IP Library › Granted Patent US 11,329,745
Granted Patent B2
US 11,329,745 · App. 16/718,574 · Granted May 10, 2022

Dynamically estimating a propagation time between a first node and a second node of a wireless network

Inventors: Meghna Agrawal (Cupertino, CA); Andrew Nuttall (Mountain View, CA)
Assignee: Skylo Technologies, Inc.
H04J3/0661H04B17/364H04B17/391H04W56/004H04W56/0065
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Quick Facts
Patent No.
US 11,329,745
App. No.
16/718,574
Filed
Dec 18, 2019
Granted
May 10, 2022
Kind
B2
Art Unit
2465
USPC
370/503
Abstract

Apparatuses, methods, and systems for dynamically estimating a propagation time between a first node and a second node of a wireless network are disclosed. One method includes receiving, by the second node, from the first node a packet containing a first timestamp representing the transmit time of the packet, receiving, by the second node, from a local time source, a second timestamp corresponding with a time of reception of the first timestamp received from the first node, calculating a time difference between the first timestamp and the second timestamp, storing the time difference between the first timestamp and the second timestamp, calculating a predictive model for predicting the propagation time based the time difference between the first timestamp and the second timestamp, and estimating the propagation time between the first node and the second node at a time by querying the predictive model with the time.

Claims (46)

1. A method of dynamically estimating a propagation time between a first node and a second node of a wireless network, comprising:

a. receiving, by the second node, from the first node a packet containing a first timestamp representing the transmit time of the packet;

b. receiving, by the second node, from a local time source, a second timestamp corresponding with a time of reception of the first timestamp received from the first node;

c. calculating a time difference between the first timestamp and the second timestamp;

d. storing the time difference between the first timestamp and the second timestamp;

e. calculating, by the second node, a predictive model for predicting the propagation time based on the time difference between the first timestamp and the second timestamp;

f. estimating, by the second node, the propagation time between the first node and the second node at a time, comprising querying the predictive model with the time; and

updating the predictive model based on a determined error in estimates of the propagation time.

2. The method of claim 1 , further comprising:

storing a time of the calculating of the time difference;

wherein calculating, by the second node, the predictive model is further based on the time of calculating the time difference.

3. The method of claim 1 , further comprising:

performing steps a, b, c, d, N successive times for N packets; and

calculating, by the second node, the predictive model for predicting the propagation time, based on time differences between the first timestamps and the second timestamps of each of the N packets.

4. The method of claim 3 , wherein the N packets are a running number of packets of a continuous series of packets.

5. The method of claim 1 , further comprising:

estimating, by the second node, additional first time stamps of additional packets based on the first time stamp, and forward integrating counter information provided by the first node.

6. The method of claim 1 , wherein calculating, by the second node, the predictive model for predicting the propagation time based the time difference between the first timestamp and the second timestamp comprises:

selecting a regression model base on a-priori information about characteristics including a cyclic nature of the propagation time between the first node and the second node; and

computing parameters of the regression model based on at least the time difference between the first timestamp and the second timestamp.

7. The method of claim 1 , further comprising identifying a time recent threshold between a time of a last time difference calculation and the time, wherein the time recent threshold is identified based on an estimated rate of change of system dynamics of the first node and the second node.

8. The method of claim 1 , wherein the first node comprises a base station and the second node comprises a hub.

9. The method of claim 8 , wherein a wireless communication link is formed between the base station and the hub.

10. The method of claim 1 , further comprising, the second node, using the predicted propagation time to facilitate wireless communication between the second node and the first node comprising synchronizing reception timing of wireless communication from the second node to the first node.

11. The method of claim 1 , wherein how frequently additional first timestamp and second time stamps are received by the second node is selected based on a determined error in estimates of the propagation time.

12. The method of claim 1 , wherein how frequently additional first timestamp and second time stamps are received by the second node is selected based on at least one of user or hub-initiated commands and configurations, or an ephemeris of a satellite within a wireless link between the second node and the first node.

13. The method of claim 1 , further comprising selecting how frequently to estimate the propagation time between the first node and the second node at additional times, and accordingly querying the predictive model with the future times based on a determined error in estimates of the propagation time.

14. The method of claim 1 , further comprising selecting how frequently to estimate the propagation time between the first node and the second node at additional times, and accordingly querying the predictive model with the future times based on at least one of user or hub-initiated commands and configurations, or an ephemeris of a satellite within a wireless link between the second node and the first node.

15. The method of claim 1 , further comprising updating the predictive model based on at least one of user or hub-initiated commands and configurations, or an ephemeris of a satellite within a wireless link between the second node and the first node.

16. The method of claim 1 , wherein when the estimated propagation time is within an error estimate threshold, then further comprising

receiving, first node, one or more preambles from a set of one or more data sources of the second node during a scheduled time slot;

receiving, by the first node, one or more virtual preambles from a network server during the scheduled time slot, wherein the one or more virtual preambles are associated with another set of one or more data sources of the second node;

generating, by the first node, responses to the preambles and the virtual preambles, wherein the responses included scheduled time and frequency allocations for uplink communication from the set of one or more data sources and the other set of one or more data sources; and

transmitting, by the first node, the responses to the set of one or more data sources and the other set of one or more data sources.

17. A node configured to:

a. receive from a first node a packet containing a first timestamp representing the transmit time of the packet;

b. receive from a local time source, a second timestamp corresponding with a time of reception of the first timestamp received from the first node;

c. calculate a time difference between the first timestamp and the second timestamp;

d. store the time difference between the first timestamp and the second timestamp;

e. calculate a predictive model for predicting the propagation time based on the time difference between the first timestamp and the second timestamp;

f. estimate the propagation time between the first node and the second node at a time, comprising querying the predictive model with the time; and

g. update the predictive model based on a determined error in estimates of the propagation time.

18. The node of claim 17 , wherein the node is further configured to:

perform steps a, b, c, d, N successive times for N packets; and

calculate the predictive model for predicting the propagation time, based on time differences between the first timestamps and the second timestamps of each of the N packets.

19. The node of claim 17 , wherein the node is further configured to select how frequently to estimate the propagation time between the first node and the second node at additional times, and accordingly querying the predictive model with the future times based on a determined error in estimates of the propagation time.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 18, 2019
From: AGRAWAL, MEGHNA; NUTTALL, ANDREW
To: SKYLO TECHNOLOGIES, INC.
Reel/Frame 051318/0012 →
Continuity (3)
Provisional Application 62890553 · Aug 22, 2019
Provisional Application 62914438 · Oct 12, 2019
Related Publication 20210058180A1 · Feb 25, 2021