Granted Patent B2

US 12,665,708 · App. 18/416,225 · Granted Jun 23, 2026

Inventors: Fehmi Emre Kadan (London, GB); Onur Dizdar (London, GB); Stephen Wang (London, GB)

Assignee: VIAVI Solutions Inc.

H04L1/203H04L1/0009H04L1/0026

Abstract

Claims (61)

1 . A method, comprising:

obtaining information associated with one or more targets, wherein the information associated with the one or more targets includes sensing information and a communication performance control parameter;

determining a sensing beampattern based at least in part on the information associated with the one or more targets;

determining a target sensing autocorrelation matrix for the sensing beampattern;

identifying a candidate sensing autocorrelation matrix for a joint communication and sensing transmission based at least in part on the target sensing autocorrelation matrix;

determining a target sensing precoder based at least in part on the candidate sensing autocorrelation matrix; and

generating a joint communication and sensing precoder based at least in part on the target sensing precoder and the communication performance control parameter.

2 . The method of claim 1 , further comprising generating a plurality of joint communication and sensing precoder coefficients using the joint communication and sensing precoder.

3 . The method of claim 2 , wherein generating the plurality of joint communication and sensing precoder coefficients comprises generating the plurality of joint communication and sensing precoder coefficients for a mono-static joint communication and sensing system.

4 . The method of claim 2 , wherein generating the plurality of joint communication and sensing precoder coefficients comprises generating the plurality of joint communication and sensing precoder coefficients for a bi-static joint communication and sensing system.

5 . The method of claim 1 , further comprising:

evaluating, using one or more reference symbols for each user equipment (UE) of a plurality of UEs, a first parameter associated with a Type-1 channel estimation error, wherein the first parameter is based at least in part on a maximum eigenvalue of a covariance matrix for the Type-1 channel estimation error;

evaluating, using one or more channel vectors for each UE of the plurality of UEs, a second parameter associated with a Type-2 channel estimation error, wherein the second parameter is based at least in part on a maximum error norm value for the Type-2 channel estimation error; and

calculating a modified error matrix based at least in part on the first parameter and the second parameter.

6 . The method of claim 5 , further comprising generating a modified joint communication and sensing precoder based at least in part on the modified error matrix, the target sensing precoder, and the communication performance control parameter.

7 . The method of claim 1 , further comprising:

identifying a singular value decomposition of a direct path channel matrix;

calculating a null-space matrix based at least in part on the singular value decomposition of the direct path channel matrix;

evaluating an eigenvalue decomposition of a transformed sensing autocorrelation matrix; and

calculating a modified candidate sensing autocorrelation matrix based at least in part on the eigenvalue decomposition of the transformed sensing autocorrelation matrix.

8 . The method of claim 7 , wherein determining the target sensing precoder based at least in part on the candidate sensing autocorrelation matrix comprises determining the target sensing precoder based at least in part on the modified candidate sensing autocorrelation matrix, wherein the joint communication and sensing precoder is based at least in part on the target sensing precoder.

9 . A device, comprising:

one or more processors configured to:

obtain information associated with one or more targets, wherein the information associated with the one or more targets includes sensing information and a communication performance control parameter;

determine a sensing beampattern based at least in part on the information associated with the one or more targets;

determine a target sensing autocorrelation matrix for the sensing beampattern;

identify a candidate sensing autocorrelation matrix for a joint communication and sensing transmission based at least in part on the target sensing autocorrelation matrix;

determine a target sensing precoder based at least in part on the candidate sensing autocorrelation matrix; and

generate a joint communication and sensing precoder based at least in part on the target sensing precoder and the communication performance control parameter.

10 . The device of claim 9 , wherein the one or more processors are configured to generate a plurality of joint communication and sensing precoder coefficients using the joint communication and sensing precoder.

11 . The device of claim 9 , wherein the one or more processors are configured to:

evaluate, using one or more reference symbols for each user equipment (UE) of a plurality of UEs, a first parameter associated with a Type-1 channel estimation error, wherein the first parameter is based at least in part on a maximum eigenvalue of a covariance matrix for the Type-1 channel estimation error;

evaluate, using one or more channel vectors for each UE of the plurality of UEs, a second parameter associated with a Type-2 channel estimation error, wherein the second parameter is based at least in part on a maximum error norm value for the Type-2 channel estimation error; and

calculate a modified error matrix based at least in part on the first parameter and the second parameter.

12 . The device of claim 11 , wherein the one or more processors are configured to generate a modified joint communication and sensing precoder based at least in part on the modified error matrix, the target sensing precoder, and the communication performance control parameter.

13 . The device of claim 9 , wherein the one or more processors are configured to:

identify a singular value decomposition of a direct path channel matrix;

calculate a null-space matrix based at least in part on the singular value decomposition of the direct path channel matrix;

evaluate an eigenvalue decomposition of a transformed sensing autocorrelation matrix; and

calculate a modified candidate sensing autocorrelation matrix based at least in part on the eigenvalue decomposition of the transformed sensing autocorrelation matrix.

14 . The device of claim 13 , wherein the one or more processors, to determine the target sensing precoder based at least in part on the candidate sensing autocorrelation matrix, are configured to determine the target sensing precoder based at least in part on the modified candidate sensing autocorrelation matrix, wherein the joint communication and sensing precoder is based at least in part on the target sensing precoder.

15 . A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

one or more instructions that, when executed by one or more processors of a device, cause the device to:

obtain information associated with one or more targets, wherein the information associated with the one or more targets includes sensing information and a communication performance control parameter;

determine a sensing beampattern based at least in part on the information associated with the one or more targets;

determine a target sensing autocorrelation matrix for the sensing beampattern;

identify a candidate sensing autocorrelation matrix for a joint communication and sensing transmission based at least in part on the target sensing autocorrelation matrix;

determine a target sensing precoder based at least in part on the candidate sensing autocorrelation matrix; and

generate a joint communication and sensing precoder based at least in part on the target sensing precoder and the communication performance control parameter.

16 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the device to generate a plurality of joint communication and sensing precoder coefficients using the joint communication and sensing precoder.

17 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the device to:

evaluate, using one or more reference symbols for each user equipment (UE) of a plurality of UEs, a first parameter associated with a Type-1 channel estimation error, wherein the first parameter is based at least in part on a maximum eigenvalue of a covariance matrix for the Type-1 channel estimation error;

evaluate, using one or more channel vectors for each UE of the plurality of UEs, a second parameter associated with a Type-2 channel estimation error, wherein the second parameter is based at least in part on a maximum error norm value for the Type-2 channel estimation error; and

calculate a modified error matrix based at least in part on the first parameter and the second parameter.

18 . The non-transitory computer-readable medium of claim 17 , wherein the one or more instructions further cause the device to generate a modified joint communication and sensing precoder based at least in part on the modified error matrix, the target sensing precoder, and the communication performance control parameter.

19 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the device to:

identify a singular value decomposition of a direct path channel matrix;

calculate a null-space matrix based at least in part on the singular value decomposition of the direct path channel matrix;

evaluate an eigenvalue decomposition of a transformed sensing autocorrelation matrix; and

calculate a modified candidate sensing autocorrelation matrix based at least in part on the eigenvalue decomposition of the transformed sensing autocorrelation matrix.

20 . The non-transitory computer-readable medium of claim 19 , wherein determining the target sensing precoder based at least in part on the candidate sensing autocorrelation matrix comprises determining the target sensing precoder based at least in part on the modified candidate sensing autocorrelation matrix, wherein the joint communication and sensing precoder is based at least in part on the target sensing precoder.

Assignments (4)

Continuity (1)

References Cited (20)