Multiple radio frequency impairment estimation
AssigneeVestel Elektronik Sanayi ve Ticaret A. S.
InventorsMehmet Ali Aygül, Hüseyin Arslan
Life of this patent
Estimating the term…
Abstract
The present disclosure relates to the detection of impairments in a received wireless communication signal. It may detect the presence of each of N types (sources) of impairments and possibly the amount of the impairment present in the received signal. The detection includes processing of the received signal by a trainable model trained to distinguish N sources of impairments by applying learning, with N being an integer larger than one. The trainable model outputs, for each source j of the N sources, a contribution of the j-th source of impairments to the obtained signal. The contribution may be binary, indicating the presence or absence of the j-th source of impairment, or may also indicate the amount of impairment.
Claims12
A method for estimating radio frequency transmission impairments, the method comprising:
- obtaining a signal received over a wireless channel;
- processing the obtained signal by a trainable model trained to distinguish N sources of impairments, N being an integer larger than one;
- and
- outputting from the trainable model, for each source j of the N sources, a contribution of the j-th source of impairments to the obtained signal;
- wherein the machine learning includes one or more types of machine learning methods comprising a multi-layer perceptron, long short-term memory, and/or convolutional neural network, and at least two of the N sources of impairments are processed by different types of the machine learning methods.
A method for training a trainable model for estimating radio frequency transmission impairments, comprising:
- obtaining a training set comprising plural training data comprising input signal impaired by an impairment and by a transmission channel and an impairment indication indicating type of the impairment, signal;
- inputting the training set into the trainable model;
- adapting parameters of the trainable model according to the inputted training set;
- and
- storing the adapted parameters for use in said estimating radio frequency transmission impairments.
An apparatus for estimating radio frequency transmission impairments, the apparatus comprising processing circuitry configured to:
- obtain a signal received over a wireless channel;
- process the obtained signal by a trainable model trained to distinguish N sources of impairments by applying supervised learning, N being an integer larger than one;
- and
- outputting from the trainable model, for each source j of the N sources, a contribution of the j-th source of impairments to the obtained signal;
- wherein the processing circuitry is further configured to train the learning module by:
- obtaining a training set comprising plural training data including input signal impaired by an impairment and by a transmission channel and an impairment indication indicating type of the impairment, signal;
- inputting the training set into the trainable module;
- adapting parameters of the trainable module according to the machine learning using the inputted training set;
- and
- storing the adapted parameters for use in said estimating radio frequency transmission impairments.
Dependencies are inferred from the claim text.