US2023224237A1PendingUtilityA1

Automated network control systems that adapt network configurations based on the local network environment

Assignee: INTEL CORPPriority: Jun 26, 2020Filed: Dec 28, 2022Published: Jul 13, 2023
Est. expiryJun 26, 2040(~13.9 yrs left)· nominal 20-yr term from priority
H04W 36/302H04L 41/0681H04L 41/0886H04W 24/04H04L 45/08H04L 41/0645H04L 41/065H04L 41/12H04L 41/0823H04L 41/0816H04L 41/145G06N 3/049G06N 3/08H04W 28/0236H04W 28/0278H04W 24/02H04W 40/02Y02D30/70H04W 24/06H04L 41/16H04W 52/245
70
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Claims

Abstract

Systems, apparatuses and methods may provide for technology that adjusts, via a short-term subsystem, a communications parameter for one or more of wireless communication devices based on data from one or more of a plurality of sensors. The technology may also determine, via a neural network, a prediction of future performance of the wireless network based on a state of the network environment, wherein the state of the network environment includes information from the short-term subsystem and location information about the wireless communication devices and other objects in the environment, and determine a change in network configuration to improve a quality of communications in the wireless network based on the prediction of future performance of the wireless network. The technology may further generate generic path loss models based on time-stamped RSSI maps and record a sequence of events that cause a significant drop in RSSI to determine a change in network configuration.

Claims

exact text as granted — not AI-modified
1 . (canceled) 
     
     
         2 . An apparatus comprising:
 an interface;   instructions in the apparatus;   programmable circuitry to execute the instructions to at least:
 access wireless communication information from an access point, the access point in a wireless network within a first environment; 
 analyze the wireless communication information based at least in part on a received signal strength indicator (RSSI) within the wireless network, the RSSI predicted by a neural network of the apparatus, the neural network trained using reinforcement learning; 
 detect a condition of the wireless network based on analysis of the wireless communication information; and 
 change a setting of the access point based on the detected condition. 
   
     
     
         3 . The apparatus of  claim 2 , wherein the access point is a first access point and the wireless communication information includes information related to communications transmitted by a second access point, the second access point different from the first access point. 
     
     
         4 . The apparatus of  claim 3 , wherein the information related to communications transmitted by the second access point is sniffed by the first access point. 
     
     
         5 . The apparatus of  claim 2 , wherein the updated setting updates operation of the wireless access point instantaneously. 
     
     
         6 . The apparatus of  claim 2 , wherein the programmable circuitry is to cause the access point to use the updated setting. 
     
     
         7 . The apparatus of  claim 2 , wherein the programmable circuitry is to update the setting to change a transmission power of the access point. 
     
     
         8 . The apparatus of  claim 2 , wherein the programmable circuitry is to update the setting to change a wireless transmission channel of the access point. 
     
     
         9 . The apparatus of  claim 2 , wherein the programmable circuitry is to detect a location of an object using the wireless communication information. 
     
     
         10 . At least one non-transitory computer readable storage medium comprising instructions to cause processor circuitry to at least:
 access wireless communication information from an access point, the access point in a wireless network within a first environment;   analyze the wireless communication information based at least in part on a received signal strength indicator (RSSI) within the wireless network, the RSSI predicted by a neural network, the neural network trained using reinforcement learning;   detect a condition of the wireless network based on analysis of the wireless communication information; and   change a setting of the access point based on the detected condition.   
     
     
         11 . The at least one non-transitory computer readable storage medium of  claim 10 , wherein the access point is a first access point and the wireless communication information includes information related to communications transmitted by a second access point, the second access point different from the first access point. 
     
     
         12 . The at least one non-transitory computer readable storage medium of  claim 11 , wherein the information related to communications transmitted by the second access point is sniffed by the first access point. 
     
     
         13 . The at least one non-transitory computer readable storage medium of  claim 10 , wherein the updated setting updates operation of the wireless access point instantaneously. 
     
     
         14 . The at least one non-transitory computer readable storage medium of  claim 10 , wherein the instructions are to cause the processor circuitry to cause the access point to use the updated setting. 
     
     
         15 . The at least one non-transitory computer readable storage medium of  claim 10 , wherein the instructions cause the processor circuitry to update the setting to change a transmission power of the access point. 
     
     
         16 . The at least one non-transitory computer readable storage medium of  claim 10 , wherein the instructions cause the processor circuitry to update the setting to change a wireless transmission channel of the access point. 
     
     
         17 . The at least one non-transitory computer readable storage medium of  claim 10 , wherein the instructions are to cause the processor circuitry to detect a location of an object using the wireless communication information. 
     
     
         18 . A method comprising:
 accessing wireless communication information from an access point, the access point in a wireless network within a first environment;   analyzing, by executing an instruction with at least one processor, the wireless communication information based at least in part based on a received signal strength indicator (RSSI) within the wireless network, the RSSI predicted by a neural network, the neural network trained using reinforcement learning;   detecting a condition of the wireless network based on analysis of the wireless communication information; and   change a setting of the access point based on the detected condition.   
     
     
         19 . The method of  claim 18 , wherein the access point is a first access point and the wireless communication information includes information related to communications transmitted by a second access point, the second access point different from the first access point. 
     
     
         20 . The method of  claim 19 , wherein the information related to communications transmitted by the second access point is sniffed by the first access point. 
     
     
         21 . The method of  claim 18 , wherein the updated setting updates operation of the wireless access point instantaneously. 
     
     
         22 . The method of  claim 18 , further including causing the access point to use the updated setting. 
     
     
         23 . The method of  claim 18 , wherein the updated setting includes a change to a transmission power of the access point. 
     
     
         24 . The method of  claim 18 , wherein the updated setting includes a change to a wireless transmission channel of the access point. 
     
     
         25 . The method of  claim 18 , further including detecting a location of an object using the wireless communication information.

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