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Maria Juarez
Maria Juarez

Optical Wireless Communications: A Systems Approach with MATLAB Examples



Optical Wireless Communications: System and Channel Modelling with MATLAB




Optical wireless communication (OWC) is a form of data transmission that uses light as the carrier medium. OWC can offer many advantages over conventional radio frequency (RF) communication, such as high bandwidth, low power consumption, immunity to electromagnetic interference, security, and license-free operation. However, OWC also faces some challenges, such as atmospheric turbulence, weather conditions, pointing and alignment errors, background noise, and multipath fading. In this article, we will introduce the basic concepts of OWC, review the main devices and systems used for OWC, discuss the modulation techniques and schemes for OWC, present the channel models and system performance analysis for OWC, explore the emerging applications of OWC, and demonstrate how to use MATLAB for OWC system design and analysis.




optical wireless communications: system and channel modelling with matlab free pdf



Introduction




What is optical wireless communication (OWC)?




Optical wireless communication (OWC) is a form of data transmission that uses light as the carrier medium. Unlike optical fiber communication, which uses guided light waves in a physical medium, OWC uses unguided light waves in free space or air. OWC can be classified into three categories based on the wavelength range of the light source: infrared (IR) communication, visible light communication (VLC), and ultraviolet (UV) communication. IR communication uses wavelengths between 700 nm and 1 mm, VLC uses wavelengths between 380 nm and 780 nm, and UV communication uses wavelengths between 10 nm and 380 nm.


Why is OWC important?




OWC is important because it can offer many advantages over conventional radio frequency (RF) communication, such as:


  • High bandwidth: The optical spectrum is much wider than the RF spectrum, which means that OWC can support higher data rates and more users.



  • Low power consumption: The optical power required for OWC is much lower than the RF power required for RF communication, which means that OWC can save energy and reduce heat generation.



  • Immunity to electromagnetic interference: The optical signals used for OWC are not affected by electromagnetic interference from other sources, which means that OWC can improve signal quality and reliability.



  • Security: The optical signals used for OWC are confined to a narrow beam or a line-of-sight path, which means that OWC can prevent eavesdropping and jamming.



  • License-free operation: The optical spectrum is not regulated by any authority, which means that OWC can avoid spectrum scarcity and licensing fees.



What are the main challenges and opportunities of OWC?




OWC also faces some challenges, such as:


  • Atmospheric turbulence: The optical signals used for OWC can be distorted by the fluctuations of the refractive index of the air, which means that OWC can suffer from signal fading and scintillation.



  • Weather conditions: The optical signals used for OWC can be attenuated by the absorption and scattering of the air molecules, water droplets, dust particles, and fog, which means that OWC can experience signal loss and outage.



  • Pointing and alignment errors: The optical signals used for OWC require precise pointing and alignment between the transmitter and the receiver, which means that OWC can be affected by mechanical vibrations, misalignment, and tracking errors.



  • Background noise: The optical signals used for OWC can be corrupted by the ambient light from the sun, the moon, the stars, and artificial sources, which means that OWC can have a low signal-to-noise ratio (SNR).



  • Multipath fading: The optical signals used for OWC can be reflected by the walls, the ceiling, the floor, and other objects in indoor environments, which means that OWC can encounter multipath interference and inter-symbol interference (ISI).



However, OWC also has some opportunities, such as:


  • New applications: OWC can enable new applications that are not feasible or efficient with RF communication, such as underwater communication, vehicular communication, indoor positioning, illumination and communication integration, and biomedical sensing.



  • New technologies: OWC can benefit from new technologies that can improve the performance and functionality of OWC systems, such as light-emitting diodes (LEDs), laser diodes (LDs), photodiodes (PDs), spatial light modulators (SLMs), beam steering devices, adaptive optics, and optical antennas.



  • New techniques: OWC can adopt new techniques that can enhance the capacity and robustness of OWC systems, such as multiple-input multiple-output (MIMO), orthogonal frequency division multiplexing (OFDM), polarization shift keying (PolSK), spatial modulation (SM), diversity combining, channel coding, equalization, and beamforming.



