Patent Application

App. No. 18/807,067

Abstract

Claims (237)

1 . A method for optimizing service-level-policy-based network performance management in a 5G wireless network slice, comprising

analyzing, by a slice analytics module, a target slice throughput of the slice in comparison to an observed slice throughput of the slice to compute a slice-throughput error function; and

updating, by the slice analytics module, based on at least the slice-throughput error function, at least one of the following: i) radio resource management policy maximum ratio (rRMPolicyMaxRatio) for the slice; ii) radio resource management policy minimum ratio (rRMPolicyMinRatio) for the slice; and iii) radio resource management policy dedicated ratio (rRMPolicyDedicatedRatio) for the slice.

2 . The method of claim 1 , further comprising at least one of:

i) along with updating the rRMPolicyMaxRatio, further updating a corresponding shared pool of resource blocks (RBs) for the slice;

ii) along with updating the rRMPolicyMinRatio, further updating a corresponding prioritized pool of RBs for the slice; and

iii) along with updating the rRMPolicyDedicatedRatio, further updating a corresponding dedicated pool of RBs for the slice.

3 . The method of claim 1 , wherein the updating comprises at least one of:

i) increasing the rRMPolicyMaxRatio for the slice;

ii) decreasing the rRMPolicyMaxRatio for the slice;

iii) increasing the rRMPolicyMinRatio for the slice;

iv) decreasing the rRMPolicyMinRatio for the slice;

v) increasing the rRMPolicyDedicatedRatio for the slice; and

vi) decreasing the rRMPolicy DedicatedRatio for the slice.

4 . The method of claim 1 , wherein the slice analytics module is at a near-RT RIC 161 , the method further comprising:

subscribing, at the near-RT RIC 161 , to slice-related parameters, from an E2 node;

receiving the slice-related parameters the near-RT RIC 161 from the E2 node;

analyzing, by slice analytics module, the slice-related parameters to determine an adaptive action for the updating; and

communicating the adaptive action to the E2 node.

5 . The method of claim 4 , wherein the near-RT RIC 161 receives the slice-related parameters from the E2 node periodically or on an event basis.

6 . The method of claim 4 , wherein the E2 node is a Distributed Unit (DU), and the slice-related parameters comprise at least one of:

an observed throughput of the slice;

a number of Data Radio Bearers (DRBs) or logical channels for each 5G Quality of Service Identifier (5QI) type corresponding to the slice;

an average Channel Quality Indicator (CQI) for a current reporting interval, where the CQI is indicated by a User Equipment (UE) 101 to a gNodeB (gNB) 106 ;

a fraction of DRBs for each 5QI j for which a Quality of Service (QOS) requirement cannot be met by the DU 152 ;

a dedicated, prioritized, and shared pool of (Resource Blocks) RBs for the slice;

utilized RBs from the dedicated, prioritized, and shared pool of RBs for the slice;

a number of RBs used for each 5QI type corresponding to the slice;

an RB utilization in the cell;

A location info each of the UEs 101 ; and

weights used to compute a scheduling metric for each of the DRBs or logical channels at the DU 152 .

7 . The method of claim 4 , wherein the E2 node is a Centralized Unit (CU), and the slice-related parameters comprise at least one of:

a number of UEs 101 which are supporting Protocol Data Unit (PDU) sessions corresponding to the slice;

the RMPolicyDedicatedRatio, the rRMPolicyMinRatio, and the rRMPolicyMaxRatio for a number of the PDU sessions for the slice;

utilization of resources in terms of the number of PDU sessions;

a fraction of DRBs for each 5QI for which QoS requirements cannot be met in the CU 151 and over a CU-DU mid-haul; and

location information for each UE 101 corresponding to the slice.

8 . The method of claim 4 , wherein the E2 node is a CU, wherein the adaptive action comprises at least one of:

changing rRMDedicatedRatio or rRMPolicyMinRatio or rRMPolicyMaxRatio for RBs for a subset of slices; and

changing of a plurality of weights that are used to compute a scheduling metric for each of a plurality of logical channels.

9 . The method of claim 1 , wherein the slice analytics module is at a Centralized Unit-User Plane (CU-UP), the method further comprising:

configuring a slice Service Level Agreement (SLA) at an operator slice management module;

communicating the slice SLA from a slice management module to a Radio Access Network (RAN) management module;

communicating the Slice SLA to the CU-CP;

analyzing, at the CU-CP the slice SLA and providing a CU-CP an initial estimate of resources needed for the slice for the update;

communicating slice-related parameters from the CU-CP to DU;

communicating, by the CU-CP, slice-related performance measures to CU-CP;

analyzing, by the slice analytics module at CU-CP, slice-related performance measures that it received from the CU-CP and from the DU; and

if the slice analytics module determines it can optimize performance of some slices, changing the values of slice-related parameters to improve performance, and specifying a time from which these new parameters can be applied.

