Skip to main content
Home Wireless Communication Modulation MATLAB Beamforming Project Ideas MIMO Computer Networks

Pathloss : Large Scale & Small Scale Pathloss and Pathloss Exponent 'n'



In wireless communication, the path loss is proportional to the square of the operating carrier frequency. As a result, the higher the frequency, the greater the path loss. Although path loss is affected by several parameters, including fading, shadowing, angle of arrival (AOA), and angle of departure (AOD), and others. In comparison to lesser frequencies, when the frequency is extremely high, it is easily absorbed by atmospheric gases, vapor, and rain. In the case of higher frequencies, however, the penetration loss is also greater. Path loss is linearly proportional to the carrier frequency, according to Firs' free space path loss. Path loss parameters are often divided into two categories. 1. Large Scale Path loss; 2. Small Scale Path loss. Large-scale path losses are basically path losses due to the distance between transmitter and receiver, shadowing loss, etc. Examples of small-scale path losses due to fading, angle of arrival & angle of departure, etc.


1. Free Space Pathloss:

This phenomenon occurs when a signal travels across empty space. The formula for free space path loss, or FSPL, is
Pathloss = 20log10(λ/4Ï€d) ... (1)

Free space path loss, however, is not completely relevant when discussing real-world wireless communication systems, particularly cellular wireless networks. because the FSPL includes atmospheric path loss. In addition, variable environmental conditions, regardless of TX and RX distance, result in varied path loss. For various environments, the path-loss exponent (PLE) 'n' changes dramatically. Below, we've talked about PLE.

Received signal power in an atmospheric environment can be defined as

Pr  = Pt + Gt + Gr + 20log10(λ/4Ï€d) + atmospheric pathloss……… (2)

                                             Pr = Received Power & Pt = Transmitted Power                                             
                                             Î» = wavelength of carrier frequency
                                             d = distance between Tx & Rx
                                            Gt & Gr = transmitter & receiver antenna gain, respectively
                                            20log10(λ/4Ï€d) = free space path loss at first propagation reference distance d

2. Close-in Path Loss Model:

The close-in path loss model is appropriate for current wireless communication systems operating at sub-6 GHz band or higher and is also applicable for millimeter wave 5G communication.

.... (3)

FSPL (d0) denotes free space path loss at the first few meters (i.e., 1 meter). The letter 'n' stands for path loss exponent. The letter 'd' represents the total path length between the transmitter and the receiver. The shadowing factor is denoted by the symbol, χσ.

This allows us to calculate path loss for current wireless communication bands, such as UWB communication, with excellent precision. This path loss model implies that it is extremely high for the first few meters, then exponentially increases based on the path loss exponent value for that environment (LOS or NLOS, urban or rural, etc.). In 28 GHz transmission, for example, path loss from the first meter is roughly 32 dB Following then, path loss grows by the wireless environment's path loss exponent value.


3.1. Large Scale Pathloss:

The path loss increases as the distance between the transmitter and receiver grow because the signal is attenuated in the atmospheric air as it travels the distance. When a path of equal length is propagated at different frequencies, the path loss is higher at higher frequencies than at lower frequencies. Similarly, path loss for LOS and NLOS pathways differs when TX and RX are positioned at a given distance. Because NLOS pathways typically cover a greater distance than LOS paths. The LOS path connects the transmitter and receiver in a straight line. [Read More about LOS and NLOS Paths]


3.2. Small Scale Pathloss:

Fading, angle of arrival (AOA) at the receiver, angle of departure (AOD) at the receiver, and other factors contribute to small-scale route losses. We send a signal from the transmitter antenna, which then spreads away from the antenna. There must be structures and vegetation there. As a result, the signal is reflected or refracted by the walls of the building or the foliage. The reflected or refracted signal then travels to the receiver via many NLOS paths other than the line of sight (LOS). Finding a LOS path between transmitter and receiver in densely built locations is tough. As a result, the same signal comes as MPCs at the receiver, and we find temporal dispersion for the arrival of the first and last MPCs for broadcasting the same signal from the transmitter side. Fading is caused by these MPCs. There are various types of fading, such as slow or fast fading, frequency selective fading, and so on. Fast fading occurs when the channel impulse response varies rapidly. Frequency selective fading refers to fading that varies according to frequency. We can see distinct fading patterns depending on the frequency. Assume we're looking at a different fading type/property for frequency F1 and a different fading type/property for frequency F2.

People are good at skipping over material they already know!

View Related Topics to







Admin & Author: Salim

profile

  Website: www.salimwireless.com
  Interests: Signal Processing, Telecommunication, 5G Technology, Present & Future Wireless Technologies, Digital Signal Processing, Computer Networks, Millimeter Wave Band Channel, Web Development
  Seeking an opportunity in the Teaching or Electronics & Telecommunication domains.
  Possess M.Tech in Electronic Communication Systems.


Contact Us

Name

Email *

Message *

Popular Posts

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...

Modulation Constellation Diagrams BER vs. SNR MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...   MATLAB Script for  BER vs. SNR for M-QAM, M-PSK, QPSk, BPSK %Written by Salim Wireless %Visit www.salimwireless.com for study materials on wireless communication %or, if you want to learn how to code in MATLAB clc; clear; close all; % Parameters num_symbols = 1e5; % Number of symbols snr_db = -20:2:20; % Range of SNR values in dB % PSK orders to be tested psk_orders = [2, 4, 8, 16, 32]; % QAM orders to be tested qam_orders = [4, 16, 64, 256]; % Initialize BER arrays ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); % BER calculation for each PSK order and SNR value for i = 1:length(psk_orders) psk_order = psk_orders(i); for j = 1:length(snr_db) % Generate random symbols data_symbols = randi([0, psk...

