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) 



Contact Us

Name

Email *

Message *

Popular Posts

Design of CMOS Flip-Flops (SR, D, JK)

Design of CMOS Flip-Flops (SR, D, JK) A flip-flop or latch is a circuit with two stable states, used to store state information. It is the basic storage element in sequential logic and a fundamental building block in digital electronics systems, including computers and communication devices. Flip-flops and latches act as data storage elements for states, pulse counting, and synchronization of variably-timed input signals to a reference clock. Flip-flops can be transparent/opaque (latches) or clocked (synchronous, edge-triggered). Latches are level-sensitive, while flip-flops are edge-sensitive. In sequential logic, the output depends on current inputs and previous states. Fig.1 shows a sequential circuit combining a combinational block and a memory element. ...

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 The Role of the Q-function in BER vs. SNR The Q-function is the standard tool for calculating BER in systems like BPSK or QPSK over AWGN (Additive White Gaussian Noise) channels. For BPSK: In BPSK, we transmit +√E b (bit 1) and -√E b (bit 0). The decision boundary is set at 0 . If -√E b was sent, an error occurs if noise r > √...

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 Calculation 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 figur...

Channel Impulse Response (CIR) (with MATLAB + Simulator)

📘 Overview & Theory 📘 How CIR Affects the Signal 🧮 Online Channel Impulse Response Simulator 🧮 MATLAB Codes 📚 Further Reading What is the Channel Impulse Response (CIR)? 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. 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. Fig: Dirac Delta Function The result of this calculation is that all frequencies are responded to equally by δ(t) . This is crucial since we never know which frequenci...

FFT Butterfly Method Explained (with Simulations)

4-Point FFT Using Butterfly Method Given: x[n] = {0, 1, 2, 3} Step 1: Split into Even & Odd Even indices: x e = {x[0], x[2]} = {0, 2} Odd indices: x o = {x[1], x[3]} = {1, 3} Step 2: 2-point DFT For any {a, b}: DFT = {a + b, a - b} Even Part (E): {0+2, 0-2} = {2, -2} Odd Part (O): {1+3, 1-3} = {4, -2} Step 3: Combine Using Butterfly X[k] = E[k] + W 4 k O[k] X[k + 2] = E[k] - W 4 k O[k] Twiddle Factors (N=4): W 4 0 = 1, W 4 1 = -j Final Calculations: X[0] = E[0] + W 4 0 O[0] = 2 + (1)(4) = 6 X[2] = E[0] - W 4 0 O[0] = 2 - (1)(4) = -2 X[1] = E[1] + W 4 1 O[1] = -2 + (-j)(-2) = -2 + 2j X[3] = E[1] - W 4 1 O[1] = -2 - (-j)(-2) = -2 - 2j Final Answer: X[k] = {6, -2 + 2j, -2, -2 - 2j} 8-Point FFT Using Butterfly Method Given: x[n] = {0,1,2,3,4,5,6,7} Step 1: Split into Bit-Reversed Order To perform DIT-FFT, split the 8 points into pairs of two: Group A: {x[0], x[4]} = {0, 4}...

Frequency Bands : EHF, SHF, UHF, VHF, HF, MF, LF, VLF and Their Uses

Frequency Bands >> EHF, SHF, UHF, VHF, HF, MF, LF... Frequency Bands and Their Uses 1. Extremely High Frequency (EHF) 30 - 300 GHz Uses 5G Networks 5G millimeter wave band 6G and beyond (Experimental) RADAR 2. Super High Frequency (SHF) 3 - 30 GHz Uses Ultra-wideband (UWB) Airborne RADAR Satellite Communication Microwave Link Communication or SATCOM 3. Ultra High Frequency (UHF) 300 - 3000 MHz Uses Satellite Communication Television Surveillance Navigation aids Also, read important wireless communication terms 4....

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 ) ...

Pulse Amplitude Modulation and Demodulation

📘 Overview & Theory of Pulse Amplitude Moduation (PAM) 🧮 Pulse Amplitude Demoduation 🧮 MATLAB Code for PAM 📚 Further Reading 📂 Other Topics on Pulse Amplitude Modulation ... 🧮 Simulation results for comparison of PAM, PWM, PPM, DM, and PCM 🧮 Other Pulse Modulation Techniques (e.g., PWM, PPM, DM, and PCM) 🧮 MATLAB Code for Pulse Amplitude Modulation and Demodulation of an Analog Signal (2) 🧮 MATLAB Code for Pulse Amplitude Modulation and Demodulation of Digital data  Pulse Amplitude Modulation (PAM) Sampling allow us to represent real world continuous signal, such as audio or video, in a format suitable for digital processing and storage. This sampled discrete-time signal is inherently digital. A digital signal is a discrete-time signal that is further quantized in amplitude. Pulse Amplitude modulation (PAM) is the modulation technique in which amplitude of carrier pulses is...