Skip to main content

Alamouti's Scheme for MIMO Communication

 

 The Alamouti scheme is a simple and effective space-time block coding (STBC) technique used in wireless communications to achieve diversity gain. It's designed for systems with two transmit antennas and one or more receive antennas, providing transmit diversity.

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.

Alamouti 2 X 1 Matrix Equation Representation

y
=
h11
h21
X
s1 -s2*
s2 s1*
+
n
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 symbols transmitted from the two antennas in the current time slot have the necessary phase relationships to achieve diversity gain at the receiver.

Here's how the Alamouti precoding matrix works:

    In the first time slot, symbols s1​ and s2​ are transmitted from the two antennas without any phase manipulation.
    In the second time slot, symbols −s2∗​ and s1∗​ are transmitted from the two antennas. The negative sign and complex conjugate ensure the correct phase relationship required for diversity gain at the receiver.
    At the receiver, combining the signals from the two time slots using Alamouti decoding allows for effective recovery of the transmitted symbols, even in the presence of fading.

By using Alamouti's STBC and the corresponding precoding matrix, the MIMO system can achieve diversity gain and improve performance without requiring explicit channel knowledge at the transmitter. 

 

Orthogonality Property 

Alamouti's Space-Time Block Coding (STBC) scheme ensures that symbols transmitted from different antennas in successive time slots are orthogonal to each other. This orthogonality property is essential for enabling simple decoding at the receiver and achieving diversity gain without requiring channel knowledge at the transmitter.



Now, let's calculate the inner product (dot product) between two encoded symbols transmitted from different antennas in successive time slots.

Let x1x1​ and x2x2​ be the encoded symbols transmitted from the two antennas in the first and second time slots respectively.

x1=[s1 ; s2]
x2=[−s2∗​ ; s1∗​​]

The inner product x1' * x2​ is given by:

x1' * x2​ = [s1 ; ​​s2​​] * [−s2∗​ ; s1∗​​]
=−∣s2∣^2 + ∣s1∣^2


Since the symbols s1​ and s2​ are independent and identically distributed (IID) random variables with equal power, their magnitudes are equal, i.e., ∣s1∣=∣s2∣. Therefore, the inner product x1' * x2​ simplifies to:

x1' * x2 = −∣s2∣^2 + ∣s1∣^2 = 0x1T​x2​= −∣s1∣^2 + ∣s1∣^2 = 0

This shows that the inner product between the encoded symbols transmitted from different antennas in successive time slots is zero, indicating orthogonality.

This orthogonality property allows the receiver to effectively decode the transmitted symbols by taking advantage of the diversity provided by the multiple antennas without interference between symbols transmitted from different antennas.

 

 
 
Fig 1:  BER vs SNR for Alamouti's Precoding Matrix for 2 X 2 MIMO in MATLAB

(Get MATLAB Code for Alamouti's Precoding Matrix for 2 X 2 MIMO in MATLAB)

Also Read about

[1] Alamouti's Precoding Matrix for 2 X 2 MIMO in MATLAB

[2] Theoretical BER vs SNR for Alamouti's Scheme  

[3] MATLAB Code for Multi-User STBC (using Alamouti's Scheme) 

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

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

📘 Overview of BER and SNR 🧮 Online Simulator for BER calculation of m-ary QAM and m-ary PSK 🧮 MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... 📚 Further Reading 📂 View Other Topics on M-ary QAM, M-ary PSK, QPSK ... 🧮 Online Simulator for Constellation Diagram of m-ary QAM 🧮 Online Simulator for Constellation Diagram of m-ary PSK 🧮 MATLAB Code for BER calculation of ASK, FSK, and PSK 🧮 MATLAB Code for BER calculation of Alamouti Scheme 🧮 Different approaches to calculate BER vs SNR 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. BER = (number of bits received in error) / (total number of tran...

Theoretical BER vs SNR for binary ASK, FSK, and PSK with MATLAB Code + Simulator

📘 Overview & Theory 🧮 MATLAB Codes 📚 Further Reading Theoretical BER vs SNR for Amplitude Shift Keying (ASK) The theoretical Bit Error Rate (BER) for binary ASK depends on how binary bits are mapped to signal amplitudes. For typical cases: If bits are mapped to 1 and -1, the BER is: BER = Q(√(2 × SNR)) If bits are mapped to 0 and 1, the BER becomes: BER = Q(√(SNR / 2)) Where: Q(x) is the Q-function: Q(x) = 0.5 × erfc(x / √2) SNR : Signal-to-Noise Ratio N₀ : Noise Power Spectral Density Understanding the Q-Function and BER for ASK Bit '0' transmits noise only Bit '1' transmits signal (1 + noise) Receiver decision threshold is 0.5 BER is given by: P b = Q(0.5 / σ) , where σ = √(N₀ / 2) Using SNR = (0.5)² / N₀, we get: BER = Q(√(SNR / 2)) Theoretical BER vs ...

