel approaches and recent advances on ongoing research directions related to cognitive radio in the context of Machine-to-Machine and Internet of Things. That is, this study reviews CR solutions that address generic problems of IoT including emerging challenges of autonomicity, scalability, energy efficiency, heterogeneity in terms of user equipment capabilities, complexity and environments, etc.  
[PERSON] et al. [25] propose the utilization of the Social Internet of Things (SIoT) paradigm, according to which objects are capable of establishing social relationships in an autonomous way, with respect to the rules set by their owners. The resulting social network enables faster and trustworthy  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **LoRa** & **SigFox** & **Wi-SUN** & **NB-IoT** & **LTE-M** \\ \hline Coverage & \(\sim\)11 km & \(\sim\)13 km & \(\sim\)5 km & \(\sim\)15 km & \(\sim\)11 km \\ Spectrum & 800–900 MHz & 800–900 MHz & 900 MHz & 700–900 MHz & 700–900 MHz \\ Band & ISM/unlicensed & ISM/unlicensed & ISM/unlicensed & Cellular/licensed & Cellular/licensed \\ Bandwidth & 125 KHz & 0.1/0.6 KHz & 0.1 KHz & 200 KHz & 20 MHz \\ Data Rate & \(\sim\)10 kbps & \(\sim\)100 bps & \(\sim\)300 kbps & 150 kbps & \(\sim\)10 Mbps \\ TX Power & 14 dBm & 14/27 dBm & 13/24 dBm & 23/35 dBm & 23 dBm \\ Roaming & N & N & N & Y & Y \\ \hline \hline \end{tabular}
\end{table}
Table 1: Low Power Wide Area Radio Technologies for Internet of Things (IoT) Service.  
information/service discovery exploiting the social network of \"friend\" objects. The general approach is described according to which members of the SIoT collaborate to exchange channel status information.  
[PERSON] et al. [26] propose a distributed spectrum sensing method based on an IoT architecture. The architecture comes in support of short-range video broadcasting for delivering commercial contents to several TV devices in an indoor scenario, involving several sensing-enabled objects in a joint manner. The main contribution of this study is the creation of new templates for the virtual objects (VOs) in order to represent the spectrum sensing capabilities of the involved devices. The VOs are combined at the higher levels of the IoT platform to find the relevant VOs and to decide whether the sensed channels can be used or not by secondary users.