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Intensity modulation technologies
The throughput of an optical communication system explicitly depends on the speed of optoelectronic components including modulator and detector. Hence, it is important for a system designer to consider practical aspects of each of these components. Optical modulation technology in general and intensity modulation technology in particular make use of three basic components: DML, EAM and March-Zehnder Modulator (MZM).
Directly Modulated Lasers
The simplest way to imprint information into optical intensity is using a DML. In this technique, the laser input current is driven by an electrical signal. In linear regime, the output optical intensity is proportional to the driving signal. Hence, if transmitted data is modulated onto the laser driving current, the information is transformed into the intensity of an optical carrier, which propagates through a fiber link to the receiver. One of the most naive modulation techniques simply involves switching on and off the laser according to a binary data bit pattern. The resulting modulation waveform is Non Return-to-Zero (NRZ) which is widely used in optical access and metropolitan networks [6]. Due to their compactness and low cost, compact DML-based transponders are available with modulation speed up to 10 Giga-Bit Per Second (Gb/s). The principal limitations of DMLs are small extinction ratio, which is in the order of 10 dB, and inherent chirp, because of which a residual phase modulation accompanies the desired intensity modulation. The small extinction ratio limits the maximum achievable Signal-to-Noise Ratio (SNR) on the receiver side. The inherent laser chirp broadens the transmitted signal bandwidth, resulting in inter-channel interference in Dense Wavelength Division Multiplexing (DWDM) systems.
Electroabsorption Modulators
Unlike DMLs where a modulation of laser carrier density results in a modulated output photon density, EAMs work on the absorption principle. An EAM is composed of an active region sandwiched between a p-doped and an n-doped layer. When a bias voltage is applied across the p-n junction, the bandgap of the active region is changed. This phenomenon is known as Franz-Keldysh effect. When the bias voltage is small, the bandgap is wide enough so that the device is transparent to the laser light. However, when the bias voltage increases, the bandgap is reduced such that the active region begins to absorb the laser light. The transmission function of an EAM is shown in Figure 1.2. In linear regime, the output light intensity has a linear relationship with the input bias voltage, resulting in an intensity modulation of light.
In practice an EAM can be integrated with a Distributed Feedback (DFB) laser, which serves as the CW light source, on the same substrate to form an EML. This compact design reduces the important insertion loss of an EAM device. Similar to DMLs, EMLs are compact and low-cost. They are available with modulation speed up to 80 Gb/s. The device also produces some residual chirp and the extinction ratio is in the order of 10 dB.
Mach-Zehnder Modulators
Unlike EAMs, which work on absorption principle, MZMs work on the principle of interference. The input optical signal is split into two paths at an input coupler. At the device output, the optical signals are recombined. According to the phase difference between the two optical fields, the recombination can be destructive or constructive, resulting in an intensity modulation. In order to control the phase change of the output optical light, each path (or arm) is equipped with a phase modulator such that the phase shift is linearly proportional to the applied electrical voltage. The transmission function of an MZM is illustrated in Figure 1.2. When compared to DMLs and EMLs, MZMs can be used to create an intensity modulation without generating chirp. MZMs have an excellent extinction ratio which is in the order of 20 dB. For these reasons MZMs are extensively used in optical transmission systems where the data rate exceeds 10 Gb/s. Due to the possibility of independently modulating the optical intensity and phase, MZMs can be used to create many advanced optical modulation formats [7].
