Orthogonal frequency division multiplexing (OFDM) has recently gained substantial interest in high capacity optical fiber communications. Unlike wireless systems, optical OFDM systems are constrained by the limited resolution of the ultra high-speed digital-to-analog converters (DAC) and analog-to-digital converters (ADC). Additionally, the situation is exacerbated by the large peak-to-average power ratio (PAPR) inherent in OFDM signals. In this paper, we study the effects of clipping and quantization noise on the system performance. We analytically quantify the introduced distortion as a function of bit resolution and clipping ratio, both at the DAC and ADC. With this we provide a back-to-back signal-to-noise ratio analysis to predict the bit error rate of the system, assuming a fixed received optical power and ideal electrical-optical-electrical conversion. Simulation and experimental results are used to confirm the validity of the expressions.

We demonstrate a field programmable gate array (FPGA) based optical orthogonal frequency division multiplexing (OFDM) transmitter implementing real time digital signal processing at a sample rate of 21.4 GS/s. The QPSK-OFDM signal is generated using an 8 bit, 128 point inverse fast Fourier transform (IFFT) core, performing one transform per clock cycle at a clock speed of 167.2 MHz and can be deployed with either a direct-detection or a coherent receiver. The hardware design and the main digital signal processing functions are described, and we show that the main performance limitation is due to the low (4-bit) resolution of the digital-to-analog converter (DAC) and the 8-bit resolution of the IFFT core used. We analyze the back-to-back performance of the transmitter generating an 8.36 Gb/s optical single sideband (SSB) OFDM signal using digital up-conversion, suitable for direct-detection. Additionally, we use the device to transmit 8.36 Gb/s SSB OFDM signals over 200 km of uncompensated standard single mode fiber achieving an overall BER<10(-3).

No abstract

No abstract

2 a o. 41 w 1" 8 12 a '0 0.1 0.2 0.3 0.4 0.5 inpul pulse ehsrgy E," (pj) Fig.2. Energy and F W W of a pulse transmitted in cascaded regenerators versus initial pulse energy. Number of cascaded regenerators are I(dotted curve), 2(dot-dashed curve), and 5(solid curve) in (a) for type-A regenerators and I(doned curve), )(dot-dashed curve), and IO(solid curve) in (b) far typed regenerators -0 5 -B h -0.5 2 0 0 -1 number of lt)genem1016 Fig.3. Restoration of time shifts by the cascaded regenerators. Solid and dashed curves are for the type-A and we-B regenerators, respectively, tively. The k& have sawto& s h a p e b e c k MONDAY AFTERNOOON / OFC 2003 I VOL. 1 / I 0 9the eye degradations both at the entrance and exit of each regenerator are plotted. Fig.). Eye degradation versus hansmission distance of a single-channel 4OGbitis highly-dispened pulse transmission when no regenerators are inserted (dotted curve), tpe-A regenerators are inserted (solid c w e s ) , and t j p e B regenerators are inserted (dashed curves) at evew 2,3, and 5 spans.A novel h i s t o p m method to estimate the white Gaussian noise in the nelwork is proposed. This method can be used to correctly deconvolve white noise frotn other sources of degradalion. The limits of the deconvolution technique are also investigated. 1. Introduction Future all optical networks (AON) will transport a variety of voice and data signals over optical channels regardless of their format or bit rate. One major obstacle in these networks is the transparent implementation af performance monitoring, fault localization and network management. Different (analogue) monitoring schemes have been proposed [I] and most ofthem fall within two categories: spectral methods and sampling methods. The former, albeit simple and fast to implement, are insensitive to distortion such as chromatic din-Gdthey usually utilize the statistical information of the signal to derive histograms and the bit mor rate (BER). Furthermore, the histograms and especially the marks' histogram take a distinctive shape for every source of degradation [3] and this could be used to determine the cause of signal distortion during msmissian. Indeed, identifying the sources of distvtiion is an important task to isolate faulty components, to anticipate major equipment degradation @re-emptive maintenance), and to estimate quality of service for a new path (connection management). In general, the histogram reflects a combination of distortion and noise existing on the transmission path. In other wards, the different "symptoms" appearing an the histogram and originating from different ~ources of degradation me convolved together and could be separated by using the FFT deeonvoiution method. This technique was first proposed by Weinert et all41 to evaluate crosstalk in an environment dominated by Gaussian noise. However, Unless the exact amount of Gaussian noise is known, the use ofthis technique will not lead to the correct detection of crosstau( [5j. In this paper, wue present a novel way of evaluating the Gaussian n...