Machine learning-based vector quantization method and device for limited feedback in wireless communication system

A method of determining a precoder by a transmitter in a wireless communication system, the method comprising:

• transmitting, by the transmitter, a signal to a receiver;
• receiving, by the transmitter from the receiver, feedback information including at least one selection vector;
• obtaining, by the transmitter, at least one codeword candidate by using the at least one selection vector;
• obtaining, through a fully connected layer of a deep neural network at the transmitter, a feature matrix based on the at least one codeword candidate;
• and
• determining, by the transmitter, the precoder based on the feature matrix,
• wherein the at least one selection vector is configured with a same number of elements as the number of the at least one codeword candidate included in a predetermined codebook and includes at least one non-zero element,
• wherein the at least one selection vector specifies a weight-based combination for at least one of the at least one codeword candidate,
• wherein the at least one selection vector is obtained based on a normalized feature matrix, wherein the normalized feature matrix is obtained by applying normalization to the feature matrix,
• wherein ei*,l which is an l-th element of the at least one selection vector ei* is expressed as in Equation below:
• e
• i
• ★
• ,
• l
• =
• 
• G
• _
• ⁢
• c
• l
• 
• α
• ∑
• j
• =
• 1
• 2
• B
• 
• G
• _
• ⁢
• c
• j
• 
• α
• where, G is the normalized feature matrix,
• cx is a x-th codeword of the at least one codeword candidate,
• 2B corresponds to the number of the at least one codeword candidate,
• α is a predetermined positive real number.

A receiving device performing feedback in a wireless communication, the receiving device comprising:

• a transceiver;
• an antenna unit;
• a memory;
• and
• a processor,
• wherein the processor is configured to:
• receive, through the transceiver, a signal from a transmitting device,
• obtain and store in the memory a feature matrix, through a fully connected layer of a deep neural network at the receiving device, based on the signal received from the transmitting device through the transceiver and stored in the memory;
• based on the feature matrix, obtain and store in the memory a selection vector for at least one codeword candidate included in a predetermined codebook;
• and
• transmit feedback information including the selection vector to the transmitting device through the transceiver,
• wherein the selection vector is configured with a same number of elements as the number of the at least one codeword candidate and includes at least one non-zero element,
• wherein the selection vector specifies a weight-based combination for at least one of the at least one codeword candidate,
• wherein the selection vector is obtained based on a normalized feature matrix, wherein the normalized feature matrix is obtained by applying normalization to the feature matrix, wherein ei*,l which is an l-th element of the selection vector ei* is expressed as in Equation below:
• e
• i
• ★
• ,
• l
• =
• 
• G
• _
• ⁢
• c
• l
• 
• α
• ∑
• j
• =
• 1
• 2
• B
• 
• G
• _
• ⁢
• c
• j
• 
• α
• where, G is the normalized feature matrix,
• cx is a x-th codeword of the at least one codeword candidate,
• 2B corresponds to the number of the at least one codeword candidate,
• α is a predetermined positive real number.

A transmitting device determining a precoder in a wireless communication system, the transmitting device comprising:

• a transceiver;
• an antenna unit;
• a memory;
• and
• a processor,
• wherein the processor is configured to:
• transmit, through the transceiver, a signal to a receiving device;
• receive and store in the memory feedback information including at least one selection vector from the receiving device through the transceiver;
• obtain and store in the memory at least one codeword candidate by using the at least one section vector;
• obtain and store in the memory, through a fully connected layer of a deep neural network at the transmitting device, a feature matrix based on the at least one codeword candidate;
• and
• determine the precoder based on the feature matrix,
• wherein the at least one selection vector is configured with a same number of elements as the number of the at least one codeword candidate included in a predetermined codebook and includes at least one non-zero element,
• wherein the at least one selection vector specifies a weight-based combination for at least one of the at least one codeword candidate,
• wherein the at least one selection vector is obtained based on a normalized feature matrix, wherein the normalized feature matrix is obtained by applying normalization to the feature matrix, wherein ei*,l which is an l-th element of the at least one selection vector ei* is expressed as in Equation below:
• e
• i
• ★
• ,
• l
• =
• 
• G
• _
• ⁢
• c
• l
• 
• α
• ∑
• j
• =
• 1
• 2
• B
• 
• G
• _
• ⁢
• c
• j
• 
• α
• where, G is the normalized feature matrix,
• cx is a x-th codeword of the at least one codeword candidate,
• 2B corresponds to the number of the at least one codeword candidate,
• α is a predetermined positive real number.