10 . The method of claim 1 , further comprising:

continuously analyzing slice-related performance measures at the E2 node; and

performing data analytics at the slice analytics module;

wherein the data analytics comprises computing a plurality of error functions for each slice k over M training data instances, including at least one of:

a) comparing the target slice throughput error with the observed slice throughput; and

b) analyzing delay-sensitive applications and comparing a target number of data radio bearers (DRBs) which should meet the delay requirements with an observed number of data radio bearers (DRBs) which meet their delay requirements.

11 . The method of claim 10 , further comprising:

computing the plurality of error functions as least square functions.

12 . The method of claim 11 , further comprising:

for a), the slice analytics module computes the plurality of error functions as:

E

k

SliceThroughput

(

n

)

=

∑

i

=

1

M

E

k

i

R

k

SliceThroughput

(

n

)

=

∑

i

=

1

M

R

k

i

13 . The method of claim 11 , further comprising:

for b), the slice analytics module computes the plurality of error functions as delay-related error functions:

E

k

SliceDRBDelay

(

n

)

=

∑

i

=

1

M

E

k

i

R

k

SliceDRBDelay

(

n

)

=

∑

i

=

1

M

R

k

i

14 . The method of claim 10 , further comprising:

updating, at the slice analytics module, the rRMPolicyMaxRatio or a corresponding shared pool of RBs, or both.

15 . The method of claim 14 , wherein the slice analytics module i) selectively updates the rRMPolicyMaxRatio for a slice or ii selectively updates a corresponding shared pool of RBs, or both i and ii.

16 . The method of claim 15 , further comprising:

updating, at the slice analytics module, the rRMPolicyMinRatio, or a corresponding shared pool of RBs, or both.

17 . The method of claim 16 , wherein the slice analytics module:

identifies a difference in the slice-throughput error function, E k SliceThroughput for consecutive time intervals and sets an I k SliceThroughput , and

updates or maintains the rRMPolicyMinRatio for slice k based on the slice-throughput error function.

18 . The method of claim 17 , wherein the slice analytics module:

if the I k SliceThroughput is equal to zero and an I k SliceDRBDelay is equal to zero, identifies a difference in a next error functions slice-throughput error function error, R k SliceThroughput , and a next delay-related error functions: R k SliceDRBDelay for consecutive time intervals; and

updates or maintains the rRMPolicyMinRatio for slice k based on the next slice-throughput error function error, R k SliceThroughput and the next delay-related error functions: R k SliceDRBDelay .

19 . The method of claim 17 wherein:

the slice-analytics module updates the rRMPolicyDedicatedRatio for slice k as:

maxAllowedrRMPolicyMinRatio

k

⁢

(

n

+

γ

d

+

1

)

=

minimum

⁢

{

rRMPolicyMinRatio_II

k

⁢

(

n

+

γ

d

+

1

)

,

maxAllowedrRMPolicyMinRatio

k

⁢

(

n

+

γ

d

+

1

)

}

where,

rRMPolicyMinRatio_II k (n+Y d +1)=(1+θ k ) q1 *rRMPolicyMinRatio(n)*I k SliceThroughput +(1+θ k d ) q1 *rRMPolicyMinRatio(n)*I k sliceDRBDelay

and max AllowedrRMPolicyMinRatiok (n+Y d +1) is the maximum rRMPolicyMinRatio permitted for slice k in the time interval (n+Y d +1)},

where

i) Y d is greater than or equal to one and “q” is also greater than or equal to 1;

ii) Y d can be chosen to be higher than “8”

iii) θ k for each slice k is chosen to be between 0 and 1,

iv) θ k d for each slice k is chosen to be between 0 and 1

v) q is between 0 and 1, and

vi) q1 is between 0 and 1.

20 . The method of claim 17 wherein:

the slice-analytics module updates the rRMPolicyDedicatedRatio for slice k as:

rRMPolicyDedicatedRatio

k

⁢

(

n

+

γ

d

+

1

)

=

minimum

⁢

{

rRMPolicyDedicatedatRatio_II

k

⁢

(

n

+

γ

d

+

1

)

,

maxAllowedrRMPolicyDecicatedRatio

k

⁢

(

n

+

γ

d

+

1

)

}

where

rRMPolicyDedicatedRatio_II k (n+Y d +1)=(1+(θ k −ε k ))*

rRMPolicyDedicatedRatio(n)*I k SliceThroughput +(1+(θ k d −ε k d ))*

rRMPolicyDedicatedRatio(n)*I k sliceDRBDelay ,

and

maxAllowedrRMPolicyDedicatedRatio k (n+Y d +1) is a maximum

rRMPolicyDedicatedRatio permitted for slice k in the time interval (n+Y d +1)} where

i) Y_d is greater than or equal to one and “q” is also greater than or equal to 1,

ii) Y_d can be chosen to be higher than “8”,

iii) (θ k −ε k ), where ε k is chosen to be between 0 and θ k ,

iv) (θ k d −ε k d ), where ε k d is chosen to be between 0 and θ k d )

v) q is 1, and

vi) q1 is 1.

Assignments (14)