2023-06-16 14:33 Tags: # Log-distance path loss model Commonly used model for large scale propagation modelling. Path loss is based on empirical measurements. [^1] Log distance path loss is a mathematical model used to describe the attenuation or loss of signal strength as it propagates through a wireless communication channel. It is a simplified representation of the effects of distance, obstruction, and other factors that can degrade the signal. The log distance path loss model is based on the inverse square law, which states that the power of a signal decreases as the square of the distance from the transmitter increases. The model assumes that the received signal power (Pr) is inversely proportional to the distance (d) raised to a power exponent (n). Mathematically, it can be represented as: Pr = Pt - 10 * n * log10(d/d0) + X where: - Pr is the received signal power in decibels (dB) - Pt is the transmitted signal power in decibels (dB) - n is the path loss exponent, which depends on the environment and frequency - d is the distance between the transmitter and receiver - d0 is a reference distance - X is a zero-mean Gaussian random variable representing the log-normal shadow fading component. The path loss exponent (n) typically ranges between 2 and 6, depending on the propagation environment. It takes into account factors such as the frequency of the signal, the characteristics of the surrounding environment (e.g., free space, urban area, indoor environment), and the presence of obstacles or interference. The reference distance (d0) is a fixed distance at which the path loss is known or calibrated. It is often chosen as a reference point where the received power is measured. The value of d0 can vary depending on the specific system or application. The term X represents the log-normal shadow fading, which accounts for random variations in signal strength due to obstacles, multipath propagation, and other environmental factors. It is modeled as a zero-mean Gaussian random variable with a standard deviation that reflects the statistical properties of the fading process. It is important to note that the log distance path loss model is a simplification and may not capture all the complexities of real-world wireless propagation. Different models, such as the Okumura-Hata or COST 231 models, have been developed to provide more accurate predictions in specific environments. References: 1. Rappaport, T. S. (2002). Wireless Communications: Principles and Practice. Prentice Hall. 2. Goldsmith, A. (2005). Wireless Communications. Cambridge University Press. 3. Saleh, A. A., & Valenzuela, R. A. (1987). A statistical model for indoor multipath propagation. IEEE Journal on Selected Areas in Communications, 5(2), 128-137. # References [^1]: [A-SURVEY-ON-CHANNEL-MODELING-FOR-VEHICULAR-COMMUNICATIONS](../../03%20-%20University/Thesis/literature%20review/1st%20-%20significant/A-SURVEY-ON-CHANNEL-MODELING-FOR-VEHICULAR-COMMUNICATIONS.pdf) [^2]: https://chat.openai.com/share/5012c25d-ed97-484b-8e59-3e48d89b374a