Channel Estimation utilizing Decision Feedback Equalizer (DFE)

  Channel estimation using DFE is a similar process to a non-linear equalization process. In DFE (decision feed equalizer), equalization error bits/symbols between the feedforward tabs and feedback taps are calculated continuously. And equalizer's tap weights tap weights are updated correspondingly.  In plain language, the error between the received bits and known training bits is calculated, and tap weights are updated accordingly. The equalizer estimates the channel impulse response (CIR) .  Once we find the channel impulse response or channel information, we can easily retrieve the original message signal from the noisy data. In the communication process, the whole system is modeled as a linear time-invariant (LTI) system. And  y = h*x + n where, y = received signal            x = transmitted signal           n = additive white Gaussian noise [Read more about the Linear time-invariant (LTI) system and convolu...

Theoretical BER vs SNR for BPSK

Let's simplify the explanation for the theoretical Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) for Binary Phase Shift Keying (BPSK) in an Additive White Gaussian Noise (AWGN) channel.  Key Points Fig 1: Constellation Diagrams of BASK, BFSK, and BPSK [↗] BPSK Modulation: Transmits one of two signals: +√Eb ​ or -√Eb , where Eb​ is the energy per bit. These signals represent binary 0 and 1 . AWGN Channel: The channel adds Gaussian noise with zero mean and variance N0/2 (where N0 ​ is the noise power spectral density). Receiver Decision: The receiver decides if the received signal is closer to +√Eb​ (for bit 0) or -√Eb​ (for bit 1) . Bit Error Rate (BER) The probability of error (BER) for BPSK is given by a function called the Q-function. The Q-function Q(x) measures the tail probability of the normal distribution, i.e., the probability that a Gaussian random variable exceeds a certain value x.  Formula for BER: BER=Q(...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

Modulation Constellation Diagrams BER vs. SNR BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ... 1. What is Bit Error Rate (BER)? The abbreviation BER stands for bit error rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. It is defined as,  In mathematics, BER = (number of bits received in error / total number of transmitted bits)  On the other hand, SNR refers to the signal-to-noise power ratio. For ease of calculation, we commonly convert it to dB or decibels.   2. What is Signal the signal-to-noise ratio (SNR)? SNR = signal power/noise power (SNR is a ratio of signal power to noise power) SNR (in dB) = 10*log(signal power / noise power) [base 10] For instance, the SNR for a given communication system is 3dB. So, SNR (in ratio) = 10^{SNR (in dB) / 10} = 2 Therefore, in this instance,...

MATLAB Codes for Various types of beamforming | Beam Steering, Digital...

Beamforming Techniques MATLAB Codes for Beamforming... The mathematical [↗] and theoretical aspects of beamforming [↗] have already been covered. We'll talk about coding in MATLAB in this tutorial so that you may generate results for different beamforming approaches. Let's go right to the content of the article. In analog beamforming, certain codebooks are employed on the TX and RX sides to select the best beam pairs. Because of their beamforming gains, communication created through the strongest beams from both the TX and RX side enhances spectrum efficiency. Additionally, beamforming gain directly impacts SNR improvement. Wireless communication system capacity = bandwidth*log2(1+SNR) bits/s. Thus, the capacity or overall throughput of the system increases. MATLAB Script %Written by Salim Wireless %Visit www.salimwireless.com for study materials on wireless communication %or, if you want to learn how to code in MATLAB clear all;...

Constellation Diagrams of ASK, PSK, and FSK

Modulation ASK, FSK & PSK Constellation BASK (Binary ASK) Modulation: Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BFSK (Binary FSK) Modulation: Transmits one of two signals: +√Eb​ ( On the y-axis, the phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals: +√Eb​ or -√Eb (they differ by 180 degree phase shift), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  This article will primarily discuss constellation diagrams, as well as what constellation diagrams tell us and the significance of constellation diagrams. Constellation diagrams can often demonstrate how the amplitude and phase of signals or symbols differ. These two characteristics lessen the interference between t...

Comparisons among ASK, PSK, and FSK | And the definitions of each

Modulation ASK, FSK & PSK Constellation MATLAB Simulink MATLAB Code Comparisons among ASK, PSK, and FSK    Comparisons among ASK, PSK, and FSK Comparison among ASK,  FSK, and PSK Performance Comparison: 1. Noise Sensitivity:    - ASK is the most sensitive to noise due to its reliance on amplitude variations.    - PSK is less sensitive to noise compared to ASK.    - FSK is relatively more robust against noise, making it suitable for noisy environments. 2. Bandwidth Efficiency:    - PSK is the most bandwidth-efficient, requiring less bandwidth than FSK for the same data rate.    - FSK requires wider bandwidth compared to PSK.    - ASK's bandwidth efficiency lies between FSK and PSK. Bandwidth Calculator for ASK, FSK, and PSK The baud rate represents the number of symbols transmitted per second Select Modulation Type: ASK...

Constellation Diagram of PSK in Detail

        Fig 1: Constellation Diagram of PSK    In the above figure, the binary bit '1' is represented by S1(t) and the binary bit '0' by S2(t), respectively. So, energy of S1(t) = (√(Eb))2 = Eb So, energy of S2(t) = (-√(Eb))2 = Eb Distance between the signaling points, d12 = 2(√(Eb))   Energy per bit for binary '1' and binary '0'           High-order PSK (e.g., 8 PSK, 16 PSK) can transmit more bits per symbol but is more sensitive to noise. Low-order PSK (e.g., BPSK, QPSK) is less susceptible to noise. PSK modulation can be visualized using a constellation diagram, where each point represents a symbol. In the presence of noise, points may be away from the original positions, making them harder to distinguish.