In some examples, a receiver can include a sampler circuit that can be configured to process a data input signal corresponding to a current bit received at a receiver based on a capacitive weighted signal to compensate for distortion effects that a previously received bit at the receiver has on the data input signal. The receiver can include a capacitive coupling feedback circuit that can be configured to generate the capacitive weighted signal corresponding to a weighted detected bit of the previously received bit based on a capacitance of a subset of capacitors of a plurality of capacitors of the feedback circuit. The capacitive coupling feedback circuit can be configured to selectively control a number of capacitors of the plurality of capacitors that are connected in parallel corresponding to the subset of capacitors to control an amount of weight applied to the detected bit to generate the capacitive weighted signal.

The disclosed systems and methods are directed to transmitting and receiving symbols. In particular, splitting, a symbol dataset into symbol subsets, modulating, the symbol subsets using different sub-carriers, roll off factors and time acceleration factors, performing frequency shifting and combining the frequency shifted and modulated symbol subsets to generate a digital multiband (DMB) signal, transmitting and receiving the DMB signal, down converting the received DMB signal into a plurality of baseband signals, segregating the plurality of baseband signals in accordance with a manner by which the symbol subsets have been processed before transmission, forwarding a first portion of the plurality of baseband signals to a minimum mean square error (MMSE) based receiver, forwarding a second portion of the plurality of baseband signals to a matched filter-based receiver, and combining the output of the MMSE based receiver and matched filter-based receiver to generate an equivalent symbol dataset.

LMS adaption systems and methods disclosed herein adaptively switch between modes of operation that selectively avoid using the imaginary part of an error signal, in effect, allowing for an LMS adaption that switches between utilizing only the real part of the error signal and utilizing the full complex error signal. Various embodiments take advantage of this added flexibility by implementing a dynamic power saving scheme that, for example, during times when high tracking performance (e.g., high accuracy or high SNR) is not needed, saves power by not energizing a number of multiplier and adder circuits that are expensive in terms of power consumption, thereby, trading power savings for a possible temporary reduction in tracking performance. In embodiments, power savings are accomplished by adaptive power-gating systems and methods that in parts of an analog LMS adaption circuit turn on and off current sources in analog multiplier circuits on demand.

A transmission device includes a receiver configured to receive a frame signal including synchronization data, main signal data, and an error correction code, a compensator configured to compensate for distortion of the frame signal based on a compensation coefficient, a detector configured to detect synchronization timing of the frame signal from the synchronization data; a corrector configured to correct an error of the frame signal after the distortion is compensated, based on the error correction code according to the synchronization timing, a generator configured to generate a replica signal from the frame signal after the error is corrected by the corrector, based on the synchronization timing, the replica signal corresponding to the frame signal before the distortion is compensated, and an update processor configured to update the compensation coefficient based on the replica signal and the frame signal before the distortion is compensated.

A semi-blind channel estimation method and apparatus are provided. The semi-blind channel estimation method includes: step S1: obtaining data that includes a first training sequence and that is received by a receive end; step S2: performing minimum mean square error channel estimation based on the data and the prestored first training sequence, to obtain a channel parameter matrix; step S3: detecting the first training sequence by using a least square detection algorithm, to obtain estimated data; and step S4: using the estimated data as a second training sequence, replacing the first training sequence in step S2 with the second training sequence, and cyclically performing step S2 and step S3 on the second training sequence, until a channel parameter matrix obtained last time is the same as a channel parameter matrix obtained this time, and then stopping circulation, to estimate a final channel parameter matrix.

Disclosed embodiments include a decision feedback equalizer (DFE) comprising an N-bit parallel input adapted to be coupled to a communication channel and configured to receive consecutive communication symbols, a first DFE path including a first path input configured to receive communication symbols, and a first adder having a first adder input coupled to the first path input. There is a first DFE filter having outputs responsive to the first DFE filter inputs, the outputs coupled to the second adder input. The DFE includes a first path having a first slicer and a first multiplexer, a first path multiplexer output, and a second DFE path including a second path input configured to receive a second communication symbol, a second adder, a second DFE filter, a second slicer, and a second multiplexer.

A receiver includes a continuous-time equalizer, a decision-feedback equalizer (DFE), data and error sampling logic, and an adaptation engine. The receiver corrects for inter-symbol interference (ISI) associated with the most recent data symbol (first post cursor ISI) by establishing appropriate equalization settings for the continuous-time equalizer based upon a measure of the first-post-cursor ISI.

Described herein are systems and methods that perform coarse chromatic dispersion (CD) compensation by applying precomputed coarse front-end equalizer (FEE) tap weights to a receiver based on an assumed propagation distance. After a waiting period, the FEE tap weights are applied, and it is determined whether the FEE tap weights cause a decision-directed tracking of channel rotations to satisfy a stability metric. In response to the stability metric not being satisfied, the assumed propagation distance is adjusted and used to obtain updated FEE tap weights. Conversely, if the stability metric is satisfied, a fine CD compensation is performed that comprises maintaining the updated FEE tap weights; performing an iterative least-mean-squared (LMS) error adaption to adjust Back-End Equalizer (BEE) tap weights and obtain updated BEE tap weights; and using the updated BEE tap weights to adjust the FEE tap weights to, ultimately, have the BEE output an equalized data bit stream.

A method comprising modulating a plurality of synchronized signals by an orthogonal probe sequence (OPS) to generate a plurality of modulated synchronized signals, wherein the OPS comprises a zero element (0-element) column that indicates a start or an end of the OPS, and concurrently transmitting, using one or more transmitters, the plurality of modulated synchronized signals over a duration of a number of discrete multi-tone (DMT) symbols, wherein each of the plurality of modulated synchronized signals is intended for one of a plurality of receivers that are remotely coupled to the one or more transmitters via a vectored group of subscriber lines, and wherein the 0-element column causes all of the plurality of modulated synchronized signals to have a zero-amplitude during a first or a last of the DMT symbols.

Examples described herein include setting an equalizer tap setting and gain setting in a serializer/deserializer (SerDes). In some examples, determining an equalizer setting and gain setting occurs by causing a mean-square error cost scheme tracking to lock to an offset from a minimum of a cost of the mean-square error cost scheme without pausing error cost tracking. In some examples, the mean-square error cost scheme comprises a least mean square (LMS) scheme. In some examples, determining an equalizer setting comprises: applying increases or decreases to an equalizer setting, and an increase to an equalizer setting can be a different amount than an amount of decrease to an equalizer setting.