Skip to main content

MATLAB Guide: Modeling UVLC Capacity Lower Bounds


MATLAB Guide: Modeling UVLC Capacity Lower Bounds

UVLC Capacity

Calculating the point-to-point capacity of an underwater optical link requires modeling Gaussian noise and water attenuation (Beer-Lambert Law).

1. The Capacity Lower Bound Formula

C_LB = h(X) + ln(Hc) - f(rho) - h(Y|X)

Breaking Down the Symbols

This equation is essentially a "Data Budget." You start with a total amount of information and subtract everything that ruins it along the way.

h(X)
The Volume of your Shout (Input Entropy)
This is the total information you are trying to send. A "louder" signal with more variety allows for more data.
ln(Hc)
The Fog Tax (Channel Loss)
Water isn't clear. It absorbs light. This term is a "tax" you pay to the ocean. The murkier the water, the more data you lose here.
AD UNIT: In-Article Native
f(ρ)
The LED Penalty (Constraints)
Unlike a radio, an LED cannot have "negative light." It's either on or off. This mathematical penalty accounts for the physical limits of using light bulbs to send data.
h(Y|X)
The Background Splashing (Noise)
This is the "static" in the water—sunlight, heat, or electronic interference. If the splashing is too loud, the message gets garbled.

Why Does This Matter?

Engineers use this formula to build Autonomous Underwater Vehicles (AUVs). By solving this equation, they can predict exactly how far a robot can swim away from its base before the "Underwater Wi-Fi" cuts out.

If the result (CLB) is high, you can stream 4K video from the ocean floor. If it's low, you might only be able to send a simple text message.

2. Implementation Snippet

Use the following MATLAB function to solve for the Lagrange multiplier (λ*) in Case I distributions:

function lambda = solve_lambda()
    % Solves for input optimization
    fun = @(x) 1 - (1./x - exp(-x)./(1-exp(-x)));
    lambda = fzero(fun, 1);
end

3. Visualizing Results

To plot the OSNR (Optical Signal-to-Noise Ratio) against capacity in nats/Hz, you must account for different extinction coefficients (c):

  • Clear Ocean: c = 0.151
  • Coastal Water: c = 0.305
  • Turbid Harbor: c = 2.17

This code allows engineers to predict link performance before deploying expensive underwater AUVs.

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

How to use MATLAB Simulink

Introduction to MATLAB Simulink MATLAB Simulink is a popular add-on of MATLAB. Here, you can use different blocks like modulator, demodulator, AWGN channel, etc. And you can do experiments on your own. Steps to Get Started 1. Go to the 'Simulink' tab at the top navbar of MATLAB. If not found, click on the add-on tab, search 'Simulink,' and then click on it to add. 2. Once you installed the simulation, click the 'new' tap at the top left corner. 3. Then, search the required blocks in the 'Simulink library.' Then, drag it to the editor space. 4. You can double-click on the blocks to see the input parameters. 5. Then, connect the blocks by dragging a line from one block's output terminal to another block's input. 6. If the connection is complete, click the 'run' tab in the middle of the top navbar. 7. After clicking on the run ...

OFDM Waveform with MATLAB Code (with Simulator)

  In OFDM (Orthogonal Frequency Division Multiplexing) , we transmit multiple orthogonal subcarriers simultaneously. Since the subcarriers are orthogonal , they do not interfere with each other, which is one of the main advantages of OFDM. Practically, OFDM converts a wideband signal into multiple narrowband orthogonal subcarriers. For typical wireless communication, if the signal bandwidth (or symbol duration) exceeds the coherence bandwidth of the channel, the signal experiences frequency-selective fading . Fading distorts the signal, making it difficult to recover the original information. By using OFDM, we transmit the same wideband signal across multiple orthogonal narrowband subcarriers, reducing the effect of fading. For example, if we want to transmit a signal of bandwidth 1024 kHz , we can divide it into N = 8 subcarriers . Each subcarrier is then spaced by: Δf = Total Bandwidth N = 1024 8 kHz...

