Integrated Wireless-pon access Network Architectures Milos Milosavljevic

: General description of inter-software functionalities for WiMAX transceivers
Optical and Wireless PHY Integration
stored in the target environment (i.e. MATLAB) via galaxy ports (e.g. CoSimInputOpt) and 
on is executed. The expected output data are then collected and fed back 
interoperable model and evaluate its preliminary performance, a IEEE802.16d 
WiMAX OFDM transceiver model was built in MATLAB and applied at the VPI CoSim 
transmitter and receiver, demonstrating 
modelling platforms. The performance of 
WiMAX channels was modelled with no channel coding applied in order to present a worst case 
software functionalities for WiMAX transceivers

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Chapter 3 Optical and Wireless PHY Integration
58 
At the transmitter, following the symbol formation and serial to parallel conversion in 
MATLAB, the subcarrier mapping block could be used to insert guard carriers for a brick-wall 
spectrum shape [35].
The resulting frequency domain signal was subsequently transformed to the time domain using 
the 256 point IFFT prior to parallel to serial conversion and cyclic prefix addition. The 
quantisation process and signal shaping are performed in VPI.
At the other end, the WiMAX receiver performs the inverse functions to those of the 
transmitter. The 14 bits digital to analog (D/A) and analog to digital (A/D) converters at the 
transmitter and receiver respectively were used to minimise quantisation noise [35]. The cyclic 
prefix removal, FFT and wireless channel equalisation at the receiver are performed in 
MATLAB while VPI is used for estimating the symbol error rate (SER) and EVMs.
Critically, estimating the SER of the electrical mQAM signal in RoF systems raises additional 
issues compared to classical systems where only additive white Gaussian noise (AWGN) 
influences signal quality [37]. The probability density function (PDF) of the received I and Q 
signals does not always follow a Gaussian distribution. It was shown that this PDF is Gaussian 
when electrical or optical noise (ASE) is the main impairment [37]. On the other side, when 
composite triple beat (CTB) also called third-order inter-modulation distortions (IMD3) occurs, 
this PDF tends to an Exponential distribution. More generally, the PDF lies between a Gaussian 
and an Exponential distribution, making the SER more complicated to estimate. In addition to 
the above, nonlinear distortions can be amplitude-dependent so that the distribution statistics 
(e.g. the variance) may be different for each symbol [37].
To account for these characteristics, the SER estimation is based on an independent 
approximation of the left and right tails of the signal’s PDF, corresponding to each mQAM 
symbol [38].

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