Dynamic Resource Allocation for Network Echo Cancellation
Current adaptation algorithms for network echo cancelers are designed without regard to the fact that, invariably, a single canceler chip handles many conversations simultaneously. This implies that for N c channels, the processor must handle N c times the peak computational load of a single channel. If the number of channels is large, however, it should be possible to reduce the demands on the processor to something close to N c times the average load. Some additional computational capacity would, of course, be necessary to take care of statistical fluctuation in the requirements, but the required safety margin becomes smaller as N c becomes larger. (With the speed and memory now available on a chip, the number of channels can be several hundred, so the safety margin might not have to be large.) Once the problem is looked upon as that of dealing with a large number of channels, it is also possible to take advantage of other knowledge about speech patterns and characteristics of long distance circuits to further reduce the computational load. In this chapter, we show how the computational requirement can, in principle, be reduced by a very large factor perhaps as large as thirty.
KeywordsSpeech Signal Adaptive Filter Acoustic Echo Cancellation NLMS Algorithm Cumulative Magnitude
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