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator!   Start Simulator for binary ASK Modulation Message Bits (e.g. 1,0,1,0) Carrier Frequency (Hz) Sampling Frequency (Hz) Run Simulation Simulator for binary FSK Modulation Input Bits (e.g. 1,0,1,0) Freq for '1' (Hz) Freq for '0' (Hz) Sampling Rate (Hz) Visualize FSK Signal Simulator for BPSK Modulation ...

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 ...

MATLAB Code for QPSK Modulation and Demodulation

📘 Overview 🧮 MATLAB Codes 🧮 Theory 🧮 BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc 📚 Further Reading   Quadrature Phase Shift Keying (QPSK) is a digital modulation scheme that conveys two bits per symbol by changing the phase of the carrier signal. Each pair of bits is mapped to one of four possible phase shifts: 0°, 90°, 180°, or 270° 00  ===> 0 degree phase shift of carrier signal 01  ===> 90 degree 11  ===> 180 degree 10  ===> 270 degree   MATLAB Script clc; clear all; close all; clc; M = 4; data = randi([0 (M-1)], 1000, 1); Phase = 0; modData=pskmod(data,M,Phase); figure(1); scatterplot(modData); channelAWGN = 15; rxData2 = awgn(modData, channelAWGN); figure(2); scatterplot(rxData2); demodData = pskdemod(rxData2,M,Phase);   Result data 1 0 2 2 0 2 1 . . . modData -1.00000000000000 + 1.22464679914735e-16i -1.83697019872103e-16 - 1.000000000000...

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...(with Online Simulator)

🧮 MATLAB Code for BPSK, M-ary PSK, and M-ary QAM Together 🧮 MATLAB Code for M-ary QAM 🧮 MATLAB Code for M-ary PSK 📚 Further Reading MATLAB Script for BER vs. SNR for M-QAM, M-PSK, QPSK, BPSK % Written by Salim Wireless clc; clear; close all; num_symbols = 1e5; snr_db = -20:2:20; psk_orders = [2, 4, 8, 16, 32]; qam_orders = [4, 16, 64, 256]; ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); for i = 1:length(psk_orders) psk_order = psk_orders(i); for j = 1:length(snr_db) data_symbols = randi([0, psk_order-1], 1, num_symbols); modulated_signal = pskmod(data_symbols, psk_order, pi/psk_order); received_signal = awgn(modulated_signal, snr_db(j), 'measured'); demodulated_symbols = pskdemod(received_signal, psk_order, pi/psk_order); ber_psk_results(i, j) = sum(data_symbols ~= demodulated_symbols) / num_symbols; end end for i...

MATLAB code for Pulse Code Modulation (PCM) and Demodulation

📘 Overview & Theory 🧮 Quantization in Pulse Code Modulation (PCM) 🧮 MATLAB Code for Pulse Code Modulation (PCM) 🧮 MATLAB Code for Pulse Amplitude Modulation and Demodulation of Digital data 🧮 Other Pulse Modulation Techniques (e.g., PWM, PPM, DM, and PCM) 📚 Further Reading MATLAB Code for Pulse Code Modulation clc; close all; clear all; fm=input('Enter the message frequency (in Hz): '); fs=input('Enter the sampling frequency (in Hz): '); L=input('Enter the number of the quantization levels: '); n = log2(L); t=0:1/fs:1; % fs nuber of samples have tobe selected s=8*sin(2*pi*fm*t); subplot(3,1,1); t=0:1/(length(s)-1):1; plot(t,s); title('Analog Signal'); ylabel('Amplitude--->'); xlabel('Time--->'); subplot(3,1,2); stem(t,s);grid on; title('Sampled Sinal'); ylabel('Amplitude--->'); xlabel('Time--->'); % Quantization Process vmax=8; vmin=-vmax; %to quanti...

MATLAB Code for ASK, FSK, and PSK (with Online Simulator)

📘 Overview & Theory 🧮 MATLAB Code for ASK 🧮 MATLAB Code for FSK 🧮 MATLAB Code for PSK 🧮 Simulator for binary ASK, FSK, and PSK Modulations 📚 Further Reading ASK, FSK & PSK HomePage MATLAB Code MATLAB Code for ASK Modulation and Demodulation % The code is written by SalimWireless.Com % Clear previous data and plots clc; clear all; close all; % Parameters Tb = 1; % Bit duration (s) fc = 10; % Carrier frequency (Hz) N_bits = 10; % Number of bits Fs = 100 * fc; % Sampling frequency (ensure at least 2*fc, more for better representation) Ts = 1/Fs; % Sampling interval samples_per_bit = Fs * Tb; % Number of samples per bit duration % Generate random binary data rng(10); % Set random seed for reproducibility binary_data = randi([0, 1], 1, N_bits); % Generate random binary data (0 or 1) % Initialize arrays for continuous signals t_overall = 0:Ts:(N_bits...