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Evaluation criteria for optical OFDM signals
The quality of optical signals is a very important parameter in optical communications. Several metrics are in common use, like optical signal-to-noise power ratio (OSNR), Q-factor, error vector magnitude (EVM) and bit error rate (BER). In this work we have used two metrics in order to evaluate the signal quality, bit error rate (BER), and error vector magnitude (EVM).
Error vector magnitude (EVM)
Measuring the EVM provides important information on the performance of transmitters and receivers in digital communications. The EVM can determine the type of damage present in a signal and helps to identify their source. EVM is the accumulation of a given vector differences between the ideal reference signal and the measured time signal. It is set to N symbols mean squared error ⃗ and normalized to unity by | ⃗ | where | ⃗ | is the magnitude of the vector reference signal (Figure 1- 11) and is usually expressed in % rms (root mean square).
Bit error rate (BER)
In digital transmission, the number of bit errors is the number of received bits of a datastream over a communication channel that have been altered due to noise, interference, distortion or bit synchronization errors. The bit error rate (BER) is the number of bit errors divided by the total number of transferred bits. The relationship between BER, EVM and M-QAM modulation format for AWGN channel is given by [32]. In our work we consider our results valid if we have BER = × − which can be corrected by forward error correction (FEC) techniques. This BER value corresponds to the EVM values seen in Table 1 according to Figure 1- 12.
Optical transmitter devices
The role of the optical transmitter is to convert an electrical input signal into the corresponding optical signal and then launch it into the optical fiber serving as a communication channel. The major component of an optical transmitter is an optical source. Fiber optic communication systems employ semiconductor optical sources such as semiconductor lasers [1]. Semiconductor lasers are of different types (Fabry Perot (FP) lasers, distributed feedback (DFB) lasers, vertical cavity surface emitting lasers, etc…).
DFB lasers
Distributed feedback (DFB) semiconductor lasers were developed during the 1λ80’s and are used routinely for WDM lightwave systems. Despite the technological complexities, DFB lasers are routinely produced commercially, they are nearly used in all 1.55 m systems operating at bit rates of 2.5 Gb/s or more. DFB lasers are reliable enough that they have been used since 1992 in all transoceanic lightwave systems [1]. The optical signal output from a semiconductor laser in continuous wave (CW) mode shows fluctuations in intensity, phase, and frequency. The intensity fluctuation results in a limited signal to noise ratio (SNR), while the phase fluctuation leads to a nonzero spectral linewidth Δ. The relative intensity noise (RIN) often expressed in dB/Hz is defined as the ratio between the average of the density of the spectrum of optical intensity fluctuations and the square of the instantaneous optical intensity.
Optical fiber channel
At the heart of the optical communication systems, optical fibers are used as the transmission channel. An optical fiber consists of a cylindrical central core of silica surrounded by a cladding having a refractive index ng slightly lower than that of the core material. The light is confined in the core by the phenomenon of total reflection. There are two main types of optical fibers used in communication systems: multimode fibers (MMFs) and single mode fibers (SMFs). Multimode fibers are still used for local area networks (short distances) and single mode fibers (SMFs) for access/metropolitan/core network applications. The main benefits of fibers are their large transmission capacity, low weight, very low attenuation and immunity to electromagnetic interference. Despite its advantages, there remain constraints that impose a compromise between speed and distance such as losses in the line (link power budget), the chromatic dispersion, polarization mode dispersion and fiber nonlinear effects. We briefly explain each of these phenomenas.
Fiber losses
The optical signal that is propagating through an optical fiber suffers from attenuation. The optical signal attenuation is a very important factor since a minimum optical signal level must be present at the receiver so as to be properly detected. The attenuation of an optical signal is generally expressed in dB/km using the following relationship: Fiber losses depend on the wavelength of transmitted light. Figure 1- 18 shows the loss spectrum α() of a single-mode fiber made in 1979 [1]. The fiber exhibited a loss of only about 0.2 dB/km in the wavelength region near 1.55 m, the lowest value first realized in 1979. This value is close to the fundamental limit of about 0.16 dB/km for silica fibers [1]. The loss spectrum exhibits a strong peak near 1.39 m and several other smaller peaks. A secondary minimum is found to occur near 1.3 m, where the fiber loss is below 0.5 dB/km. Since fiber dispersion is also minimum near 1.3 m, this low-loss window was used for secondgeneration lightwave systems. Fiber losses are considerably higher for shorter wavelengths and exceeds 5 dB/km in the visible region, making it unsuitable for long-haul transmission. Several factors contribute to overall losses; their relative contributions are also shown in Figure 1- 18. The two most important among them are material absorption and Rayleigh scattering.
Chromatic Dispersion
The main advantage of single-mode fibers is that intermodal dispersion is absent simply because the energy of the injected pulse is transported by a single mode. However, pulse broadening does not disappear altogether. The group velocity associated with the fundamental mode is frequency dependent because of chromatic dispersion. As a result, different spectral components of the pulse travel at slightly different group velocities, a phenomenon referred to as group-velocity dispersion (GVD), intramodal dispersion, or simply fiber dispersion [1]. Intramodal dispersion has two contributions, material dispersion and waveguide dispersion. This causes intersymbol interference which results in an increase of the bit error rate (BER) of the communication system.
