Skip to main content

Difference between AWGN and Rayleigh Fading


1. Introduction

Rayleigh fading coefficients and AWGN, or Additive White Gaussian Noise (AWGN) in Wireless Channels, are two distinct factors that affect a wireless communication channel. Mathematically, the received signal is represented as:

Rayleigh Fading due to multi-paths
Fig: Rayleigh Fading due to multi-paths

Let's explore wireless communication under two common noise scenarios: AWGN (Additive White Gaussian Noise) and Rayleigh fading.

y = h * x + n ... (i)

The symbol '*' represents convolution (in frequency-selective multipath channels) or multiplication (in frequency-flat fading channels).

The transmitted signal x is modified by the channel coefficient or channel impulse response (h), and the symbol "n" stands for the white Gaussian noise added to the signal. Due to multiple propagation paths (reflections, diffractions), the channel impulse response (h) changes, leading to the phenomenon of Rayleigh fading.

2. Additive White Gaussian Noise (AWGN)

The mathematical effect involves adding Gaussian-distributed noise to the modulated signal. In a channel where fading is negligible (h=1), the received signal y(t) is:

y(t) = x(t) + n(t)

Where:

  • x(t) is the modulated signal.
  • n(t) is the AWGN with zero mean and variance σ².

The effect of AWGN is to add random variations to the amplitude and phase of the signal, which can lead to erroneous detection. The SNR (signal-to-noise ratio) plays a crucial role in determining the quality of demodulation; in AWGN channels, the BER decreases exponentially as SNR increases.

We measure SNR at the receiver side to evaluate performance (Signal-to-Noise Ratio (SNR) Explained). Because the power spectral density (PSD) of this noise is frequency independent (flat), it is termed "white" Gaussian noise.

3. Rayleigh Fading

AWGN and Rayleigh Fading illustration

Mathematically, Rayleigh fading can be represented as a complex Gaussian random variable with zero mean. This occurs when there is no dominant Line-of-Sight (LOS) path. The received signal y(t) is:

y(t) = h * x(t) + n(t)

  • h is the complex fading coefficient, representing random attenuation and phase shift.
  • x(t) is the modulated signal.
  • n(t) is the noise.

Rayleigh fading causes random fluctuations in signal power (fades). Diversity, achieved through multiple antennas (MIMO), is the most effective method to mitigate these deep fades.

The Rayleigh distribution describes how the amplitudes a = |h| vary. For a normalized channel (average power = 1), the PDF is:

fA(a) = 2a e-a^2, a ≥ 0

The phases of the fading channel coefficient are uniformly distributed over the range 0 to 2Ï€.

Simulator for the Effect of AWGN and Rayleigh Fading on a BPSK Signal

Experiment for Students: Set the SNR value to 0 dB and the number of multipath components to 1. You will observe that the theoretical BER of the BPSK signal is approximately 0.078 at an SNR of 0 dB.

Wireless communication system simulation featuring multipath components and BPSK modulation.

Wireless communication system simulation

MATLAB Code: AWGN vs Rayleigh Fading

% Written by SalimWireless.Com 
clc; clear all; close all;

% Parameters
SNR_dB = 0:2:20; 
num_bits = 10^6; 

% BPSK modulation
message = randi([0 1], 1, num_bits);
modulated_signal = 2 * message - 1;

ber_awgn = zeros(size(SNR_dB));
ber_rayleigh = zeros(size(SNR_dB));

for i = 1:length(SNR_dB)
    % 1. AWGN Channel
    rx_awgn = awgn(modulated_signal, SNR_dB(i), 'measured');
    ber_awgn(i) = sum((rx_awgn > 0) ~= message) / num_bits;
    
    % 2. Rayleigh Channel (Coherent Detection)
    h = (randn(1, num_bits) + 1i * randn(1, num_bits)) / sqrt(2);
    rx_rayleigh = h .* modulated_signal;
    rx_rayleigh = awgn(rx_rayleigh, SNR_dB(i), 'measured');
    
    % Coherent compensation (removing phase rotation)
    rx_comp = rx_rayleigh .* conj(h);
    ber_rayleigh(i) = sum((real(rx_comp) > 0) ~= message) / num_bits;
end

