irection every 200 m with a speed range between 10 and 40 kph. 9.6.3.3 Freeway Mobility Model This mobility model is for unidirectional mobility. In this model, the device keeps moving in a constant direction for the whole scenario with variable speed. We have taken this model to represent vehicle movement on the motorway. This model 9 Feasibility of LDM to Serve User-IoT Pairs in the Future Wireless Network assumed the vehicle speed to be between 40 and 100 kph. Moreover, as the vehicle does not take turns frequently and moves freely via a single road at a higher speed, we can assume their movement to be unidirectional for a more petite time frame. This model is a simple linear model where the receiver's position can be predicted. Results and Analysis We are presenting two sets of analyses to evaluate our transmission framework. In the first set, we test the performance of LDM transmission without any additional channel coding. The results show different channel SNR requirements for UL and LL data detection. Moreover, our analytical model is also verified in this analysis. In the second set, we test the link sustainability of LDM pair with mobility. All our previously discussed mobility models are considered in this simulation, and the results show the feasibility of LDM for mobile receivers. 9.7.1 The Performance of LDM in an OFDM Framework In this simulation, two independent data sets are transmitted using LDM within an OFDM framework using an AWGN channel model. The SNR values presented in the results refer to the overall channel SNR for the OFDM signal. Table 9.1 presents the parameter used in these simulations. The analytical model in (9.10) is also evaluated alongside the simulated values. The distribution of channel capacity between UL and LL is also given, which provides a clear indication of the applicability of both layers for IoT devices and users, respectively. The performance bound of the UL layer presented in the earlier section is evaluated in Fig. 9.5. The BER performance follows a waterfall curv