# LoRaWAN Path Loss Measurements in an Urban Scenario Including Environmental Effects
## 1 Introduction  
The Internet of things (IoT) is an enabling paradigm of Industry 4.0 that uses sensors to extract environment-aware data in diverse applications, such as domotics [1], smart energy [2], and precision agriculture [3], among other things. The data collected is further stored and analyzed to perform classifications or regressions, helping organizations make decisions about their processes [4]. Although there are applications where the end nodes (ENs) transmit information over short distances and have unlimited energy resources (e.g., domotics), there are also some cases where the ENs must be deployed in hard-to-access places where the sensors' information has to be transmitted over distances, and where changing batteries is difficult or impossible, e.g., in forest fire monitoring [5], regulating the water level in dams [6], and landslide detection [7]. Thus, when the application has low energy and long-distance constraints, low power wide area networks (LPWANs) are used because they exhibit a good compromise between range and power consumption [8]. One of the most widespread protocols for LPWANs is LoRaWAN [9], which has gained popularity for IoT deployments because it operates in unlicensed bands, consumes low energy, and covers wide ranges compared to other competitors like narrow-band IoT (NB-IoT) or Sigfox [10]. Because LoRaWAN is a wireless sensor network (WSN) protocol [11], deploying ENs in the field requires previous network planning and link budget analyses. These analyses help establish the network parameters that achieve reliable connectivity at low energy consumption, so designers can choose different radio elements, including antennas' geometries, antennas' gains, allowed attenuations caused by cables and connectors, expected path loss (PL) and shadowing features posed by the channel, and transmission powers [12]. Consequently, the link budget calculation guarantees that the received signal strength indicator (RSSI) on the gateway (GW) side is sufficiently large to be demodulated correctly. The PL effects can be estimated by using theoretical models (e.g., Friis [13], and two-ray [12]) or empirical models (e.g., Okumura-Hata [14] and log-distance models [12]) to accomplish the link margin goals. More specifically, the Friis approach considers that the PL depends only on distance and frequency and does not consider multipath phenomena that cause shadowing [15]. Besides, the two-ray model considers a theoretical approximation of the line of sight (LoS) ray and the ray reflected over the ground, so it partially considers shadow fading effects [12]. However, because the multipath phenomenon in real applications is very diverse and complex, empirical models based on measurement campaigns are also proposed. For instance, the Okumura-Hata approach [14] provides a closed-form expression derived from collected data in Tokyo, Japan. It depends on the distance between the EN and the GW, the antenna heights, and the frequency. This model was fitted for large cells where the antennas' heights are from 30 to 100 m; however, in WSN/IoT networks, ENs' antennas are close to the ground (for example, in precision agriculture [16]), causing shadow fading effects up to 14 dB [12], which may not be suitable for IoT applications, considering that the maximum transmitter power is about 20 dBm (e.g., LoRaWAN [9]). Because of these limitations, a log-distance path loss model (LDPLM) is also fitted from field data, including a shadow fading term, which is modeled considering that the probability density function (PDF) attends a lognormal distribution. In that way, according to [17], the statistical validity of the LDPLM must meet the following conditions: (_i_) pass an analysis of variance (ANOVA) test, by which the log-distance weight (also known as a path-loss exponent) is analyzed to check its significance, and (_ii_) the residual error/shadow fading term must be log-normally distributed, homoscedastic, and uncorrelated.