# Software-Defined NB-IoT Uplink Framework--The Design, Implementation and Use Cases
## 7 Conclusions  
The complexity of the cellular systems requires wide knowledge on the radiocommunication signal processing. The new era of the technical sciences, including radiocommunication, is mostly based on the software solutions. Such an approach enables simulations in the different types of environment, from the very basic to the harsh ones, or different use cases. It gives scientists and students opportunities to develop best-suited cellular concepts, such as the NB-IoT. In Section 3, some NB-IoT simulators were described in terms of their abilities and limitations. However, the implementation of the real radiocommunication interface in the sensor devices on the basis of computer simulations is often very ineffective, as it does not take into account the limitations of the low-level implementation in general purpose processors or the FPGA matrices. Therefore, the implemented didactic framework, based on the didactic experience of the authors, goes beyond the simple simulations concerning implementation constraints as well. The main advantage of this approach is the opportunity to observe and further analyze both inter- and intramodule data flow along the whole physical layer, according to Figure 2. It is worth mentioning that this feature is not provided by the commercially available simulation tools such as Matlab or Simulink. All presented functions are organized as the functional modules that are compliant with Rel. 13/14 3 GPP standards. Their detailed description is included in Section 5, and further supported by the functional analysis included in Section 6.  
Not every module has the same computational cost, so it is reasonable to focus on the software optimization as it directly influences the power consumption when the computational time is reduced. From the educational point of view, it is even more important to implement some software parts step by step, because it provides better understanding of the issue. Observations presented in Section 6 allow students to assess which part of the uplink they should expend more effort on, especially in the context of efficient sensor networks. It is worth mentioning that every part of the PHY layer can be checked and evaluated independently by using the specially generated sets of the input vectors. During the future works, authors want to propose a similar framework for the downlink path that is currently under development. It will provide similar possibilities which will extend the didactic abilities of the hardware- and software-based laboratory for the Bachelors and Masters students.  
A.O., O.B., K.K.C., P.R. and J.S. methodology, designing and performing measurements, data analysis, scientific discussions, and writing the paper. All authors have read and agreed to the published version of the manuscript.  
This work has been partially financed and carried out as part of the project entitled \"A software-defined, universal radio interface for intelligent devices of Internet of Things\", co-financed under the European Regional Development Fund within the Smart Growth Operational Program, agreement no. POIR.01.01.01-00-1025/19, realized in the Gdansk University of Technology, Faculty of Electronics Telecommunication and Informatics, Department of Radiocommunication Systems and Networks.  
**Data Availability Statement:** Input and output vectors with additional parameters test matrix are available for free from the authors with the CC BY license for educational purposes.  
**Conflicts of Interest:** The authors declare no conflict of interest.