Performance Analysis of MISO Multi-hop Over Log-normal Channels 

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Indoor wireless optical communications

Indoor wireless optical communication can be classied into infrared and visible light communications (VLC). VLC has great attention nowadays due to its ability to communicate and illuminate simultaneously. White illumination using light-emitting diodes (LEDs) is preferred for VLC, due to their long lifetimes and energy eciencies (at least 10 times greater than incandescent bulbs). In addition, by as early as 2018, majority of lighting installations are expected to be LED-based. This green technology can be used in places where radio frequency (RF) is prevented such as hospitals and airplanes [22, 23].
Moreover, it can be used for positioning of mobile devices in indoor environments as supermarkets, shopping malls, and museums (using the camera sensor as the receiver). The market for mobile indoor positioning in the retail sector is expected to reach $5 billion by 2018 [24]. Also, sale navigation using VLC technology [25] is very interesting application as depicted in Figure 2.2. In addition, VLC can be used for smart automotive lighting using the already existing LEDs in the car to decrease the percentage of accidents [26].
In September 2011, IEEE ratied 802.15.7, a wireless personal area network standard for VLC at data rates ranging from 11 kbps to 96 Mbps [25]. VLC faces a lot of challenges such as increasing the temperature which reduces the LEDs lifetime, dimming of the light source for low data rates, path loss attenuation, sunlight and articial light eects, uctuation of the brightness of light and eye constrains safety and incorrect detection of LED color [27]. Dierent potential solutions are proposed in the literature to mitigate these challenges such as special lters for uctuation of the brightness of the light, advanced modulation techniques for dimming of the light source and feedback correction for the incorrect detection of LED color [27]. High eciency LEDs named organic light emitting diodes (OLEDs), contains multi- lms such as carbon and hydrogen between two conductors, has been introduced since 1990 [28]. The advantages of OLEDs are low cost, no restriction on size, bright, power ecient and light weight. However, OLEDs have many challenges such as degradation of the organic layer and OLEDs have a capacitor-like behavior so huge bandwidth require small photoactive area while small OLEDs does not support the required illumination. These challenges limit the data rate being in the range of 2.7 Mbps [29]. Finally, OLEDs for VLC still needs a lot of developments to be commercialized.

Underwater wireless optical communications

Recently, wireless optical communication has been deployed for underwater robot [30], see Figure 2.3. LEDs are preferred than laser for robot communications as LEDs have a small size and low price. The authors achieved 20-30 meters propagation distance with average power consumption of 500 mW. The interesting thing is the cost of wireless optical communication devices is only 70 dollars. Dierent data rates between 9600 bps to 38400 bps were carried out to ensure the reliability of the system.

Space wireless optical communications

NASA employed wireless optical communications link between Moon and Earth for a propagation distance of 384600 km at 622 Mbps [31]. German Space Agency, named DLR-Space, employed wireless optical communications link between two low Earth orbit (LEO) satellites (TerraSAR-X and NFIRE) see Figure 2.4. This link is considered the rst coherent link for wireless optical satellite communication with BPSK and homodyne detection for about 8000 km and 5.6 Gbps is achieved [32].

Free-space optical communications

FSO communications or outdoor wireless optical usually referred to wireless optical communications among buildings see Figure 2.5. In this thesis, we focus on FSO using lasers.

Coherent and non-coherent detection

FSO systems use coherent or non-coherent. In coherent systems, the information is encoded by the optical amplitude, frequency, or phase modulation. At the receiver side, the received eld is optically mixed with a locally generated optical eld. In noncoherent systems, intensity modulation 1 of the emitted light is employed to convey the information. At the receiver side, the photo-detector directly detects changes in light intensity without the need for a local oscillator. These systems are also known as intensity modulation and direct detection (IM/DD) systems.