% Plotting
figure;
semilogy(SNR_dB, ber_awgn, 'b-o', 'LineWidth', 2); hold on;
semilogy(SNR_dB, ber_rayleigh, 'r-o', 'LineWidth', 2);
grid on; xlabel('SNR (dB)'); ylabel('BER');
legend('AWGN', 'Rayleigh Fading');
title('BER Performance: AWGN vs Rayleigh Fading');

Output

Graph showing BER performance for AWGN vs Rayleigh Fading
Fig 1: Effects of AWGN and Rayleigh Fading in Wireless Communication

Equalizer to reduce Rayleigh Fading or Multi-path Effects

(Get the MATLAB Code for the below)

BER of Equalized BPSK Signal

Diversity Gain MATLAB Code

% Written by SalimWireless.Com 
clc; clear; close all;
N = 1e5; data = randi([0,1], 1, N); x = 2 * data - 1;
nRx_max = 5; snr_dB = 0:2:15;                 
ber_sim = zeros(length(snr_dB), nRx_max);

for j = 1:nRx_max
    for k = 1:length(snr_dB)
        h = (randn(j, N) + 1i * randn(j, N)) / sqrt(2);
        y = h .* repmat(x, j, 1);
        y = awgn(y, snr_dB(k), 'measured');
        
        % Equal Gain Combining (EGC)
        y_rec = sum(y .* exp(-1i * angle(h)), 1); 
        ber_sim(k, j) = sum((real(y_rec) > 0) ~= data) / N;
    end
end

figure; semilogy(snr_dB, ber_sim); grid on;
xlabel('SNR (dB)'); ylabel('BER'); title('BER with EGC Diversity');
legend('1 Rx', '2 Rx', '3 Rx', '4 Rx', '5 Rx');

Output

Graph showing BER vs SNR for Equal Gain Combining (EGC)
Fig 2: BER vs SNR for Equal Gain Combining (EGC)

Frequently Asked Questions

Q. Why does Rayleigh fading occur?

A. Due to multi-path propagation without a Line-of-Sight component.

Q. Which kind of fading is Rayleigh fading?

A. Small-scale fading.

Q. When does deep fade occur?

A deep fade occurs when multiple signals reach the receiver out-of-phase, interfering destructively and significantly dropping the signal power.

Further Reading 



Contact Us

Name

Email *

Message *

Popular Posts

Q-function in BER vs SNR Calculation (with Simulation)

Q-function in BER vs. SNR Calculation In digital communications and signal processing, the Q-function plays a significant role in predicting system reliability. It allows engineers to quantify the probability that Gaussian noise will exceed a specific threshold, causing a bit error. What is the Q-function? The Q-function is a mathematical function representing the tail probability of the standard normal (Gaussian) distribution. It is the complementary cumulative distribution function (CCDF) of a standard Gaussian distribution. Q(x) = (1 / √(2Ï€)) ∫â‚“∞ e^(-t² / 2) dt Q-Function Interactive Simulator Move the slider to see how the "Tail Probability" (the area in red) changes. This area represents the Probability of Error (BER) . Threshold Distance ( x ) — (Simulates Increasing SNR) x = 1.0 Q(x) = 0.1587 ...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...(MATLAB Code + Simulator)

Bit Error Rate (BER) & SNR Guide Analyze communication system performance with our interactive simulators and MATLAB tools. 📘 Theory 🧮 Simulators 💻 MATLAB Code 📚 Resources BER Definition SNR Formula BER Calculator MATLAB Comparison 📂 Explore M-ary QAM, PSK, and QPSK Topics ▼ 🧮 Constellation Simulator: M-ary QAM 🧮 Constellation Simulator: M-ary PSK 🧮 BER calculation for ASK, FSK, and PSK 🧮 Approaches to BER vs SNR What is Bit Error Rate (BER)? The BER indicates how many corrupted bits are received compared to the total number of bits sent. It is the primary figure of merit f...

