Digital adaptive receiver employing maximum-likelihood sequence estimation with neural networks
AssigneeTexas Instruments Incorporated
InventorJohn D. Provence
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Abstract
A maximum-likelihood sequence estimator receiver includes a matched filter connected to a digital transmission channel and a sampler for providing sampled signals output by the matched filter. The sampled signals are input to an analog neural network to provide high-speed outputs representative of the transmission channel signals. The neural network outputs are also provided as inputs to a coefficient estimator which produces coefficients for feedback to the matched filter. For time-varying transmission channel characteristics, the coefficient estimator provides a second coefficient output which is utilized for changing the interconnection strengths of the neural network connection matrix to offset the varying transmission channel characteristics.
Claims39
A digital receiver for maximum-likelihood sequence estimation of digital signals transmitted over a time-dispersive transmission channel, comprising:
- a matched filter with an input for receiving signals transmitted over the transmission channel;
- and
- a neural network for receiving sampled signals output by said matched filter and for providing output signals of said receiver which are estimates of signals initially transmitted over said transmission channel.
A digital receiver for maximum-likelihood sequence estimation of digital signals transmitted over a time-dispersive transmission channel, comprising:
- a matched filter with an input for receiving signals transmitted over a transmission channel;
- and
- a network for carrying out neural type of function for receiving sampled signals output by said matched filter and for minimizing a cost function according to an expression ##EQU25## for generating a sequence of data symbols representing a maximum-likelihood estimation of the transmitted sequence, where a.sub.i are the digital signals transmitted, z.sub.i are sampled output of the matched filter, and s.sub.k are the coefficients for the maximum-likelihood sequence estimation.
A digital receiver for maximum-likelihood sequence estimation of digital signals transmitted over a time-dispersive transmission channel, comprising:
- a matched filter having an input and an output, said input for receiving signals transmitted over the transmission channel;
- a sampler connected to the output of said matched filter for sampling signals output by said matched filter to provide a sampled signal;
- a multiple stage serial-to-parallel shift register for receiving a series of said sampled signals and providing a parallel output thereof;
- a neural network having a number of neurons for receiving the parallel output of said shift register, said neural network having a number of outputs comprising the output of said receiver;
- and
- a coefficient estimator for receiving an estimated sequence output by said neural network and for receiving digital signals carried by said channel, and further including an output providing coefficient information coupled back to said neural network for modifying connection strengths of said network.
A method of processing signals received over a digital transmission channel using maximum-likelihood sequence estimation techniques, comprising the steps of:
- coupling the signals through a filter adapter for matching to the transmission channel;
- converting the signals to digital signals;
- and
- presenting the digital signals to a neural network to provide a high-speed output estimation of the signals initially transmitted of the transmission channel.
Dependencies are inferred from the claim text.