Fig 1: Digital Beamforming    The main working principle between the beamforming (or analog beamforming) is to maximize the signal strength in a particular direction towards the receiver. For example, you can steer the antenna manually towards the transmitter to maximize the signal strength, like dish antennas. However, the approach could be more practical for mobile communications. With the help of a phase shifter, we do it electronically. On the other hand, for example, a dish antenna has an aperture that adds some gain to the received signal.Similarly, placing many antennas at a particular space instant creates a beam in a specific direction, minimizing signal strength in the rest of the directions. Here, a combination of antennas creates virtual apertures. On the transmitter side, it transmits a more robust signal toward the receiver. Oppositely, it makes a virtual aperture at the receiver and captures the signal more efficiently. The main advantage of beamforming is maximiz

  The code below is an example of 2 X 2 MIMO.   MATLAB Code clc; clear all; close all; % MIMO System Parameters numTx = 2; % Number of transmit antennas numRx = 2; % Number of receive antennas numSymbols = 50; % Number of symbols to transmit % Generate random binary data data = randi([0, 1], numTx, numSymbols); % PSK Modulation (BPSK) modulatedSymbols = 1 - 2 * data; % BPSK modulation: '0' maps to +1, '1' maps to -1 % Precoding (Identity Matrix for demonstration) precodingMatrix = eye(numTx); % Transmit Signal transmitSignal = precodingMatrix * modulatedSymbols; % Channel (Rayleigh Fading Channel) H = (randn(numRx, numTx) + 1i * randn(numRx, numTx)) / sqrt(2); % Rayleigh fading channel % Received Signal receivedSignal = H * transmitSignal; % Demodulation demodulatedSymbols = H' * receivedSignal; % PSK Demodulation (BPSK) receivedData = demodulatedSymbols < 0; % Decision threshold at 0 Output       Fig 1: Original Message Bits             Fig 2: Received Message

  In Rayleigh fading, the channel coefficients tend to have a Rayleigh distribution, which is characterized by a random phase and magnitude with an exponential distribution. This means the magnitude of the channel coefficient follows an exponential distribution with a mean of 1. In Rician fading, there is a dominant line-of-sight component in addition to the scattered components. The channel coefficients in Rician fading can indeed tend towards 1, especially when the line-of-sight component is strong. When the line-of-sight component dominates, the Rician fading channel behaves more deterministically, and the channel coefficients may tend towards the value of the line-of-sight component, which could be close to 1.   MATLAB Script clc; clear all; close all; % Define parameters numSamples = 1000; % Number of samples K_factor = 5; % K-factor for Rician fading SNR_dB = 20; % Signal-to-noise ratio (in dB) % Generate complex Gaussian random variable for Rayleigh fading channel h_rayleigh = (

  MATLAB Script % The code is written by SalimWireless.Com clc; clear all; close all; % Generate random bits numBits = 100; bits = randi([0, 1], 1, numBits); % Define parameters numSubcarriers = 4; % Number of subcarriers numPilotSymbols = 3; % Number of pilot symbols cpLength = ceil(numBits / 4); % Length of cyclic prefix (one-fourth of the data length) % Add cyclic prefix dataWithCP = [bits(end - cpLength + 1:end), bits]; % Insert pilot symbols pilotSymbols = ones(1, numPilotSymbols); % Example pilot symbols (could be any pattern) dataWithPilots = [pilotSymbols, dataWithCP]; % Perform OFDM modulation (IFFT) dataMatrix = reshape(dataWithPilots, numSubcarriers, []); ofdmSignal = ifft(dataMatrix, numSubcarriers); ofdmSignal = reshape(ofdmSignal, 1, []); % Display the generated data disp("Original Bits:"); disp(bits); disp("Data with Cyclic Prefix and Pilots:"); disp(dataWithPilots); disp("OFDM Signal:"); disp(ofdmSignal); %%%%%%%%%%%%%%%%%%%%%%%%%%% Demodul

  Alamouti's Space-Time Block Coding (STBC) is a technique used in MIMO wireless communication systems to achieve diversity gain without requiring channel knowledge at the transmitter. It involves transmitting multiple copies of the same symbols over multiple antennas with specific phase relationships. This allows the receiver to combine the signals effectively and recover the transmitted symbols even in the presence of fading. The Alamouti precoding matrix is constructed based on the Alamouti code, which defines the phase relationships between the symbols transmitted from different antennas over two consecutive time slots. For a 2x1 MIMO system (two transmit antennas and one receive antenna), the Alamouti precoding matrix is as follows: Precoding Matrix=[s1  −s2∗;  s2   s1∗] Where:     s1 and s2 are the symbols to be transmitted from the two antennas in the current time slot.     s1∗​ and s2∗​ are the complex conjugates of s1​ and s2​ respectively. This matrix ensures that the sy