Energy and spectral eciencies

There are two important factors relative to the choice of a modulation scheme as energy eciency and spectral eciency. Energy eciency refers to the minimum bit error rate (BER) at a target data rate for a given transmit energy irrespectively of the occupied bandwidth. However, it does not take into account the implementation complexity. Spectral eciency, on the other hand, refers to the information transmission rate for a given bandwidth without taking the required transmit energy into account [2, 49].

Modulations suitable for IM/DD systems

On-o keying (OOK), a binary level modulation scheme, is the most commonly used IM technique due to its simple implementation. In OOK signaling, modulated data is represented by the presence (on) or absence (o) of a light pulse in each symbol interval. At the receiver side and for an optimal signal detection, the instantaneous channel fading coecient should be estimated to perform dynamic thresholding [49]. In addition, OOK has relatively poor energy and spectral eciency [50]. Another modulation technique is the pulse position modulation (PPM), which is an energy ecient modulation technique that does not require dynamic thresholds for optimal detection compared with OOK [51].
In comparison with PPM, multiple PPM (MPPM) is proposed in [52] to achieve a higher spectral eciency at the expense of demodulation complexity. It is important to note that although optical communications have a large bandwidth and high spectral eciency modulation, it requires high-speed electronic circuits which are dicult to be designed and implemented. Under the constraint on peak transmiting power, MPPM outperforms PPM in signal-to-noise ratio (SNR) gain [51, 53]. Compared with PPM, pulse width modulation (PWM) has higher spectral eciency at the expense of higher average power requirements [54].
Digital pulse interval modulation (DPIM) sends a pulse followed by a number of empty slots which depends on the information bits. To avoid the problem of consecutive on pulses, an additional guard slot is added to each symbol. The major drawback of DPIM is the inferior error performance compared with PPM and MPPM as they require symbol synchronization [55]. Other modulation techniques based on PWM and PPM are dierential PPM (DPPM) and pulse-position-pulse-width modulation (PPMPWM). In DPPM, the slots after the on pulse are discarded so every DPPM symbol ends with a pulse which decreases the complexity of the synchronization at the receiver. Discarding the empty slots improves the spectral eciency of the system. However, variable rate encoding and decoding have practical drawbacks [56, 57]. In PPMPWM, the energy eciency and the spectral eciency are in mid-way between PWM and PPM [54]. Multiple pulse amplitude modulation (M-PAM) can be used in FSO to obtain high spectral eciency compared with OOK at the expense of energy eciency and system complexity as it requires a laser with variable emission intensity [58].

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Subcarrier intensity modulation

In subcarrier intensity modulation (SIM), the data is rst modulated onto a RF signal then the signal is transmitted using the IM of an optical source. The concept of the SIM is to transmit parallel data streams through a number of non-orthogonal overlapping subcarriers [59]. Compared with coherent modulation at the same spectral eciency, SIM has cost eective implementation at the expense of energy eciency as a result of DC bias added to the signal to avoid negative amplitudes [2, 59]. The DC bias problem can be decreased by using a variable bias for each symbol [60].

Polarization modulation

Polarization modulation (PM) encodes the information as dierent states of the polarization of the laser source by an external modulator. At the receiver, based on the extraction of stoke parameters of received light, the signal can be recovered. PM has high mitigation to atmospheric turbulence as the polarization states are less aected by atmospheric turbulence compared with amplitude and phase. Moreover, PM has a high immunity to the phase noise and non-linearity of lasers. This advantage makes it a perfect solution for long-range FSO applications. However, PM requires perfect transmitter-receiver polarization alignment [61, 62, 63].

