Project 2

Orthogonal frequency division multiplexing (OFDM) is a digital communication method that divides a high-rate data stream into multiple lower-rate streams, called subcarriers, which are transmitted simultaneously over different frequency channels. OFDM has several advantages over other methods of digital communication, including robustness against frequency-selective fading, high spectral efficiency, and simple equalization at the receiver.

The second major MIMO technique is Spatial Multiplexing. Spatial multiplexing enables a MIMO transmitter/receiver pair to increase its throughput without increasing bandwidth usage or transmit power. Multiplexing increases throughput linearly with the number of transmit or receive antennas, whichever is lower.

By enabling spatial channelization and diversity, MIMO expands bandwidth available within a given spectral bandwidth and space. There are three MIMO transmission techniques, and each offers an opportunity to selectively and adaptively optimize the space and bandwidth already in use.

MIMO is an antenna technology. It improves the capacity and data transmission rate of the communication system by connecting multiple antennas at the transmitter and the receiver.

To design an OFDM system using MATLAB, you can follow these steps:

1. Generate a data stream and modulate it onto a set of subcarriers using quadrature amplitude modulation (QAM) or some other suitable modulation scheme.

2. Map the modulated subcarriers onto an OFDM symbol by inserting a guard interval between the subcarriers and taking the inverse fast Fourier transform (IFFT). The guard interval helps to reduce inter-symbol interference (ISI) caused by multipath fading.

3. Add cyclic prefix to the OFDM symbol, which is a copy of the last part of the symbol appended to the beginning. This helps to reduce ISI caused by multipath fading at the receiver.

4. Transmit the OFDM symbol over a channel, which may introduce frequency-selective fading, noise, and other impairments.

5. At the receiver, remove the cyclic prefix and perform FFT to recover the modulated subcarriers.

6. Equalize the received subcarriers using a frequency domain equalization method such as zero-forcing (ZF) or minimum mean squared error (MMSE) equalization. This helps to compensate for the frequency-selective fading introduced by the channel.

7. Demodulate the equalized subcarriers to recover the original data stream.

8. Calculate the bit error rate (BER) by comparing the recovered data stream with the original data stream. The BER is a measure of the accuracy of the data transmission, and can be used to determine the performance of the OFDM system.

And, I have submit the OFDM Matlab code for your reference:

clc;
clear;
close all;

N = 64;
cp_size = 16;

symbol_duration = 1/20e6;

subcarrier_spacing = 1/symbol_duration;

num_symbols = 1000;

frame_length = N + cp_size;

snr_range = 0:15;

ber = zeros(size(snr_range));
ser = zeros(size(snr_range));

for i = 1:length(snr_range)

snr = snr_range(i);
ber = 0;
for k = 1:num_symbols

data = randi([0 3],1, N);
symbols = qammod(data, 4);
ofdm_symbols = sqrt(N)*ifft(symbols);

ofdm_symbols_cp = [ofdm_symbols(:, (end-cp_size+1):end) ofdm_symbols];

tx_signal = ofdm_symbols_cp;

channel_ir = [1 0.6 0.2];

rx_signal = filter(channel_ir,1,tx_signal);

rx_signal_noisy = awgn(rx_signal, snr);

rx_signal_filtered = rx_signal_noisy;

rx_symbols_cp = rx_signal_filtered(:, cp_size+1:end);

equalized_symbols = fft(rx_symbols_cp)./fft(channel_ir,N);

equalized_symbols_f = (equalized_symbols);

rx_data = qamdemod(equalized_symbols_f, 2^2);

[~, nber] = biterr(data, rx_data);
[~, ser] = symerr(symbols, equalized_symbols_f);
ber = ber + nber;
end
tber(i) = ber/num_symbols;
end

figure(1);
plot(real(equalized_symbols_f),imag(equalized_symbols_f),'x')

figure(2);
semilogy(snr_range,tber)

Notice: Here with i attached Matlab code in .fig format.

I Used 4 transmit and 4 receive antennas, And i attached image of compare the BER for MIMO OFDM system with that od a SISO OFDM System. Kindly find my attachement.