ve quite different long and short term BER ever, a point will come when the error control coding system can no requirements. For speech, a listener will usually be tolerant to the longer cope and then significant numbers of decoded data blocks low level of background noise caused by randomly distributed may contain errors, now the proportion of error free blocks becomes errors (Takahashi, 1988). Burst errors usually cause more objection- a useful measure of performance. Bursts of errors No errors Long term recorded mean BER Measurement interval Figure 28.8 Variation of BER with time in a burst error environment 28/8 Digital transmission Thus, in order to quantify the error distribution characteristics, the BER measure must be refined by the addition of other measures. Table 28.2 Error performance objectives; an example (CCITT, 1988a) 28.2.3 Available time Performance Objective This is the percentage of time, in a specified time interval, in which parameter the BER is less than a specified threshold. Degraded Fewer than 10% of one-minute intervals to This measure is especially useful when blocks of data are pro- minutes have a BER worse than 10-6 tected by an error control coding scheme. The coding algorithm will Severely Fewer than 0.2% of one-second intervals to usually be able to handle a given number of errors in a block. errored seconds have a BER worse than 10 Blocks with more errors will be decoded erroneously. If the BER measurement interval corresponds to the error control block length Errored seconds Fewer than 8% of one-second intervals to then, with the appropriate BER threshold, the available time will have any errors (i.e. EFS > 92%) correspond to the percentage of error free blocks after decoding the received data. 28.2.4 Error-Free Seconds (EFS) From the network operators point of view, this specification is somewhat incomplete. With the increasing deployment of digital networks a connection will often comprise a number of links per- This is the proportion of one-second intervals, in a specified ti