Table of contents :

List of Figures
List of Tables
Mathematical Notation
1 Introduction 
1.1 Background
1.2 Thesis Contributions
1.3 Thesis Organization
2 State of the Art 
2.1 Introduction
2.2 Key Technologies
2.2.1 Indoor wireless optical communications
2.2.2 Underwater wireless optical communications
2.2.3 Space wireless optical communications
2.2.4 Free-space optical communications
2.3 Motivation
2.4 Major Challenges
2.4.1 Geometric loss
2.4.2 Misalignment loss
2.4.3 Weather attenuation loss
2.4.4 Background noise
2.4.5 Atmospheric turbulence
2.5 Atmospheric Turbulence Channels
2.5.1 Experimental results
2.5.2 Simulation results
2.5.3 Proposed analytical models
2.6 Suggested Solutions
2.6.1 Modulation techniques Coherent and non-coherent detection Energy and spectral eciencies Modulations suitable for IM/DD systems Subcarrier intensity modulation Polarization modulation Coherent modulation
2.6.2 Forward error correction techniques Reed-Solomon (RS) codes Concatenated Reed-Solomon codes Turbo codes and low-density parity-check codes FEC drawbacks for FSO
2.6.3 Aperture averaging
2.6.4 Spatial diversity Single-input multiple-output Multiple-input single-output Multiple-input multiple-output Correlation eects
2.6.5 Multi-hop relay systems Conventional multi-hop relay systems All-optical multi-hop relay systems Coherent multi-hop relay systems Subcarrier intensity modulation multi-hop relay systems Optimum placement for multi-hop relay systems Photon counting receiver for multi-hop relay systems Beam size variation at the receiver for multi-hop relay systems Hybrid spatial diversity and multi-hop relay systems Hybrid FSO and RF links for multi-hop relay systems
2.6.6 Cooperative relay systems Transmission relays Types of DF cooperative relay systems Conventional cooperative relay systems All-optical cooperative relay systems Subcarrier intensity modulation cooperative relay systems Selected relay for cooperative relay systems Power allocation for cooperative relay systems Multiple-source cooperation relaying Optimum placement for cooperative relay systems Multi-hop parallel relaying Mean time between failures for cooperative relay systems Inter-relay cooperation of cooperative relay systems Two-way relay systems
2.7 Practical Results
2.8 Summary
3 Diversity Techniques for Correlated Log-normal Channels 
3.1 Introduction
3.2 System Model
3.3 Performance Analysis
3.3.1 Orthogonal Space-Time Block Codes
3.3.2 Repetition Codes
3.4 Numerical Results and Discussions
3.5 Summary
4 Performance Analysis of Space Shift Keying Over Turbulent Channels 
4.1 Introduction
4.2 System Model
4.3 Performance Analysis
4.4 Average BER Probability of SSK Over Turbulent Channels
4.4.1 Negative exponential channels
4.4.2 LN channels (moderate turbulence)
4.4.3 LN channels (weak turbulence)
4.5 Numerical Results and Discussions
4.6 Summary
5 Performance Analysis of MISO Multi-hop Over Log-normal Channels 
5.1 Introduction
5.2 System Description
5.2.1 Single-Input Single-Output
5.2.2 MISO Using Repetition Codes
5.2.3 Multi-Hop DF Relaying
5.2.4 MISO Multi-Hop DF Relaying
5.3 Numerical Results and Discussions
5.4 Summary
6 Relay Selection For Full-Duplex FSO Relays Over Turbulent Channels 
6.1 Introduction
6.2 System And Channel Models
6.2.1 System Model
6.2.2 LN Channels
6.2.3 G-G Channels
6.3 Outage Performance Analysis
6.3.1 LN Channels
6.3.2 G-G Channels
6.4 Performance Analysis
6.5 Numerical Results and Discussions
6.6 Summary
7 Conclusions and Future Work 
7.1 Conclusions
7.2 Recommendations for Future Work
Appendix A 
A.1 List of Publications
Appendix B 
B.1 Approximation of Equation (3.27)
B.2 Matlab Code of Equation (3.27)
B.2.1 Introduction
B.2.2 The Matlab code
B.3 Proof of Equation (5.7)
B.4 Proof of Equation (5.15)
Appendix C 
C.1 The error function
C.2 The complementary error function
C.3 Meijer’s G-function


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