Systems, apparatus, articles of manufacture, and methods for private network mobility management
Methods, apparatus, systems, and articles of manufacture are disclosed for private network mobility management. An example private network in a box includes interface circuitry to communicate with multi-access terrestrial network (TN) nodes and non-terrestrial network (NTN) nodes, machine readable instructions, and programmable circuitry. The example programmable circuitry is to generate a first mesh associated with a geographical area of the private network and a second mesh associated with the geographical area. The example programmable circuitry is also to initiate at least one of the multi-access TN nodes in alignment with the first mesh and at least one of the NTN nodes in alignment with the second mesh. Additionally, the example programmable circuitry is to facilitate communication associated with at least one user equipment within at least one of the first mesh or the second mesh using the private network.
1 . A private network comprising:
interface circuitry to communicate with multi-access terrestrial network (TN) nodes which support a first communication access medium and non-terrestrial network (NTN) nodes which support a second communication access medium;
machine readable instructions; and
at least one programmable circuit to be programmed by the machine readable instructions to:
generate a first grid for a first portion of a geographical area of the private network covered by the multi-access TN nodes and a second grid for a second portion of the geographical area covered by the NTN nodes;
based on a predicted location of a user equipment (UE) relative to the first grid and the second grid, predict respective likelihoods of providing a stable connection between the UE and the private network via the first and second communication access mediums; and
authorize the UE to access the private network via one of the first or second communication access mediums that is predicted to have a highest likelihood.
2 . The private network of claim 1 , wherein the private network is included in a single enclosure.
3 . The private network of claim 1 , wherein one or more of the at least one programmable circuit is to generate the first grid based on location data received from the multi-access TN nodes.
4 . The private network of claim 1 , wherein one or more of the at least one programmable circuit is to:
determine a first quantity of the multi-access TN nodes to serve the UE within the geographical area; and
determine a second quantity of the NTN nodes to serve the UE within the geographical area.
5 . The private network of claim 1 , wherein one or more of the at least one programmable circuit is to predict the predicted location of the UE based on a machine learning model, a motion vector of the UE, and a current location of the UE.
6 . The private network of claim 5 , wherein one or more of the at least one programmable circuit is to:
measure respective characteristics of transmissions of reference signals received from the UE via the first and second communication access mediums;
for each of the first and second communication access mediums, predict a likelihood of providing the stable connection between the UE and the private network based on (1) the predicted location of the UE relative to one of the first grid or the second grid and (2) the respective characteristics; and
select the first communication access medium as the one of the first or second communication access mediums responsive to the first communication access medium having a larger likelihood than the second communication access medium.
7 . The private network of claim 6 , wherein the respective characteristics include respective powers and respective qualities of the transmissions of the reference signals in the first and second communication access mediums.
8 . The private network of claim 5 , wherein one or more of the at least one programmable circuit is to determine the current location of the UE while the UE is in a state of connectivity with the private network that does not require communications related to a data plane or a control plane of the private network.
9 . The private network in a box of claim 1 , wherein one or more of the at least one programmable circuit is to determine a location of the with increased resolution as a level of connectivity between the UE and the private network increases.
10 . A non-transitory computer readable medium comprising instructions to cause at least one programmable circuit of a private network to:
cause interface circuitry of the private network to communicate with multi-access terrestrial network (TN) nodes which support a first communication access medium and non-terrestrial network (NTN) nodes which support a second communication access medium;
generate a first grid for a first portion of a geographical area of the private network covered by the multi-access TN nodes and a second grid for a second portion of the geographical area covered by the NTN nodes;
based on a predicted location of a user equipment (UE) relative to the first grid and the second grid, predict respective likelihoods of providing a stable connection between the UE and the private network via the first and second communication access mediums; and
authorize the UE to access the private network via one of the first or second communication access mediums that is predicted to have a highest likelihood.
11 . The non-transitory computer readable medium of claim 10 , wherein the instructions cause one or more of the at least one programmable circuit to generate the first grid based on location data received from the multi-access TN nodes.
12 . The non-transitory computer readable medium of claim 10 , wherein the instructions cause one or more of the at least one programmable circuit to:
determine a first quantity of the multi-access TN nodes to serve the UE within the geographical area; and
determine a second quantity of the NTN nodes to serve the UE within the geographical area.
13 . The non-transitory computer readable medium of claim 10 , wherein the instructions cause one or more of the at least one programmable circuit circuitry to predict the predicted location of the UE based on a machine learning model, a motion vector of the UE, and a current location of the UE.
14 . The non-transitory computer readable medium of claim 10 , wherein the instructions cause one or more of the at least one programmable circuit to:
measure respective characteristics of transmissions of reference signals received from the UE via the first and second communication access mediums;
for each of the first and second communication access mediums, predict a likelihood of providing the stable connection between the UE and the private network based on (1) the predicted location of the UE relative to one of the first grid or the second grid and (2) the respective characteristics; and
select the first communication access medium as the one of the first or second communication access mediums responsive to the first communication access medium having a larger likelihood than the second communication access medium.
15 . The non-transitory computer readable medium of claim 14 , wherein the respective characteristics include respective powers and respective qualities of the transmissions of the reference signals in the first and second communication access mediums.
16 . The non-transitory computer readable medium of claim 13 , wherein the instructions cause one or more of the at least one programmable circuit circuitry-to determine the current location of the UE while the UE is in a state of connectivity with the private network that does not require communications related to a data plane or a control plane of the private network.
17 . The non-transitory computer readable medium of claim 10 , wherein the instructions cause one or more of the at least one programmable circuit to determine a location of the UE with increased resolution as a level of connectivity between the UE and the private network increases.
18 . A method comprising:
generating, by executing an instruction with at least one programmable circuit of a private network in a box, a first grid for a first portion of a geographical area of the private network covered by multi-access terrestrial network (TN) nodes in communication with interface circuitry of the private network in a box via a first communication access medium and a second grid for a second portion of the geographical area of the private network covered by non-terrestrial network (NTN) nodes in communication with the interface circuitry via a second communication access medium;
based on a predicted location of a user equipment (UE) relative to the first grid and the second grid, predicting, by executing an instruction with one or more of the at least one programmable circuit, respective likelihoods of providing a stable connection between the UE and the private network via the first and second communication access mediums; and
authorizing, by executing an instruction with one or more of the at least one programmable circuit, the UE to access the private network via one of the first or second communication access mediums that is predicted to have a highest likelihood.
19 . The method of claim 18 , further including predicting, the predicted location of the UE based on a machine learning model, a motion vector of the UE, and a current location of the UE.
20 . The method of claim 18 , further including:
measuring respective characteristics of transmissions of reference signals received from the UE via the first and second communication access mediums;
for each of the first and second communication access mediums, predicting a likelihood of providing the stable connection between the UE and the private network based on (1) the predicted location of the UE relative to one of the first grid or the second grid and (2) the respective characteristics; and
selecting the first communication access medium as the one of the first or second communication access mediums responsive to the first communication access medium having a larger likelihood than the second communication access medium.