Communication networks increasingly carry information at various data rates. The selected data rate for a given communication can be pre-established between the transmitter and receiver, can be signaled, for example, using handshaking techniques, or can by dynamically determined by the receiver. Data rate detection techniques allow a receiver to determine the rate of incoming data, for example, by examining the received data. Such automatic data rate detection techniques allow a receiver to receive data from a variety of transmitting devices operating at different speeds without having to establish data rates in advance
Signals arriving at a receiver are typically corrupted by intersymbol interference (ISI), crosstalk, echo, and other noise. In order to compensate for such channel distortions, communication receivers often employ well-known equalization techniques. For example, zero equalization or decision-feedback equalization (DFE) techniques (or both) are often employed. Such equalization techniques are widely-used for removing intersymbol interference and to improve the noise margin. See, for example, R. Gitlin et al., Digital Communication Principles, (Plenum Press, 1992) and E. A. Lee and D. G. Messerschmitt, Digital Communications, (Kluwer Academic Press, 1988), each incorporated by reference herein Generally, zero equalization techniques equalize the pre-cursors of the channel impulse response and decision-feedback equalization equalizes the post cursors of the channel impulse response.
A communication channel typically exhibits a low pass effect on a transmitted signal. The various frequency components of a signal will thus encounter different attenuation at the output of the channel, with higher frequency components of a transmitted signal being impaired more than lower frequency components. Thus, the impairment of a channel is said to be rate-dependent. As a result, the equalization parameters optimized for one data rate will typically not be applicable for another data rate
In the absence of a received signal, the receiver lacks information (data transitions) and cannot sustain a frequency lock. If the equalizer is allowed to train when the signal has been lost, the equalizer will produce invalid updates Likewise, there are a number of predefined patterns that are not sufficiently spectrally rich to provide valid equalization results. For example, many communications systems continuously send an idle pattern to keep the system alive, in a similar manner to a heart beat signal. The idle pattern, however, is not spectrally rich and is therefore not good for equalization.
A need therefore exists for rate-dependent methods and apparatus for equalizing a channel A further need exists for equalization methods and apparatus that can detect the data rate, and perform equalization based on the detected data rate. Yet another need exists for equalization methods and apparatus that update the equalization parameters only if one or more predefined qualifier conditions, such as a loss of signal, are not present.