Performance Evaluation of Newly Implemented Resource Blocks (RB) Allocation Schemes on NS-3 simulator for mMTC 5G NR (New Radio) Femtocells

The new standard of mobile technologies called 5G allows enormous improvements, comparing to the previous telecommunication network system LTE, in terms of user requirements by offering different use cases (eMBB, URLLC and mMTC). With the use of the Internet of Things (IoT) by 5G networks, the number of radio devices by each user will drop from 2 to around 7 to 10 devices. Despite this, the saturation of the system does not arise, thanks to the connected equipment's high density, offered by Massive machine type communications (mMTC). A Radio Resource Management RRM procedure for efficient distribution of available radio resources between those devices is essential for 5G systems. In this article, we have studied the behavior of scheduling algorithms in a 5G environment, for a large number of connected objects and for different types of data flows, while limiting to small cells (Femtocells) with a speed of 3 km/h of the User Equipment (UE). In this objective, we program in C++ two new scheduling algorithms at the base station gNb, namely Exponential PF (EXP/PF) and Exponential Rule (EXP-rule), in addition to those already existing (Maximum-Weight (MW) and Proportional Fair (PF)), using the mmWave model of the famous NS-3 simulator. The performance comparison of the different 5G scheduler schemes was inspected via two important parameters, which are the user throughput and the Signal-to-Interference-plus-Noise Ratio (SINR). Consequently, we have demonstrated that the scheduling algorithms used by LTE networks can be implemented at the 5G gNB level. The results of our simulations have shown that the EXP-rule algorithm provides the best SINR and DataRate values for voice, video and data streams.