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Online Simulator for M-ary PSK Signal Generation


M-ary PSK

M must be a power of 2 (e.g., 2, 4, 8, 16)



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Hybrid Beamforming | Page 2

Beamforming Techniques Hybrid Beamforming... Page 1 | Page 2 | clear all; close all; clc; Nt = 64; Nr = 16; NtRF = 4; NrRF = 4; At both the transmitter and receiver ends, there are four RF chains only for a hybrid beamforming system. Alternatively, every 16 antenna elements on the transmitter side is connected to a single RF chain, while every 4 antenna elements on the receiver side are connected to a single RF chain. Mixers, amplifiers, and other critical wireless communication components make up the RF chain. Now, in the case of hybrid beamforming, there can be four different data streams between the transmitter and receiver, as both sides have four RF chains, each of which is accountable for a separate data stream. For Analog Beamforming: All 64 Tx antenna elements create a beam or focus the resultant correlated signal spread from adjacent antennas to a particular direction. Similarly, it may be used for beam...

Theoretical BER vs SNR for binary ASK and FSK

📘 Overview & Theory 🧮 MATLAB Codes 📚 Further Reading Theoretical Ber vs SNR for Amplitude Shift Keying (ASK) The theoretical bit error rate (BER) for binary Amplitude Shift Keying (ASK) as a function of the signal-to-noise ratio (SNR) can be derived using the following expression: If we map the binary signals to 1 and -1 in ASK , the probability of bit error will be: BER = Q(√(2*SNR))   If we map the binary signals to 0 and 1 in ASK , the probability of bit error will be:    BER = Q(√(SNR/2))   Where: Q(x) is the Q-function, which is the tail probability of the standard normal distribution. SNR is the signal-to-noise ratio. N0 is the noise power spectral density. Where Q is the Q function In mathematics Q(x) = 0.5 * erfc(x/ √ 2)   Calculate the Probability of Error using Q-function for ASK: For ASK with amplitudes 0 and 1 : When bit '0' is transmitted, the received signal is noise only . When bit '1' is transmitted, the re...

Constellation Diagrams of ASK, PSK, and FSK

📘 Overview of Energy per Bit (Eb / N0) 🧮 Online Simulator for constellation diagrams of ASK, FSK, and PSK 🧮 Theory behind Constellation Diagrams of ASK, FSK, and PSK 🧮 MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK 📚 Further Reading 📂 Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... 🧮 Simulator for constellation diagrams of m-ary PSK 🧮 Simulator for constellation diagrams of m-ary QAM 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...

MATLAB Code for Zero-Forcing (ZF) Beamforming in 4×4 MIMO Systems

MATLAB Code for Zero-Forcing (ZF) Beamforming in 4×4 MIMO Systems clc; clear; close all; %% Parameters Nt = 4; % Transmit antennas Nr = 4; % Receive antennas (must be >= Nt for ZFBF) numBits = 1e4; % Number of bits per stream SNRdB = 0; % SNR in dB numRuns = 100; % Number of independent runs for averaging %% Precompute noise standard deviation noiseSigma = 10^(-SNRdB / 20); %% Accumulator for total errors totalErrors = 0; for run = 1:numRuns % Generate random bits: [4 x 10000] bits = randi([0 1], Nt, numBits); % BPSK modulation: 0 → +1, 1 → -1 txSymbols = 1 - 2 * bits; % Rayleigh channel matrix: [4 x 4] H = (randn(Nr, Nt) + 1j * randn(Nr, Nt)) / sqrt(2); %% === Zero Forcing Beamforming at Transmitter === W_zf = pinv(H); % Precoding matrix: [Nt x Nr] txPrecoded = W_zf * txSymbols; % Apply ZF precoding % Normalize transmit power (optional but useful) txPrecoded = txPrecoded / sqrt(mean(abs(txPrecoded(:)).^2)); %% Channel transmission with AWGN noise = noiseSigma * (randn(...

Channel Impulse Response (CIR)

Channel Impulse Response (CIR) 📘 Overview & Theory 📘 How does the channel impulse response affect the signal? 🧮 Online Channel Impulse Response Simulator 🧮 MATLAB Codes 📚 Further Reading Wireless Signal Processing CIR, Doppler Shift & Gaussian Random Variable  The Channel Impulse Response (CIR) is a concept primarily used in the field of telecommunications and signal processing. It provides information about how a communication channel responds to an impulse signal.   What is the Channel Impulse Response (CIR) ? It describes the behavior of a communication channel in response to an impulse signal. In signal processing,  an impulse signal has zero amplitude at all other times and amplitude  ∞ at time 0 for the signal. Using a Dirac Delta function, we can approximate this.  ...(i) δ( t) now has a very intriguing characteristic. The answer is 1 when the Fourier Transform of  δ(...

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

📘 Comparisons among ASK, FSK, and PSK 🧮 Online Simulator for calculating Bandwidth of ASK, FSK, and PSK 🧮 MATLAB Code for BER vs. SNR Analysis of ASK, FSK, and PSK 📚 Further Reading 📂 View Other Topics on Comparisons among ASK, PSK, and FSK ... 🧮 Comparisons of Noise Sensitivity, Bandwidth, Complexity, etc. 🧮 MATLAB Code for Constellation Diagrams of ASK, FSK, and PSK 🧮 Online Simulator for ASK, FSK, and PSK Generation 🧮 Online Simulator for ASK, FSK, and PSK Constellation 🧮 Some Questions and Answers Modulation ASK, FSK & PSK Constellation MATLAB Simulink MATLAB Code Comparisons among ASK, PSK, and FSK    Comparisons among ASK, PSK, and FSK   Simulator for Calculating Bandwidth of ASK, FSK, and PSK The baud rate represents the number of symbols transmitted per second. Both baud rate and bit rate a...

How Windowing Affects Your Periodogram

The windowed periodogram is a widely used technique for estimating the Power Spectral Density (PSD) of a signal. It enhances the classical periodogram by mitigating spectral leakage through the application of a windowing function. This technique is essential in signal processing for accurate frequency-domain analysis.   Power Spectral Density (PSD) The PSD characterizes how the power of a signal is distributed across different frequency components. For a discrete-time signal, the PSD is defined as the Fourier Transform of the signal’s autocorrelation function: S x (f) = FT{R x (Ï„)} Here, R x (Ï„)}is the autocorrelation function. FT : Fourier Transform   Classical Periodogram The periodogram is a non-parametric PSD estimation method based on the Discrete Fourier Transform (DFT): P x (f) = \(\frac{1}{N}\) X(f) 2 Here: X(f): DFT of the signal x(n) N: Signal length However, the classical periodogram suffers from spectral leakage due to abrupt truncation of the ...

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.  Understanding the Q...