Radio receiver

A method, comprising:

• obtaining a data array comprising a plurality of elements, wherein an element in the plurality of elements in the data array corresponds to a subcarrier in a plurality of subcarriers, to a timeslot in a time interval, and to an antenna stream;
• implementing a machine learning model comprising at least one neural network and a transformation, wherein the transformation comprises at least one multiplicative layer to multiply together elements in the data array, wherein the multiplicative layer is trained in conjunction with the at least one neural network of the machine learning model, and wherein output of the multiplicative layer functions as input for the at least one neural network;
• and
• inputting data into the machine learning model, wherein the data comprises at least the data array;
• wherein the machine learning model is configured to, based on the input data, output an output array representing values of the plurality of elements in the data array, wherein the values comprise bits or symbols.

A non-transitory program storage device readable with an apparatus, tangibly embodying a program of instructions executable with the apparatus for performing:

• obtaining a data array comprising a plurality of elements, wherein an element in the plurality of elements in the data array corresponds to a subcarrier in a plurality of subcarriers, to a timeslot in a time interval, and to an antenna stream;
• implementing a machine learning model comprising at least one neural network and a transformation, wherein the transformation comprises at least one multiplicative layer to multiply together elements in the data array, wherein the multiplicative layer is trained in conjunction with the at least one neural network of the machine learning model, and wherein output of the multiplicative layer functions as input for the at least one neural network;
• and
• inputting data into the machine learning model, wherein the data comprises at least the data array;
• wherein the machine learning model is configured to, based on the input data, output an output array representing values of the plurality of elements in the data array, wherein the values comprise bits or symbols.