RMS Delay Spread, Excess Delay Spread and Multi-path ...(with MATLAB + Simulator)

📘 Overview of Delay Spread and Multi-path 🧮 Excess Delay spread 🧮 Power delay Profile 🧮 RMS Delay Spread 📚 Further Reading 📂 Other Topics on RMS Delay Spread, Excess Delay ... 🧮 Multipath Components or MPCs 🧮 Online Simulator for Calculating RMS Delay Spread 🧮 Why is there significant multipath in the case of very high frequencies? 🧮 Why RMS Delay Spread is essential for wireless communication? 🧮 Why the Power Delay Profile is essential? 🧮 MATLAB Codes for Calculating Different Types of delay Spreads Delay Spread, Excess Delay Spread, and Multipath (MPCs) The fundamental distinction between wireless and wired connections is that in wireless connections signal reaches at receiver thru multipath signal propagation rather than directed transmission like co-axial cable. Wireless Communication has no set communication path between the transmitter and the receiver. The line...

Frequency Shift Keying (FSK) Modulation & Demodulation (with Simulation)

Frequency Shift Keying (FSK) Theoretical Foundations: Frequency Shift Keying (FSK) is a discrete frequency modulation scheme wherein the digital information is encoded via instantaneous shifts in the carrier signal's frequency. The fundamental implementation is Binary FSK (BFSK), which maps binary data onto two distinct, discrete spectral states. A binary '1' (the "mark" state) is represented by a carrier frequency \( f_1 \), while a binary '0' (the "space" state) corresponds to frequency \( f_2 \). Each symbol is sustained for a bit interval denoted by \( T_b \). FSK Transmitter Characterization: The mathematical model for the modulated BFSK output \( s(t) \) is defined as: \[ s(t) = \begin{cases} A_c \cos(2\pi f_1 t), & \text{for } m = 1 \\ A_c \cos(2\pi f_2 t), & \text{for } m = 0 \end{cases} \] ...

FM Bandwidth and FM Band Explained

FM radio uses the frequency band from 88 MHz to 108 MHz , which is a 20 MHz-wide spectrum . This is the range of carrier frequencies available to stations. 108 MHz − 88 MHz = 20 MHz However, a single FM station occupies only about 200 kHz . This is the bandwidth of the modulated FM signal. 1. Why One FM Station Needs ~200 kHz FM uses frequency modulation . The bandwidth depends on how far the carrier swings. Carson's Rule gives the approximate FM bandwidth: B = 2 ( Δf + f m ) ...

OFDM Symbols and Subcarriers Explained

This article explains how OFDM (Orthogonal Frequency Division Multiplexing) symbols and subcarriers work. It covers modulation, mapping symbols to subcarriers, subcarrier frequency spacing, IFFT synthesis, cyclic prefix, and transmission. Step 1: Modulation First, modulate the input bitstream. For example, with 16-QAM , each group of 4 bits maps to one QAM symbol. Suppose we generate a sequence of QAM symbols: s0, s1, s2, s3, s4, s5, …, s63 Step 2: Mapping Symbols to Subcarriers Assume N sub = 8 subcarriers. Each OFDM symbol in the frequency domain contains 8 QAM symbols (one per subcarrier): Mapping (example) OFDM symbol 1 → s0, s1, s2, s3, s4, s5, s6, s7 OFDM symbol 2 → s8, s9, s10, s11, s12, s13, s14, s15 … OFDM sym...

Orthogonal Time Frequency Space (OTFS) (with MATLAB)

In OTFS (Orthogonal Time Frequency Space) modulation — a scheme designed for high-Doppler and time-varying wireless channels — the terms ISFFT and SFFT are key mathematical transformations used to move between different representation domains. Figure: OTFS block diagram 1. ISFFT — Inverse Symplectic Finite Fourier Transform Purpose: Transforms data symbols from the delay-Doppler domain to the time-frequency domain . \[ X[n, m] = \frac{1}{\sqrt{NM}} \sum_{k=0}^{N-1} \sum_{l=0}^{M-1} x[k, l] \, e^{j2\pi \left( \frac{nk}{N} - \frac{ml}{M} \right)} \] Here, \( N \) is the number of Doppler bins (time slots), and \( M \) is the number of delay bins (subcarriers). The ISFFT maps each data symbol from the delay-Doppler grid (where the channel is sparse and easier to equalize) to the time-frequency grid (where standard multicarrier modulation like OFDM can be applied). 2. SFFT — Symplectic Finite Fourier Transform Purpose: Performs the reverse operation ...