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

📘 Overview & Theory 🧮 MATLAB Codes 📚 Further Reading Bit Error Rate (BER) Equations In ASK, noise directly affects the signal amplitude, making it the most vulnerable since the data is carried in amplitude changes. In FSK, data is represented by frequency variations, and because noise typically impacts amplitude more than frequency, FSK is more robust than ASK. In PSK, data is encoded in the signal phase, and BPSK specifically uses 180-degree phase shifts, creating the greatest separation between signal points and therefore achieving the lowest bit error rate (BER) for the same power level. BER formulas for ASK, FSK, and PSK modulation schemes. ASK BER = 0.5 × erfc(0.5 × √SNR) FSK BER = 0.5 × erfc(√(SNR / 2)) PSK BER = 0.5 × erfc(√SNR) erfc / Q-func...

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 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 figure of merit for a...

MATLAB Code for Constellation Diagram of QAM configurations such as 4, 8, 16, 32, 64, 128, and 256-QAM

📘 Overview of QAM 🧮 4-QAM MATLAB 🧮 16-QAM MATLAB 🚀 Online Simulator 📂 Other Topics on Constellation Diagrams... ▼ 🧮 MATLAB Code for 4-QAM 🧮 MATLAB Code for 16-QAM 🧮 MATLAB Code for m-ary QAM 🧮 Simulator for m-ary PSK 🧮 Simulator for m-ary QAM 🧮 Overview of Energy per Bit (Eb / N0) 🧮 Simulator for ASK, FSK, and PSK Overview of QAM One of the best-performing modulation techniques is QAM [↗] . Here, we modulate the symbols by varying the carrier signal's amplitude and phase in response to the variation in the message signal (or voltage variation). So, we may say that QAM is a combination of phase and amplitude modulation. Additionally, it performs better than ASK or PSK [↗] . In fact, any constellation for any type of modulatio...

Theoretical vs. simulated BER vs. SNR for ASK, FSK, and PSK (MATLAB Code + Simulator)

📘 Overview 🧮 Simulator 💻 Theoretical Code 📊 Simulated Code 📚 Resources Overview BER vs. SNR denotes how many bits in error are received for a given signal-to-noise ratio, typically measured in dB. Common noise types in wireless systems: 🚀 1. Additive White Gaussian Noise (AWGN) 🌊 2. Rayleigh Fading AWGN adds random noise; Rayleigh fading attenuates the signal variably. A good SNR helps reduce these effects. Bit Error Rate (BER) Equations BER formulas for ASK, FSK, and PSK modulation schemes. ASK BER = 0.5 × erfc(0.5 × √SNR) FSK BER = 0.5 × erfc(√(SNR / 2)) PSK BER = 0.5 × erfc(√SNR) erfc / Q-function (Click here) Live BER S...

FastAPI Static Files – Overview

FastAPI Static Files Often, a web application needs to include resources that do not change, even when dynamic data is rendered. These resources are called static assets . Examples of static files include: Images ( .png , .jpg ) JavaScript files ( .js ) Stylesheets ( .css ) Installing Required Library To handle static files in FastAPI, you need the aiofiles library. pip install aiofiles Mounting Static Files FastAPI uses the StaticFiles class to serve static content. You mount a folder (usually named static ) so that all files inside it can be accessed via a URL. from fastapi import FastAPI from fastapi.staticfiles import StaticFiles app = FastAPI() app.mount("/static", StaticFiles(directory="static"), name="static") Example 1: Using an Image Place an image file (for example, fa-logo.png ) inside the static folder. main.py from fastapi import FastAPI, Request from fastapi.responses import HTMLRespon...

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator!   •   Interactive ASK, FSK, and BPSK tools updated for 2025. Start Now Interactive Modulation Simulators Visualize binary modulation techniques (ASK, FSK, BPSK) in real-time with adjustable carrier and sampling parameters. 📡 ASK Simulator 📶 FSK Simulator 🎚️ BPSK Simulator 📚 More Topics ASK Modulator FSK Modulator BPSK Modulator More Topics Simulator for Binary ASK Modulation Digital Message Bits Carrier Freq (Hz) Sampl...