The data-entropy quality-budget developed by the authors is used as an alternative to the conventional power budget. The traditional power budget approach is not capable of providing a full analysis of a system with different noise types and specifically providing a measure of signal quality. The quality-budget addressed this issue by applying its dimensionless 'bit measure' to integrate the analysis of all types of losses. A data-entropy visualisation is produced for
each set of points in a reference and test signal. This data-entropy signal is a measure of signal disorder and reflects the power loss and types of signal degradation experienced by the test signal. To analyse the differences between two signals an algorithm known as phase-coherent data-scatter (PCDS) is used to assess levels of attenuation, dispersion, jitter, etc. Practical analysis of telecommunications signals using the new multiple-centroid (MC) PCDS is presented here for the first time. MC-PCDS is then used to analyse differences between sets of data-entropy signals and digital signals. The theory behind MC data-scatter is discussed and its advantages for the quantification of signal degradations are assessed. Finally, a brief consideration is given to the use of pattern recognition algorithms to measure optical signal degrading factors.
Proc. SPIE. 5825, Opto-Ireland 2005: Optoelectronics, Photonic Devices, and Optical Networks
KEYWORDS: Signal to noise ratio, Signal attenuation, Interference (communication), Data acquisition, Optoelectronics, Telecommunications, Quantization, Signal analysis, Oscilloscopes, Information theory
This paper introduces for the first time a numerical example of the data-entropy 'quality-budget' method. The paper builds on an earlier theoretical investigation into the application of this information theory approach for opto-electronic system engineering. Currently the most widely used way of analysing such a system is with the power budget. This established method cannot however integrate noise of different generic types. The traditional power budget approach is not capable of allowing analysis of a system with different noise types and specifically providing a measure of signal quality. The data-entropy budget first introduced by McMillan and Reidel on the other hand is able to handle diverse forms of noise. This is achieved by applying the dimensionless 'bit measure' in a quality-budget to integrate the analysis of all types of losses. This new approach therefore facilitates the assessment of both signal quality and power issues in a unified way. The software implementation of data-entropy has been utilised for testing on a fiber optic network. The results of various new quantitative data-entropy measures on the digital system are given and their utility discussed. A new data mining technique known as data-scatter also introduced by McMillan and Reidel provides a useful visualisation of the relationships between data sets and is discussed. The paper ends by giving some perspective on future work in which the data-entropy technique, providing the objective difference measure on the signals, and data-scatter technique, providing qualitative information on the signals, are integrated together for optical communication applications.
For the first time the term data diffraction is introduced, with examples drawn from the algorithm known as phase coherent data-scatter (PCDS) that produces identifiable visual patterns for different types of signal degradation in optical telecommunications. The main signal degradation factors that affect the performance of optical fibers include attenuation, rise-times and dispersion. The theory behind data-scatter is introduced including comprehensive explanations of the theoretical conceptual components of this technique such as centroids, exchange operation, coherence, closeness and projection radius. The various issues of assessing the quality of digital signals are outlined using a simulation study. The authors for the study of optical telecommunications issues have extended the functionality of data-scatter. This approach shows considerable promise. The utility of the data-entropy based 'quality budget method' for optoelectronic system engineering is revisited using an information theory based approach for optical telecommunications. Proposals for the implementation of pattern recognition algorithms to analyse the repeatable patterns within data-scatter are discussed. The paper concludes with brief considerations into the advantages of linking the new data-scatter and data-entropy approaches in digital fiber systems for performance quantification and assessment.