Table of contents :
RÉSUMÉ
EVOLUTION DES RESEAUX OPTIQUES
CHAPITRE 2 : MODELISATION ET VALIDATION EXPERIMENTALE D’UN RSOA
PLATEFORME DE CO-SIMULATION POUR LA SIMULATION IMDD OFDM
DISPOSITIF EXPERIMENTAL OFDM IMDD
CHAPITRE 4 : ETUDE THEORIQUE ET NUMERIQUE D’UN SYSTEME DE TRANSMISSION D’AMOOFDM IMDD
UTILISANT DIFFERENTES STRUCTURES DE SOA
INTRODUCTION
1 OVERVIEW ON IMDD-OOFDM TRANSMISSION SYSTEMS
1.1 EVOLUTION OF OPTICAL TRANSMISSION SYSTEMS
1.2 ORTHOGONAL FREQUENCY-DIVISION MULTIPLEXING (OFDM)
1.2.1 Evaluation criteria for Optical OFDM signals
1.2.2 Calculation of BER for an OFDM signal
1.3 OPTICAL OFDM IMDD TRANSMISSION SYSTEM
1.3.1 Optical transmitter devices
1.3.2 Optical fiber channel
1.3.3 PIN Photodiode
1.3.4 Analog to Digital Converter (ADC) and Digital to Analog Converter (DAC)
1.4 SEMICONDUCTOR OPTICAL AMPLIFIERS (SOAS)
1.4.1 Semiconductor optical amplifier structure
1.4.2 SOA characteristics
1.5 CONCLUSION
2 WIDEBAND TIME DOMAIN RSOA MODELING AND EXPERIMENTAL VALIDATION
2.1 INTRODUCTION
2.2 WIDEBAND TIME DOMAIN SOA/RSOA FIELD MODEL
2.2.1 Propagation of signals in an optical calculation section
2.2.2 Modelling of amplified spontaneous emission (ASE)
2.2.3 Carrier density evolution in the SOA
2.3 EXPERIMENTAL VALIDATION OF THE RSOA MODEL
2.3.1 Dynamic characterization
2.4 CONCLUSION
3 EXPERIMENTAL AND NUMERICAL ANALYSIS OF AN RSOA AS AN INTENSITY MODULATOR AND AS WAVELENGTH CONVERTER FOR IMDD-OFDM TRANSMISSION SYSTEMS
3.1 INTRODUCTION
3.2 TRANSMISSION LINK MODEL
3.3 CO-SIMULATION PLATFORM
3.4 OFDM IMDD EXPERIMENTAL SETUP
3.5 EXPERIMENTALLY GENERATED OFDM SIGNAL
3.5.1 Back to back fitting for simulation and measurement platforms
3.6 EXPERIMENTAL AND NUMERICAL ANALYSIS OF IMDD OFDM TRANSMISSION PERFORMANCES USING THE
3.6.1 Impact of input power and modulation bandwidth on the transmission performance
3.7 NUMERICAL STUDY OF ENHANCING THE TRANSMISSION PERFORMANCE OF IM-OFDM SYSTEMS USING TWO METHODS (AMOOFDM AND TWO ELECTRODE RSOA)
3.7.1 AMOOFDM transmission performances of the RSOA over 100 nm wavelength range
3.7.2 AMOOFDM transmission performances in a two electrodes RSOA configuration
3.8 WAVELENGTH CONVERSION FUNCTION OF AN IM-OFDM FORMAT
3.8.1 OOFDM wavelength conversion co-simulation platform
3.8.2 Wavelength conversion experimental system setup
3.8.3 Experimental and Numerical results with 20 Km SMF
3.9 CONCLUSION
4 THEORETICAL AND NUMERICAL STUDY OF AN AMOOFDM IMDD TRANSMISSION SYSTEM USING DIFFERENT SOA STRUCTURES
4.1 INTRODUCTION
4.2 TRANSMISSION LINK MODEL
4.2.1 SMF model
4.3 AMOOFDM IMDD TRANSMISSION PERFORMANCES OF DIFFERENT SOAS STRUCTURES AND CONFIGURATIONS
4.3.1 AMOOFDM IMDD using DFB laser as intensity modulator
4.3.2 AMOOFDM IMDD using SOA and RSOA as intensity modulators
4.3.3 AMOOFDM IMDD using RSOA
4.4 QUANTUM-DOT SEMICONDUCTOR OPTICAL AMPLIFIER AS INTENSITY MODULATOR FOR OFDM SIGNAL
4.4.1 QD-SOA-IM model
4.4.2 OOFDM system Simulation parameters
4.4.3 QD-SOA simulation parameters
4.4.4 Static and dynamic QD-SOA performances
4.4.5 Simulated system transmission performance using QD-SOA
4.5 TWO ELECTRODE-BASED SOA INTENSITY MODULATORS
4.5.1 SOA-Based Intensity Modulator Model [10]
4.5.2 Simulated transmission performance
4.6 TWO CASCADED SOAS IN A COUNTER PROPAGATING CONFIGURATION
4.6.1 TC-SOA-CC-based intensity modulator models
4.6.2 TC-SOA-CC Simulation parameters
4.6.3 Static characteristics of TC-SOA-CC
4.6.4 Effect of carrier lifetime
4.6.5 Impact of bias current and optical input power on the Transmission performances
4.6.6 Signal line rate versus transmission distance
4.6.7 Impact of negative frequency chirp
4.7 COMPARISON BETWEEN THE THREE SOA STRUCTURES
4.8 CONCLUSION
5 CONCLUSION AND PERSPECTIVE
5.1 CONCLUSION
5.2 PERSPECTIVE AND FUTURE WORK
GLOSSARY
REFERENCES
