US 2020/0028593 A1Published application

Optical communication channel equalization using a kernel

OwnerJiajia CHEN, Lu ZHANG +2inventors

InventorsJiajia CHEN, Lu ZHANG, Xiaodan Pang, Shilin Xiao

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Abstract

The disclosure relates to a method performed by an optical receiver, the method comprising receiving an optical communication signal comprised in a signal space, the signal comprising a set of received training symbols and a set of received payload symbols, determining a kernel operating in a feature space by using the set of training symbols and a reference set of training symbols indicative of an undistorted version of the training symbols, wherein determining a kernel further comprises determining at least an equalization mapping function ƒ configured to map received symbols to channel equalized symbols, and determining an error function (e) configured to generate a measure indicative of an error between symbols mapped by the equalization mapping function ƒ and an ideal equalization mapping function, performing nonlinear equalization of the payload symbols (C′1 to C′M) by performing linear equalization of the payload symbols (C′1 to C′M) in the feature space using the received training symbols (C1 to CN) and the error function (e). The disclosure further relates to an optical receiver

Claims9

Dependent claims

A method performed by an optical receiver, the method comprising:

receiving an optical communication signal comprised in a signal space, the signal comprising a set of received training symbols and a set of received payload symbols
determining a kernel operating in a feature space by using the set of training symbols and a reference set of training symbols indicative of undistorted training symbols, wherein determining a kernel further comprises:
determining at least an equalization mapping function ƒ configured to map received symbols to channel equalized symbols, wherein the received symbols comprise the set of received training symbols and the set of received payload symbols, and
determining an error function configured to generate a measure indicative of an error between the channel equalized symbols and ideal symbols, wherein the received symbols is mapped to the ideal symbols through an ideal equalization mapping function,
performing nonlinear equalization of the payload symbols by performing linear equalization of the payload symbols in the feature space using the received training symbols and the error function;
wherein the nonlinear equalization is performed using Least Mean Square equalization defined by a relation:
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where x(i) is an ideal training signal, e(i) is the error function, {right arrow over (h)} (i) is an channel equalization filter weight vector, μ is a step-size parameter, φ({right arrow over (c)}(i)) is a feature mapping function from the signal space to a kernel feature space, and {right arrow over (c)}(i) is a training signal vector.

73 more elements

Dependencies are inferred from the claim text.