Novatel Communications Ltd.

Yongbing Wan

Andrew M Sendyk

Qingli Liu

A diversity receiver employing maximum-likelihood-sequence estimation employs a separate channel estimator (44-1, . . . , 44-L) for each of a plurality of diversity channels. Each channel estimator (44-1, . . . , 44-L) produces channel-model parameters ([f.sub.1 ], . . . , [f.sub.L ]) that characterize their respective channels. A weighting-and-accumulation circuit (56) computes the responses of the thus-represented models to candidate symbol sequences, and metrics indicating the likelihoods that respective candidate sequences were the sequences actually sent are determined by comparing the model output with the received signal in a comparison circuit (58) and squaring the magnitudes of the results in a squaring circuit (60). The receiver then employs a Viterbi algorithm (62) to determine which sequence is the one most likely to have been sent. In one version, it does this on the basis of the metrics calculated for the channel whose signal is strongest, while it determines the metrics by combining partial metrics from all of the channels in another version.

Adaptive-sequence-estimation apparatus employing diversity

An improved decision feedback equalizer for use with digital communications. The equalizer includes an error detector, a process controller, a parameter selector and a data buffer for temporarily storing a digital data signal received from a communication channel. The error detector determines whether the equalizer is accurately tracking changes in the communication channel's characteristics or is lost. When the error detector determines that the equalizer is lost, the process controller responsively generates control signals for initiating an optimal retraining/recovery method for the prevailing conditions. In some retraining/recovery methods, data is temporarily stored in the buffer. The stored data is later retrieved and processed once the equalizer is retrained. Retraining is performed using a retraining signal received via the communication channel or, if available, a portion of the data signal which is suitable for retraining, thereby permitting more rapid resumption of data reception. In addition, the parameter selector, in response to a control signal from the process controller and a signal which is indicative of the rate of change of the communication channel's characteristics, dynamically adjusts the convergence rate of the equalizer to provide to an optimum value for performing retraining or tracking changes in the channel's characteristics.

Decision feedback equalizer

The channel-impulse-response estimator (44') in a maximum-likelihood-sequence-estimation receiver produces channel-model parameters for a model that produces outputs not only for symbol times but also for intermediate times between the symbol times. A symbol-sequence-derivation circuit (42') determines the most-likely sequence on the basis of metrics computed from the differences between the received signal and the responses of the model to candidate sequences not only at the symbol times but also at the intermediate times. An interpolator (100) receives the symbol decisions from the symbol-sequence-derivation circuit (42') and generates intermediate values from them by simulating the Nyquist filter formed by the concatenation of pulse-shaping filters (22 and 24) in the transmitter and matched filters (36 and 37) in the receiver. The channel-impulse-response estimator (44') uses these values together with the derived-symbol values as inputs to its updating process to maintain the model.

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Yongbing Wan