Devices and Systems for OWC




Optical sources and transmitters




The optical source is the device that generates the optical signal for OWC. The most common types of optical sources are light-emitting diodes (LEDs) and laser diodes (LDs). LEDs are semiconductor devices that emit light when an electric current passes through them. LEDs have low cost, low power consumption, long lifetime, high reliability, and wide wavelength range. However, LEDs also have low modulation bandwidth, low output power, large beam divergence angle, and incoherent emission. LDs are semiconductor devices that emit light when electrons and holes recombine in a p-n junction. LDs have high modulation bandwidth, high output power, small beam divergence angle, and coherent emission. However, LDs also have high cost, high power consumption, short lifetime, low reliability, and narrow wavelength range.


The optical transmitter is the device that modulates the optical signal with the information signal for OWC. The most common type of modulation for OWC is intensity modulation and direct detection (IM/DD), where the intensity of the optical signal is varied according to the information signal. IM/DD is simple to implement and compatible with most optical sources and detectors. However, IM/DD also has some limitations, such as nonlinear distortion, intermodulation interference, DC bias requirement, and sensitivity to background noise.


Optical detectors and receivers




The optical detector is the device that converts the optical signal into an electrical signal for OWC. The most common types of optical detectors are photodiodes (PDs) and avalanche photodiodes (APDs). PDs are semiconductor devices that generate an electric current when light falls on them. PDs have low cost, low noise, high linearity, and wide wavelength range. However, PDs also have low responsivity, low quantum efficiency, and slow response time. APDs are semiconductor devices that amplify the electric current generated by light using an internal avalanche multiplication process. APDs have high responsivity, high quantum efficiency, and fast response time. However, have high cost, high noise, low linearity, and narrow wavelength range.


The optical receiver is the device that demodulates the electrical signal and recovers the information signal for OWC. The most common type of demodulation for OWC is direct detection (DD), where the intensity of the electrical signal is measured by the detector. DD is simple to implement and compatible with most optical sources and detectors. However, DD also has some limitations, such as sensitivity to background noise, signal fading, and shot noise.


Indoor and outdoor environments




The indoor environment is the scenario where OWC is used inside a building or a room. The indoor environment can be divided into two types: diffuse and directed. Diffuse OWC uses a wide beam angle and multiple reflections to cover a large area. Diffuse OWC can provide mobility and flexibility for the users, but it also suffers from multipath interference and inter-symbol interference (ISI). Directed OWC uses a narrow beam angle and a line-of-sight (LOS) path to achieve a high data rate. Directed OWC can provide high performance and security for the users, but it also requires precise pointing and alignment between the transmitter and the receiver.


The outdoor environment is the scenario where OWC is used outside a building or in open space. The outdoor environment can be divided into two types: terrestrial and space. Terrestrial OWC uses a LOS path to communicate between two points on the ground or between a ground station and an aerial platform. Terrestrial OWC can offer high bandwidth and long distance communication, but it also suffers from atmospheric turbulence, weather conditions, and pointing and alignment errors. Space OWC uses a LOS path to communicate between two satellites or between a satellite and a ground station. Space OWC can provide global coverage and low latency communication, but it also faces challenges such as orbital dynamics, solar radiation, and thermal effects.


Modulation Techniques and Schemes for OWC




Intensity modulation and direct detection (IM/DD)




Intensity modulation and direct detection (IM/DD) is the most common type of modulation and demodulation for OWC. IM/DD modulates the intensity of the optical signal according to the information signal, and detects the intensity of the electrical signal to recover the information signal. IM/DD can be implemented using various modulation schemes, such as on-off keying (OOK), pulse position modulation (PPM), pulse width modulation (PWM), pulse amplitude modulation (PAM), and orthogonal frequency division multiplexing (OFDM). IM/DD can also be combined with different coding techniques, such as Manchester coding, differential coding, run-length limited (RLL) coding, and forward error correction (FEC) coding.


Polarization shift keying (PolSK)




Polarization shift keying (PolSK) is a type of modulation that uses the polarization state of the optical signal to carry information. PolSK modulates the polarization state of the optical signal according to the information signal, and measures the polarization state of the electrical signal to recover the information signal. PolSK can be implemented using various polarization states, such as linear polarization, circular polarization, elliptical polarization, or hybrid polarization. PolSK can also be combined with different modulation schemes, such as binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), or quadrature amplitude modulation (QAM).


