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The development of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs), and autonomous driving (AD) has progressed rapidly in recent years, driven by artificial intelligence (AI), the internet of things (IoT), and their integration with dedicated short-range communications (DSRC) systems and fifth-generation (5G) networks. This has led to improved mobility conditions in different road propagation environments: urban, suburban, rural, and highway. The use of these communication technologies has enabled drivers and pedestrians to be more aware of the need to improve their behavior and decision making in adverse traffic conditions by sharing information from cameras, radars, and sensors widely deployed in vehicles and road infrastructure. However, wireless data transmission in VANETs is affected by the specific conditions of the propagation environment, weather, terrain, traffic density, and frequency bands used. In this paper, we characterize the path loss based on the extensive measurement campaign carrier out in vehicular environments at 700 MHz and 5.9 GHz under realistic road traffic conditions. From a linear dual-slope path loss propagation model, the results of the path loss exponents and the standard deviations of the shadowing are reported. This study focused on three different environments, i.e., urban with high traffic density (U-HD), urban with moderate/low traffic density (U-LD), and suburban (SU). The results presented here can be easily incorporated into VANET simulators to develop, evaluate, and validate new protocols and system architecture configurations under more realistic propagation conditions.

The usage scenarios defined in the ITU-M2150-1 recommendation for IMT-2020 systems, including enhanced Mobile Broadband (eMBB), Ultra-reliable Low-latency Communication (URLLC), and massive Machine Type Communication (mMTC), allow the possibility of accessing different services through the set of Radio Interface Technologies (RITs), Long-term Evolution (LTE), and New Radio (NR), which are components of RIT. The potential of the low and medium frequency bands allocated by the Federal Communications Commission (FCC) for the fifth generation of mobile communications (5G) is described. In addition, in the Internet of Things (IoT) applications that will be covered by the case of use of the mMTC are framed. In this sense, a propagation channel measurement campaign was carried out at 850 MHz and 5.9 GHz in a covered corridor environment, located in an open space within the facilities of the Pedagogical and Technological University of Colombia campus. The measurements were carried out in the time domain using a channel sounder based on a Universal Software Radio Peripheral (USRP) to obtain the received signal power levels over a range of separation distances between the transmitter and receiver from 2.00 m to 67.5 m. Then, a link budget was proposed to describe the path loss behavior as a function of these distances to obtain the parameters for the close-in free space reference distance (CI) and the floating intercept (FI) path loss prediction models. These parameters were estimated from the measurements made using the Minimum Mean Square Error (MMSE) approach. The estimated path loss exponent (PLE) values for both the CI and FI path loss models at 850 MHz and 3.5 GHz are in the range of 2.21 to 2.41, respectively. This shows that the multipath effect causes a lack of constructive interference to the received power signal for this type of outdoor corridor scenario. These results can be used in simulation tools to evaluate the path loss behavior and optimize the deployment of device and sensor network infrastructure to enable 5G-IoT connectivity in smart university campus scenarios.

Abstract In this paper, estimators of the Nakagami-lognormal (NL) distribution based on the method of log-moments have been derived and thoroughly analyzed. Unlike maximum likelihood (ML) estimators, the log-moment estimators of the NL distribution are obtained using straightforward equations with a unique solution. Also, their performance has been evaluated using the sample mean, confidence regions and normalized mean square error (NMSE). The NL distribution has been extensively used to model composite small-scale fading and shadowing in wireless communication channels. This distribution is of interest in scenarios where the small-scale fading and the shadowing processes cannot be easily separated such as the vehicular environment.

The bivariate Nakagami-lognormal distribution used to model the composite fast fading and shadowing has been examined exhaustively. In particular, we have derived the joint probability density function, the cross-moments, and the correlation coefficient in power terms. Also, two procedures to generate two correlated Nakagami-lognormal random variables are described. These procedures can be used to evaluate the robustness of the sample correlation coefficient distribution in both macro- and microdiversity scenarios. It is shown that the bias and the standard deviation of this sample correlation coefficient are substantially high for large shadowing standard deviations found in wireless communication measurements, even if the number of observations is considerable.

The knowledge of the propagation channel properties is an important issue for a successful design of ultrawideband (UWB) communication systems enabling high data rates in short-range applications. From an indoor measurement campaign carried out in a typical laboratory environment, this paper analyzes the path loss and time-dispersion properties of the UWB channel. Values of the path loss exponent are derived for the direct path and for a Rake receiver structure, examining the maximum multipath diversity gain when an all Rake (ARake) receiver is used. Also, the relationship between time-dispersion parameters and path loss is investigated. The UWB channel transfer function (CTF) was measured in the frequency domain over a channel bandwidth of 7.5 GHz in accordance with the UWB frequency range (3.1–10.6 GHz).