Facilitating sparsity adaptive feedback in the delay doppler domain in advanced networks
Facilitating sparsity adaptive feedback in the delay doppler domain in advanced networks (e.g., 4G, 5G, 6G, and beyond) is provided herein. Operations of a method can comprise determining, by a first device comprising a processor, a channel covariance matrix in a time-frequency domain based on a channel estimation associated with reference signals received from a second device. The method also can comprise decomposing, by the first device, the channel covariance matrix into a group of component matrices. Further, the method can comprise transforming, by the first device, respective matrices of the group of component matrices into respective covariance matrices in a delay doppler domain. The method also can comprise determining, by the first device, channel state information feedback in the delay doppler domain.
1. A method, comprising:
decomposing, by a device comprising a processor, covariance matrices into a first covariance matrix, a second covariance matrix, and at least a third covariance matrix, wherein the covariance matrices are in a time-frequency domain based on a channel estimation; and
determining, by the device, a group of covariance matrices in a delay doppler domain as a function of respective transforms applied to the first covariance matrix, the second covariance matrix, and the third covariance matrix.
2. The method of claim 1 , wherein the determining comprises exploiting an invariance and sparsity of a channel in the delay doppler domain.
3. The method of claim 2 , wherein the exploiting comprises mitigating overhead in a communications network.
4. The method of claim 1 , wherein the determining comprises using a feedback compression protocol that exploits an invariance and sparsity of a channel in the delay doppler domain.
5. The method of claim 4 , further comprising:
performing, by the device, feedback based on a delay doppler transformation of the group of covariance matrices of the channel; and
subsampling, by the device, a delay-doppler grid, wherein the subsampling decreases feedback overhead.
6. The method of claim 1 , wherein the decomposing comprises decomposing the covariance matrices into a vertical domain, a horizontal domain, and an uncorrelated domain.
7. The method of claim 1 , further comprising:
performing, by the device, grid subsampling on the group of covariance matrices in the delay doppler domain; and
transmitting, by the device to network equipment, quantized feedback based on the performing.
8. The method of claim 1 , wherein the determining comprises applying respective symplectic fourier transforms to matrices in the group of covariance matrices.
9. The method of claim 8 , wherein the respective symplectic fourier transforms relate a delay Doppler matrix to a reciprocal time frequency.
10. The method of claim 1 , further comprising:
sorting, by the device, samples in a delay doppler grid according to respective values of norm functions of the samples;
assigning, by the device, feedback bits to the samples based on the respective norm values; and
conveying, by the device, a first group of samples selected from the samples based on the feedback bits.
11. The method of claim 1 , further comprising:
determining, by the device, a codebook according to a location of a covariance matrix and an associated value of a norm function in a delay doppler grid.
12. The method of claim 1 , wherein the decomposing comprises decomposing the group of covariance matrices based on a structure of an antenna grid at network equipment.
13. The method of claim 1 , wherein the device is configured to operate according to a fifth generation communication protocol.
14. A system, comprising:
a processor; and
a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising:
transforming respective matrices of a group of component matrices into respective covariance matrices in a delay doppler domain, wherein the group of component matrices are based on a decomposition of a channel covariance matrix in a time-frequency domain; and
determining channel state information feedback in the delay doppler domain.
15. The system of claim 14 , wherein the decomposing comprises using a feedback compression protocol that exploits an invariance and sparsity of a channel in the delay doppler domain.
16. The system of claim 15 , wherein the operations further comprise:
performing feedback based on a delay doppler transformation of the channel covariance matrix; and
subsampling a delay-doppler grid, wherein the subsampling decreases feedback overhead.
17. The system of claim 14 , wherein the decomposing comprises decomposing the covariance matrices into a vertical domain, a horizontal domain, and an uncorrelated domain.
18. A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising:
decomposing a channel covariance matrix into a group of component matrices, wherein the channel covariance matrix is in a time-frequency domain; and
determining channel state information feedback in a delay doppler domain based on a transformation of respective matrices of the group of component matrices into respective covariance matrices in the delay doppler domain.
19. The non-transitory machine-readable medium of claim 18 , wherein the operations further comprise applying respective symplectic fourier transforms to the respective matrices, and wherein the respective symplectic fourier transforms convert reciprocal time frequency into a delay doppler matrix.
20. The non-transitory machine-readable medium of claim 18 , wherein the operations further comprise:
selecting points from a group of points on a delay doppler grid, wherein a point corresponds to a covariance matrix;
selecting a precoding matrix index from a group of defined matrices based on the points; and
indicating the precoding matrix index to network equipment based on a feedback code-book based procedure.