Compression and decompression of downlink channel estimates

Patent metadata

Field	Value
Publication number	US-11728851-B2
Application number	US-202217878964-A
Country	US
Kind code	B2
Filing date	Aug 2, 2022
Priority date	Mar 6, 2019
Publication date	Aug 15, 2023
Grant date	Aug 15, 2023

Abstract

A network node determines parameters indicating a compression function for compressing downlink channel estimates, and a decompression function. The network node transmits the parameters, receives compressed downlink channel estimates, and decompresses the compressed downlink channel estimates using the decompression function. A terminal device receives the parameters, forms the compression function, compresses downlink channel estimates using the compression function, and transmits the compressed downlink channel estimates. The compression function comprises a first function formed based on at least some of the parameters, a second function which is non-linear, and a quantizer. The first function is configured to receive input data, and to reduce a dimension of the input data. The decompression function comprises a first function configured to receive input data and provide output data in a higher dimensional space than the input data, and a second function which is non-linear.

First claim

What is claimed is:

1. A method of operating a user equipment (UE), the method comprising:
receiving a first set of parameters from a network node;
compressing downlink channel estimates using a compression function; and
transmitting the compressed downlink channel estimates,
wherein the compression function comprises a neural network having:
a linear function;
a non-linear function; and
a quantizer,

wherein the linear function is based on at least one of the parameters from the first set of parameters,
wherein the linear function is configured to:
receive input data; and
provide output data with a lower dimension than the input data,

wherein the non-linear function is configured to apply a non-linear activation function to each of a plurality of numbers in the output data of the linear function,
wherein the quantizer is configured to:
receive a plurality of numbers from the non-linear function; and
apply scalar quantizers to the received numbers.

2. The method of claim 1 , wherein the compression function comprises an alternating sequence of a first type of functions and a second type of functions, wherein at least one of the first type of functions is based on parameters from the first set of parameters, and wherein the second type of functions are non-linear functions.

3. The method of claim 2 , wherein:
an order of the functions in the alternating sequence of the first type of functions and the second type of functions is predefined;
the first type of functions are linear functions or are functions comprising a linear portion and a constant portion; and
the second type of functions are predefined,
wherein the quantizer is configured to:
receive a plurality of numbers; and
apply scalar quantizers to the received numbers.

4. The method of claim 1 , further comprising:
receiving a second set of parameters, the second set of parameters indicating a decompression function for decompressing downlink channel estimates which have been compressed using the compression function;
determining, based on the first set of parameters and the second set of parameters, an updated value for at least one parameter from the first set of parameters;
forming an updated compression function based on the updated value;
compressing downlink channel estimates using the updated compression function; and
transmitting the downlink channel estimates compressed using the updated compression function.

5. The method of claim 4 , further comprising:
receiving a third set of one or more parameters, the third set of one or more parameters indicating an objective function for evaluating performance of the compression function,
wherein the updated value for at least one parameter from the first set of parameters is determined using the objective function,
the method further comprising:
determining, based on the first set of parameters and the second set of parameters, an updated value for at least one parameter from the second set of parameters; and
transmitting the updated value for at least one parameter from the second set of parameters.

6. The method of claim 1 , wherein the downlink channel estimates comprise information about channels from antenna ports of the network node to antenna ports of the UE, the method further comprising:
determining the downlink channel estimates using downlink reference signals.

7. A method of operating a network node, the method comprising:
determining a first set of parameters, the first set of parameters indicating a compression function for compressing downlink channel estimates at a user equipment (UE);
determining a decompression function for decompressing downlink channel estimates which have been compressed by the UE using the compression function;
transmitting the first set of parameters;
receiving compressed downlink channel estimates; and
decompressing the compressed downlink channel estimates using the decompression function,
wherein the decompression function comprises a neural network having:
a linear function; and
a non-linear function,

wherein determining the decompression function comprises:
determining the linear function,

wherein the first function is configured to:
receive input data and
provide output data in a higher dimensional space than the input data,

wherein the non-linear function is configured to apply a non-linear activation function to each of a plurality of numbers in the output data of the linear function.

8. The method of claim 7 , wherein:
the second function is predefined.

9. The method of claim 7 , wherein the decompression function comprises an alternating sequence of a first type of functions and a second type of functions, wherein the second type of functions are non-linear functions, and wherein determining the decompression function comprises:
determining at least one of the first type of functions.

10. The method of claim 9 , wherein:
an order of the functions in the alternating sequence of the first type of functions and the second type of functions is predefined;
the first type of functions are linear functions or are functions comprising a linear portion and a constant portion; and the second type of functions are predefined.

11. The method of claim 7 , wherein the first set of parameters and the decompression function are determined based on:
information about the terminal device; and/or
information about the network node; and/or
information about a cell of the network node.

12. The method of claim 7 , wherein the first set of parameters and the decompression function are determined based on at least one of:
a position of the network node;
a position of the terminal device;
an expected pathloss for the terminal device;
a precoding method used by the network node;
a type of preceding used to transmit downlink reference signals; or
a time and/or frequency granularity of channel state information (CSI) related measurements and reporting.

13. The method of claim 7 , wherein determining the decompression function comprises:
determining a second set of parameters; and
forming the decompression function based on the second set of parameters, wherein the first set of parameters and the second set of parameters are determined by at least:
evaluating performance of different compression functions and decompression functions using an objective function; and
selecting values for the first set of parameter and the second set of parameters based on the evaluation,

wherein the evaluation is performed using one or more neural networks, and wherein the first set of parameters and the second set of parameters correspond to weights in the one or more neural networks.

14. A user equipment (UE) comprising:
processing circuitry;
and at least one memory, the at least one memory containing instructions that when executed by the processing circuitry cause the UE to:
receive a first set of parameters from a network node;
form a compression function based on the first set of parameters;
compress downlink channel estimates using the compression function; and
transmit the compressed downlink channel estimates,
wherein the compression function comprises a neural network having:
a linear function;
a non-linear function; and
a quantizer,

wherein the linear function is formed based on at least one of the parameters from the first set of parameters,
wherein the linear function is configured to:
receive input data; and
provide output data with a lower dimension than the input data,

wherein the non-linear function is configured to apply a non-linear activation function to each of a p

Assignees

• Ericsson Telefon Ab L M

Inventors

• Timo Roy
• Faxér Sebastian
• Wernersson Niklas
• Järmyr Simon

Classifications

• H04L1/0026

  Transmission of channel quality indication · CPC title

• H04B7/0452 Primary

  Multi-user MIMO systems · CPC title

• H03M7/3059 Primary

  Digital compression and data reduction techniques where the original information is represented by a subset or similar information, e.g. lossy compression · CPC title

• H03M7/6047

  Power optimization with respect to the encoder, decoder, storage or transmission · CPC title

• H04B7/0456

  Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting · CPC title