Radio access network management application conflict coordination

1 . A method comprising:

receiving, by a processing system including at least one processor, a set of execution requests from a plurality of radio access network applications within a defined period of time, wherein each execution request of the set of execution requests is to perform at least one execution for configuring at least one aspect of a radio access network;

identifying, by the processing system, at least one conflict among at least two of the plurality of radio access network applications;

selecting, by the processing system, in response to the identifying the at least one conflict, at least one modification to the set of execution requests in accordance with a reinforcement learning-based algorithm, wherein the at least one modification comprises changing an order of executions associated with at least two of the execution requests of the set of execution requests; and

performing, by the processing system, at least a first execution associated with the set of execution requests according to the at least one modification to configure at least a first aspect of the radio access network.

2 . The method of claim 1 , wherein the processing system comprises a radio access network intelligent controller.

3 . The method of claim 1 , wherein the plurality of radio access network applications includes at least one of:

at least one open radio access network real-time application; or

at least one open radio access network non-real-time application.

4 . The method of claim 1 , further comprising:

obtaining a plurality of time series comprising metrics for a plurality of network performance indicators for the radio access network; and

identifying pairwise correlation values among the plurality of network performance indicators based upon portions of the plurality of time series associated with a correlation time period.

5 . The method of claim 4 , wherein the identifying of the at least one conflict comprises identifying that the at least two of the plurality of radio access network applications have respective goal functions that target respective network performance indicators having a negative pairwise correlation value with each other.

6 . The method of claim 5 , wherein the respective network performance indicators comprise at least two of:

an uplink throughput;

a downlink throughput;

an energy consumption;

a coverage measure; or

a spectral efficiency.

7 . The method of claim 1 , wherein the identifying of the at least one conflict comprises identifying that the at least two of the plurality of radio access network applications have respective goal functions that target a same network performance indicator.

8 . The method of claim 1 , wherein the identifying of the at least one conflict comprises identifying that the at least two of the execution requests in the set of execution requests are for configuring a same aspect of a radio access network.

9 . The method of claim 1 , wherein the at least one modification further comprises:

omitting an execution associated with at least one execution request of the set of execution requests.

10 . The method of claim 1 , wherein the at least one modification further comprises:

delaying at least one execution associated with at least one execution request of the set of execution requests.

11 . The method of claim 1 , wherein the reinforcement learning-based algorithm comprises a Q-table algorithm.

12 . The method of claim 1 , wherein the reinforcement learning-based algorithm comprises a deep neural network.

13 . The method of claim 1 , wherein the reinforcement learning-based algorithm is in accordance with a defined reward function.

14 . The method of claim 13 , wherein the reinforcement learning-based algorithm includes an exploration of modifications to sets of execution requests as candidate actions to identify changes in outcomes based upon the defined reward function.

15 . The method of claim 14 , wherein the exploration of modifications is in accordance with at least one constraint, and wherein the at least one constraint defines at least one of:

a maximum value or a minimum value for at least one network performance indicator; or

a maximum value or a minimum value for at least one configurable setting of the radio access network.

16 . The method of claim 14 , wherein the at least one modification is selected when it is determined via the reinforcement learning-based algorithm that the at least one modification provides an improved outcome in accordance with the defined reward function as compared to a non-modification of the set of execution requests.

17 . The method of claim 13 , wherein the reinforcement learning-based algorithm includes an exploration of modifications to the defined period of time.

18 . A non-transitory computer-readable medium storing instructions which, when executed by a processing system including at least one processor, cause the processing system to perform operations, the operations comprising:

receiving a set of execution requests from a plurality of radio access network applications within a defined period of time, wherein each execution request of the set of execution requests is to perform at least one execution for configuring at least one aspect of a radio access network;

identifying at least one conflict among at least two of the plurality of radio access network applications;

selecting, in response to the identifying the at least one conflict, at least one modification to the set of execution requests in accordance with a reinforcement learning-based algorithm, wherein the at least one modification comprises changing an order of executions associated with at least two of the execution requests of the set of execution requests; and

performing at least a first execution associated with the set of execution requests according to the at least one modification to configure at least a first aspect of the radio access network.

19 . An apparatus comprising:

a processing system including at least one processor; and

a computer-readable medium storing instructions which, when executed by the processing system, cause the processing system to perform operations, the operations comprising:

receiving a set of execution requests from a plurality of radio access network applications within a defined period of time, wherein each execution request of the set of execution requests is to perform at least one execution for configuring at least one aspect of a radio access network;

identifying at least one conflict among at least two of the plurality of radio access network applications;

selecting, in response to the identifying the at least one conflict, at least one modification to the set of execution requests in accordance with a reinforcement learning-based algorithm, wherein the at least one modification comprises changing an order of executions associated with at least two of the execution requests of the set of execution requests; and

performing at least a first execution associated with the set of execution requests according to the at least one modification to configure at least a first aspect of the radio access network.

20 . The apparatus of claim 19 , wherein the plurality of radio access network applications includes at least one of:

at least one open radio access network real-time application; or

at least one open radio access network non-real-time application.