Subcarrier modulation (SCM)




Subcarrier modulation (SCM) is a type of modulation that uses a high-frequency carrier signal to modulate the information signal before modulating the optical signal. SCM modulates the information signal onto a subcarrier signal using an RF modulator, and then modulates the subcarrier signal onto the optical signal using an IM/DD modulator. SCM demodulates the optical signal using an IM/DD demodulator, and then demodulates the subcarrier signal using an RF demodulator. SCM can use various subcarrier signals, such as sinusoidal waves, square waves, or sawtooth waves. SCM can also use various modulation schemes for both subcarrier modulation and optical modulation, such as amplitude modulation (AM), frequency modulation (FM), phase modulation (PM), or digital modulation.


Channel Models and System Performance Analysis for OWC




Indoor channel models




The indoor channel model describes the propagation characteristics of the optical signal in an indoor environment. The indoor channel model can be divided into two types: diffuse channel model and directed channel model. The diffuse channel model considers the multiple reflections of the optical signal from the walls, the ceiling, the floor, and other objects in the room. The diffuse channel model can be described by a Lambertian model, a double-Lambertian model, or a composite model. The directed channel model considers the LOS path of the optical signal between the transmitter and the receiver. The directed channel model can be described by a Gaussian model, a log-normal model, or a gamma-gamma model.


Outdoor channel models




The outdoor channel model describes the propagation characteristics of the optical signal in an outdoor environment. The outdoor channel model can be divided into two types: terrestrial channel model and space channel model. The terrestrial channel model considers the atmospheric effects on the optical signal, such as absorption, scattering, turbulence, and weather conditions. The terrestrial channel model can be described by a Beer-Lambert model, a Mie scattering model, a Kolmogorov turbulence model, or a Hufnagel-Valley model. The space channel model considers the space effects on the optical signal, such as orbital dynamics, solar radiation, and thermal effects. The space channel model can be described by a Keplerian orbit model, a solar irradiance model, or a thermal noise model.


Mitigation techniques for channel impairments




The mitigation techniques for channel impairments are methods that can improve the performance and reliability of OWC systems in the presence of channel impairments. The mitigation techniques for channel impairments can be divided into two types: physical layer techniques and link layer techniques. The physical layer techniques are methods that operate at the physical layer of the OWC system, such as adaptive optics, diversity combining, equalization, and beamforming. The link layer techniques are methods that operate at the link layer of the OWC system, such as retransmission, interleaving, coding, and routing.


Emerging Applications of OWC




Visible light communication (VLC)




VLC also faces some challenges, such as limited coverage, interference from ambient light, eye safety, and mobility.


Terrestrial free space optics (FSO) communication




Terrestrial free space optics (FSO) communication is a type of OWC that uses infrared or visible light as the carrier medium. FSO communication can use LDs as optical sources, and PDs or APDs as optical detectors. FSO communication can provide high bandwidth and long distance communication between two points on the ground or between a ground station and an aerial platform, such as a drone, a balloon, or a helicopter. FSO communication can also provide security, license-free operation, and easy deployment. However, FSO communication also suffers from atmospheric turbulence, weather conditions, and pointing and alignment errors.


Infrared (IR) communication




Infrared (IR) communication is a type of OWC that uses infrared light as the carrier medium. IR communication can use LEDs or LDs as optical sources, and PDs or APDs as optical detectors. IR communication can provide short-range and low-power communication for indoor applications such as remote control, wireless keyboard, wireless mouse, and wireless headset. IR communication can also provide security and immunity to electromagnetic interference. However, IR communication also has some limitations, such as low data rate, narrow bandwidth, and sensitivity to ambient light.


MATLAB Simulations and Codes for OWC




How to use MATLAB for OWC system design and analysis




MATLAB is a software tool that can be used for OWC system design and analysis. MATLAB can perform various tasks for OWC system design and analysis, such as:


  • Data generation: MATLAB can generate different types of data for OWC systems, such as random binary data, text data, image data, audio data, or video data.



  • Signal processing: MATLAB can perform different types of signal processing for OWC systems, such as modulation, demodulation, coding, decoding, filtering, equalization, or beamforming.



  • Channel modeling: MATLAB can model different types of channels for OWC systems, such as indoor channel models, outdoor channel models, or atmospheric channel models.



