US2021112425A1PendingUtilityA1

Cellular system

Assignee: TRAN BAOPriority: Sep 2, 2019Filed: Sep 16, 2020Published: Apr 15, 2021
Est. expirySep 2, 2039(~13.1 yrs left)· nominal 20-yr term from priority
Inventors:Bao TranHa Tran
B64U 2201/102G06N 3/0495G06N 3/096G06N 3/0464G06N 3/082G06N 3/09H04B 7/0695B64U 2101/23B64U 10/13B64D 39/00B64B 2201/00G06N 3/063G06N 20/10G06N 3/08H04B 17/12H04W 16/28H04B 7/0617G06N 20/00H04B 17/318B64C 39/024
60
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Claims

Abstract

A system includes one or more antennas; and a processor coupled to the antennas in communication with a predetermined target using 5G protocols.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A system, comprising:
 one or more antennas to focus on one or more predetermined targets;   one or more millimeter wave transceivers coupled to the one or more antennas; and   a processor to control the one or more transceivers and one or more antennas in communication with the predetermined target using 5G protocols.   
     
     
         2 . The system of  claim 1 , wherein the processor calibrates a radio link between a transceiver and a client device. 
     
     
         3 . The system of  claim 1 , wherein the processor is coupled to fiber optics cable to communicate with a cloud-based radio access network (RAN) or a remote RAN. 
     
     
         4 . The system of  claim 1 , comprising an edge neural network that performs predictive maintenance, remote monitoring, video surveillance, voice processing, behavior analytics, situational awareness, and contextual awareness. 
     
     
         5 . The system of  claim 1 , comprising an edge processor that performs predictive maintenance, remote monitoring, video surveillance, voice processing, behavior analytics, situational awareness, and contextual awareness. 
     
     
         6 . The system of  claim 5 , wherein the housing comprises a second moveable surface, each opposing surface has at least one antenna thereon. 
     
     
         7 . The system of  claim 1 , wherein the processor moves MEMS actuators or motors coupled to the antennas. 
     
     
         8 . The system of  claim 1 , wherein each antenna is independently steerable. 
     
     
         9 . The system of  claim 1 , comprising one or more Fresnel lenses to improve signal to noise ratio (SNR). 
     
     
         10 . The system of  claim 1 , wherein processor focuses 5G signals to the target with iterative changes in orientations of the antennas. 
     
     
         11 . The system of  claim 1 , comprising a neural network coupled to a control plane, a management plane, or a data plane to optimize 5G parameters. 
     
     
         12 . The system of  claim 1 , comprising one or more cameras and sensors to capture security information. 
     
     
         13 . The system of  claim 1 , comprising a drop in replacement housing to upgrade 3G or 4G components to 5G or 6G components. 
     
     
         14 . The system of  claim 1 , comprising a camera for individual identity identification. 
     
     
         15 . The system of  claim 1 , wherein the processor analyzes walking gaits and facial features for identity identification. 
     
     
         16 . The system of  claim 1 , wherein the processor analyzes sound captured using a microphone to determine events in progress. 
     
     
         17 . The system of  claim 1 , comprising an edge processor to provide local edge processing for Internet-of-Things (IOT) sensors. 
     
     
         18 . The system of  claim 1 , comprising an edge learning machine that uses pre-trained models and modifies the pre-trained models for a selected task. 
     
     
         19 . The system of  claim 1 , comprising a cellular device for a person crossing a street near the city light or street light, the cellular device emitting a person to vehicle (P2V) or a vehicle to person (V2P) safety message. 
     
     
         20 . The system of  claim 1 , comprising a cloud trained neural network whose network parameters are down-sampled and filter count reduced before transferring to the edge neural network.

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