Fiber-based optical propagation
The propagation of an optical signal over fibers is an electromagnetic propagation. Hence, like all electromagnetic phenomena, it is governed by Maxwell’s equations. In general, the propagation equations have several solutions corresponding to different modes in a fiber. The number of solutions (or modes) depends on the characteristics of the fiber. For further details of this aspect the reader is invited to read the second chapter in [8]. Nowadays, fiber-based optical communication infrastructures are extensively implemented with Single-Mode Fibers (SMFs). In this type of fiber the propagation equations have only one solution, which is referred to as the central HE11 mode. Because the fiber supports only one mode, the transmission is hence immune to intermodal dispersion. In this thesis the SMF is considered as being the one used in access networks. The propagation of an optical signal in an SMF can be described by the well-known nonlinear Schrödinger (NLS) equation [8], [9]
Table of contents :
Acknowledgment
Abstract
Résumé
List of figures
List of tables
Acronyms
Notation
Introduction and context
Chapter 1 Optical IMDD transmission system and optical channel detriments
1.1. Introduction
1.2. Optical IMDD transmission fundamentals
1.2.1. Intensity modulation technologies
1.2.2. Fiber-based optical propagation
1.2.3. Direct Detection
1.3. Optical channel impairments
1.3.1. Noise sources
1.3.2. Linear impairments of the optical channel
1.3.3. Nonlinear effects of the optical channel
1.4. Conclusion
Chapter 2 Key components in IMDD optical transmissions and numerical modeling
2.1. Introduction
2.2. DML modeling
2.2.1. Laser parasitics
2.2.2. Laser phase noise
2.2.3. Intrinsic laser
2.2.4. Laser parameter extraction results and model validation
2.3. Fiber link modeling – split-step Fourier method
2.4. Photodetector modeling
2.5. Large-signal regime model validation
2.5.1. Experiment set-up
2.5.2. Experimental results and model validation
2.6. Influence of parameter extraction precision on the model
2.7. Conclusion
Chapter 3 Nyquist pulse shaping technique for future PONs
3.1. Introduction
3.2. State-of-the-art equalizer structures
3.2.1. Equivalent discrete channel
3.2.2. Linear equalizers
3.2.3. Non-linear equalizers
3.2.4. Automatic synthesis
3.3. Optical IMDD receiver design
3.3.1. Finite-length fractionally spaced transversal filter
3.3.2. Non-linear receivers
3.4. Performance comparison in optical IMDD transmissions
3.4.1. Simulation parameters and set-up
3.4.2. Optimum number of FSTF and feedback filter taps
3.4.3. Required optical received power versus transmission distance
3.4.4. Required optical received power versus alpha factor
3.5. Conclusion
Chapter 4 DFT-precoded OFDM – a proposed candidate for future PONs
4.1. Introduction
4.2. OFDM modulation
4.2.1. OFDM modulation/demodulation principle
4.2.2. Cyclic prefix – how does it work in an optical IMDD system
4.3. The water-filling optimization
4.4. Levin-Campello discrete bit/power loading
4.4.1. Definitions and notations
4.4.2. Levin-Campello efficientizing algorithm
4.4.3. Levin-Campello rate adaptive algorithm
4.4.4. Levin-Campello margin adaptive algorithm
4.4.5. Levin-Campello bit/power loading for optical IMDD systems
4.5. The proposed rate adaptive precoded OFDM system
4.5.1. Transmission schemes
4.5.2. Theoretical basis
4.5.3. Algorithm description
4.5.4. Model mismatch
4.6. Performance analysis
4.6.1. Simulation setup
4.6.2. Optimum operating parameters of the laser
4.6.3. Power consumption analysis
4.6.4. Reach-versus-data rate performance comparison
4.6.5. Conclusion
4.7. Proposed system versus conventional NRZ system
4.7.1. Tolerance to chromatic dispersion
4.7.2. Tolerance to laser linewidth enhancement factor
4.8. Conclusion
Chapter 5 Proposed OFDM techniques for future PONs
5.1. Introduction
5.2. Peak-to-average power ratio
5.2.1. PAPR of real-valued OFDM signals
5.2.2. Consequences of high PAPR
5.2.3. PAPR reduction techniques
5.2.4. Conclusion
5.3. OFDM timing synchronization
5.3.1. Simulation setup
5.3.2. State-of-the-art preamble-based OFDM synchronization techniques
5.3.3. Proposed timing synchronization methods
5.3.4. Performance analysis
5.3.5. Conclusion
5.4. Conclusion
Conclusion
Contributions
Appendix A Recursive computation of the proposed synchronization technique
Appendix B Channel estimation techniques
References