  • Performance evaluation: MATLAB can evaluate different performance metrics for OWC systems, such as bit error rate (BER), signal-to-noise ratio (SNR), channel capacity, outage probability, or diversity gain.



  • Visualization: MATLAB can visualize different aspects of OWC systems, such as signal waveforms, constellation diagrams, spectra, or eye diagrams.



Examples of MATLAB simulations and codes for OWC




To illustrate how to use MATLAB for OWC system design and analysis, we will show some examples of MATLAB simulations and codes for OWC. The MATLAB simulations and codes are based on the book Optical Wireless Communications: System and Channel Modelling with MATLAB by Zabih Ghassemlooy, Wasiu Popoola, and Sujan Rajbhandari. The book covers the theory and technology of OWC systems in a comprehensive way, and provides MATLAB simulations and codes for each chapter. The book also includes a CD-ROM that contains all the MATLAB simulations and codes, as well as additional materials such as PowerPoint slides, video clips, and web links.


The following are some examples of MATLAB simulations and codes for OWC:


- Example 1: IM/DD modulation and demodulation with OOK scheme ```matlab % IM/DD modulation and demodulation with OOK scheme % Based on Chapter 4 of Optical Wireless Communications: System % and Channel Modelling with MATLAB by Z. Ghassemlooy et al. clear all; close all; clc; % Parameters N = 1000; % number of bits Rb = 1e6; % bit rate (bps) Tb = 1/Rb; % bit duration (s) fs = 10*Rb; % sampling frequency (Hz) Ts = 1/fs; % sampling period (s) t = 0:Ts:(N*Tb)-Ts; % time vector Pt = 1; % average transmitted power (W) SNRdB = 10; % SNR in dB SNR = 10^(SNRdB/10); % SNR in linear scale Pn = Pt/SNR; % noise power (W) sigma = sqrt(Pn/2); % noise standard deviation (W) % Data generation data = randi([0 1],1,N); % random binary data data_nrz = 2*data-1; % NRZ encoding % Modulation x = rectpulse(data_nrz,fs*Rb); % OOK modulation x = x.*sqrt(Pt); % scaling by power % Channel y = x; % ideal channel (no noise or distortion) % Demodulation z = y.*sqrt(Pt); % scaling by power z = intdump(z,fs*Rb); % integrate and dump z = z>0.5; % decision % Performance evaluation BER = sum(xor(data,z))/N; % bit error rate disp(['Bit error rate = ' num2str(BER)]); % Visualization figure; subplot(3,1,1); stairs([0:N-1]*Tb,data,'linewidth',2); axis([0 N*Tb -0.5 1.5]); xlabel('Time (s)'); ylabel('Data'); title('Transmitted data'); subplot(3,1,2); plot(t,x,'linewidth',2); axis([0 N*Tb -1.5 1.5]); xlabel('Time (s)'); ylabel('Signal'); title('Modulated signal'); subplot(3,1,3); stairs([0:N-1]*Tb,z,'linewidth',2); axis([0 N*Tb -0.5 1.5]); xlabel('Time (s)'); ylabel('Data'); title('Demodulated data'); ``` - Example 2: Indoor diffuse channel model with Lambertian model ```matlab % Indoor diffuse channel model with Lambertian model % Based on Chapter 6 of Optical Wireless Communications: System % and Channel Modelling with MATLAB by Z. Ghassemlooy et al. clear all; close all; clc; % Parameters m = -log10(2)/log10(cosd(60)); % Lambertian order for 120 degree LED Ts = 1e-6; % sampling period (s) L = 5; % room length (m) W = 5; % room width (m) Hr = 2; % receiver height (m) Ht = 3; % transmitter height (m) n = 1.5; % refractive index of the lens FOV = 60; % field of view of the receiver (degree) G_Con = n^2/(sind(FOV))^2; % concentrator gain Adet = 1e-4; % detector physical area (m^2) Rd = 0.5; % responsivity of the detector (A/W) P_total = 20e-3; % total transmitted power (W) N_led_x = 4; % number of LEDs in x direction N_led_y = 4; % number of LEDs in y direction delta_x = L/(N_led_x+1); % spacing between LEDs in x d


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