Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2001-05-01
2003-07-29
Bui, Bryan (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C324S076770
Reexamination Certificate
active
06601004
ABSTRACT:
TECHNICAL FIELD
The present invention relates to a method of and apparatus for measuring parameters of an electronic system by reference to an input series of data samples received and processed so as to produce in real-time at least first and second time-varying series of measurements for a given parameter. The invention may be applied in the measurement of timing errors in digital transmission systems, for example, standardised for the measurement known as Maximum Timing Interval Error (MTIE) in Synchronous Digital Hierarchy (SDH) digital transmission systems, in accordance with specifications as set out by the telecommunications standardisation sector of the International Telecommunications Union (ITU-T).
BACKGROUND ART
Modern telecommunications networks demand a high degree of synchronisation between network transmission elements. Timing is critical for all network transmission elements in SDH architectures. However, as will be explained later, phase variations in the reference clock frequencies governing synchronous network elements may introduce errors at various stages in the network.
One measure of timing errors in synchronous digital transmission systems is known as the Maximum Time Interval Error (MTIE) and is derived from an ensemble of timing error samples. In SDH systems, the timing error samples are referred to as “Time Interval Error” or TIE samples, and a standardised maximum timing variation measure, MTIE is accordingly defined. MTIE is a measure of the time variation of a signal and can also provide information on signal frequency offsets and phase transients. MTIE values, together with other parameters, are used to evaluate the performance of equipment and systems, often to diagnose a fault which has developed and which impairs customer service.
Unfortunately, implementing directly the definition of MTIE (or similar parameters) provided by the standards bodies does not permit a real-time display of the results. In particular, MTIE is generally required to be measured in parallel for a set of different times (observation intervals), to reveal information about the time varying behaviour of the signal, and aid in the diagnosis of faults. The observation intervals typically range from one second up to a day or more. To obtain the results for such intervals conventionally requires a large quantity of data to be collected and, in principle, even for the shortest observation interval, MTIE cannot be calculated until the entire data set has been gathered. This is clearly inconvenient but if, to obtain a quicker result, MTIE for the observation intervals is calculated using a partial set of data, the calculations performed must be performed again as more data becomes available.
One known such example of a test instrument offering MTIE analysis is the ANT-20 Advanced Network Tester available from Wavetek Wandel Golternann, D-72800 Eningen u. A., Germany. This product offers off-line MTIE analysis.
Apart from the delay inherent in off-line systems, another problem with the implementation of prior solutions is the large amount of data storage and computation needed to obtain the measured values of MTIE or the like, particularly for the longer observation intervals. The ITU-T specifies a minimum sample rate of 30 Hz for the TIE measurements, while samples covering at least three times the observation interval are generally required to obtain one measurement.
It is an object of the present invention to permit real-time calculation of a set of measurements such as MTIE for a range of observation intervals, while reducing the computational burden involved. A further object is to provide current estimates of measurements for a number of observation intervals, without waiting for those intervals to elapse completely.
The inventors have recognised that an alternative method of evaluating MTIE can be achieved by providing MTIE values for a given test duration by progressively discarding insignificant data for each observation interval. This offers a real-time implementation at reasonable hardware cost. More over, the inventors have recognised that in such an implementation estimates of the measurement for at least the shorter observation intervals become more quickly available. Short term problems may thus reveal themselves to the engineer as the early results are replaced with new data. Results for longer observation intervals will become available as time progresses, although initial estimates for these too can even be provided more or less immediately and continuously.
One system which purports to offer real-time MTIE measurement on this basis is Flexacom Plus, advertised by ICT Electronics on the internet at http://www.ict.es. However, details of the computation and the availability of results are not known.
DISCLOSURE OF INVENTION
The invention provides a method of measuring parameters of an electronic system by reference to an input series of data samples, the data samples being processed in a first stage process so as to produce in real-time at least a first time-varying series of measurements for a given parameter characterising the data samples over observation intervals of a first magnitude (a 10 second interval in the examples), each of said observation intervals being many times longer than the sample period of the input series, the first stage process comprising:
deriving at least a first intermediate result from data samples of the input series received in a pre-determined sub-interval, and repeating the determination for successive sub-intervals so as to generate a series of first intermediate results;
storing a finite number of said first intermediate results in a first data set, such that an observation interval of the first magnitude is encompassed by the set of sub-intervals corresponding to the stored intermediate results, the first data set being updated at least once per sub-interval by discarding an oldest intermediate result and adding a new intermediate result;
deriving from the first data set a measurement of the given parameter corresponding to the observation interval and updating said measurement to generate said series of measurements as the first data set is updated.
By storing intermediate results for sub-intervals rather than for individual samples, the size of the data set(s) can be much reduced relative to the total number of samples processed, while ensuring that the entire series of samples within each observation interval is accounted for. It will be understood that “real time” in this context does not imply that results are available without delay, or must be strictly synchronised with the flow of input samples. “Real time” in this context signifies merely that input samples can be processed, on average, substantially at the rate at which the input samples are generated.
The method may further comprise a second stage process to derive at least a second series of measurements, corresponding to observation intervals of a second magnitude longer than the first (for example, a 100 second interval), said second series of measurements being derived in real time by treating the first observation intervals as sub-intervals of the second observation interval.
The second stage process may in particular comprise:
deriving from the first data set a second intermediate result corresponding to said first observation interval, and repeating the determination for successive sub-intervals of the second observation interval so as to generate a series of second intermediate results;
storing a finite number of said second intermediate results in a second data set, such that the second observation interval is encompassed by the set of sub-intervals corresponding to the stored second intermediate results, the second data set being updated at least once per sub-interval by discarding an oldest second intermediate result and adding a new second intermediate result;
deriving from the second data set a measurement of the given parameter corresponding to the second magnitude of observation interval and updating said measurement to generate said second series of me
Ballantyne Alex
Taylor David
Agilent Technologie,s Inc.
Bui Bryan
Le John
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