Amazon Technologies, Inc.

Jungtao Liu

Rongsheng Huang

Koohyun Um

Hongbo Tian

Varadarajan Gopalakrishnan

Yinghua Ye

Avinash Joshi

Kun Ting Tsai

Morris Yuanhsiang Hsu

Ravi Ichapurapu

Chiu Ngok Eric Wong

Pratik Kalpesh Patel

Jin Dong Kim

Shao-Cheng Wang

Andrew David Price

Peruvemba Ranganathan Sai Ananthanarayanan

Sean C Murphy

Sachin Rajendra Kothari

Varada Gopalakrishnan

Songping Wu

Lori Yoshida

Sheung Mei Chan

Durgaprasad Kashinath Shamain

Stefan Mathias Hutchison

Sudheep Thota

Celalettin Umit Bas

Vipul Jain

Chirag Bhavsar

Systems, methods, and computer-readable media are disclosed for mitigating microwave interference in electronic devices. Example devices may include memory and at least one processor configured to access the memory and execute computer-executable instructions to determine that a microwave source is inactive, transmit a second message to the access point requesting the access point to send the data, receive, from the access point, the data buffered during the first duration, and transmit a third message to the access point, the third message cancelling the buffer request of the first message.

Mitigation of microwave interference

A multi-radio service of a provider network may be used to manage and route payloads for client edge devices that use multiple types of radios. The multi-radio service may associate different types of radio controllers with an edge device of a client, so that messages that are transmitted from different types of edge device radios can be handled by different radio controllers. A radio controller may receive a message and extract the payload from the message based on the data/data format specific to the radio protocol used to transmit the message. When a client-owned cloud application sends a payload to an edge device, the multi-radio service may select, based on criteria (e.g., fastest data transmission), the radio of the edge device from multiple available radios. The corresponding radio controller may then generate and send a message to the selected radio of the edge device (e.g., via a corresponding gateway).

Managing and routing payloads for client edge devices that use multiple types of radios

An IoT service of a provider network may be used to optimize downlink scheduling for edge devices that use a radio communication protocol (e.g., LoRaWAN). A processing instance receives DL packets from a client application that are to be sent to an edge device. The processing instance adds metadata entries (device ID, message ID) to a metadata queue and stores the DL packets into a data store. A scheduling instance obtains a metadata entry and the associated DL packet, formats the DL packet based on edge device information, and publishes the packet to a gateway topic. A separate connection instance receives the formatted DL packet and sends it to a gateway of the client network.

Downlink scheduling optimization for edge devices that use a radio communication protocol

An IoT service of a provider network may be used to provision edge devices with duplicate device identifiers for edge devices that use a radio communication protocol (e.g., LoRaWAN). This may allow a service provider to accept legitimate registration requests from edge devices instead of automatically rejecting them. When the IoT service receives a registration request, the service determines whether there are other devices registered with the same device ID. If so, then the service determines whether to accept or reject the request. For example, the service may determine whether the number of duplicate device IDs being used for registered devices will remain within a predefined threshold if the device is registered. If so, then the service registers the device. Otherwise, the service rejects the request.

Managing duplicate device identifiers for edge devices of client networks that use a radio communication protocol

An IoT service of a provider network may be used to increase the edge device address space while complying with a radio communication protocol. This may allow a service provider to manage a much larger number of client devices that use a particular radio communication protocol that specifies a limited address space (e.g., LoRaWAN). When the IoT service receives a join request via a private gateway of the client network, the service determines, based on the private gateway ID, the client ID of the client that owns the private gateway/client network. The service may generate a unique internal ID for the edge device by combining the client ID with an assigned device ID. The internal ID identifies the edge device as an activated device of the edge network.

Increasing edge device address space while complying with a radio communication protocol

A group of devices connected on a wireless local area network (WLAN) operate in conjunction with one another to present content. Devices in the group may be wirelessly connected via personal area network (PAN) to other devices, such as speakers. An election process is used to select a primary device. The primary device may receive content from an external source, such as a server, and distribute that content to other devices within the group via the WLAN. The parameters of that distribution, such as a content rate indicative of a bitrate of the content, transfer limit rate, and so forth are configured to preserve fidelity of the presentation while minimizing interruptions to presentation that may result due to frequency contention between the WLAN and the PAN, traffic on the WLAN, and so forth.

Bandwidth estimation and management for connected devices

A system that can determine states of human activity and transitions between those states using wireless signal data. A machine learning model such as a Hidden Markov Model (HMM) may be trained to determine transitions between states of human activity (e.g., static, slow movement, fast movement) using information from wireless signal data, such as channel state information gathered from Wi-Fi signal beacons. Depending on the state of the human activity the system may then cause certain commands to be executed corresponding to the human activity such as turning on a certain configuration of lights, playing certain music, or the like.

Human activity and transition detection

Embodiments herein describe a scanning station for identifying an air gap between one or more items stored in a container (e.g., a cardboard box) and a surface of the container (e.g., a top lid of the cardboard box). After identifying the air gap, in one embodiment, the scanning station provides instructions to a downstream cutting station where the container is cut opened. In one embodiment, the scanning station includes one or more articulating arms that each includes a scanner (e.g., a radar sensor) attached on an end of the articulating arm facing the container. Moving the articulating arms along the boundaries of the container provides a 3D image of the inside of the container. By processing this image, the scanning station can identify an air gap along a desired cut line as well as a thickness of the sides of the container.

Radar based guidance system perceiving contents of a container

Technology for indoor location estimation of wireless stations is described. In one embodiment, a processing device identifies a plurality of wireless stations that support a signal round-trip-time measurement protocol. The processing device associates the plurality of wireless stations with one another to form a logical grouping of the plurality of wireless stations and provides an indication of the plurality of wireless stations in the logical grouping to each of the plurality of wireless stations. The processing device receives a first round-trip-time measurement value for a signal transmitted between a first wireless station and a second wireless station of the logical grouping and a second round-trip-time measurement value for a signal transmitted between the first wireless station and a third wireless station of the logical grouping. These round-trip-time measurement values indicate a distance between the wireless stations, respectively. The processing device determines, using the first distance and the second distance, a position of the first wireless station relative to the second wireless station and the third wireless station.

Indoor location estimation for wireless device

Technology for multi-hop power management is described. In one embodiment, processing logic obtains a noise floor value, an interference threshold parameter, a data rate threshold parameter, and a set of channel interference metrics from each of a first mesh network device, a second mesh network device, and a third mesh network device, respectively. The processing logic identifies a network path that traverses the three mesh network devices. The processing logic calculates a first transmit power level for the first mesh network device, a second transmit power level for the second mesh network device, and a third transmit power level for the third mesh network device. Data transmissions by each of the mesh network device at the respective transmit power levels ensure a minimum data transmission rate over each hop of the network path.

Multi-hop power management in a wireless mesh network

Network hardware devices are organized in a wireless mesh network (WMN) including a base station node (BSN) device connected to a tower in a geographic area and multiple home access node (HAN) relay devices located in a geographic area and separated from one another by a distance up to approximately 500 meters. A first set of HAN relay devices is organized in a first linear sub-mesh network with a first deployment layout having an S-shape or an inverse S-shape. Each of the first set of HAN relay devices establishes a frequency-division duplex (FDD) link between itself and at least one other HAN relay device and at least one of the first set of HAN relay devices establishes a time-division duplex (TDD) link over which the at least one of the HAN relay devices communicates with the BSN device.

Frequency planning and hexagon pattern layouts of linear sub-mesh networks of a wireless mesh network for broadband connectivity

Network hardware devices are organized in a wireless mesh network (WMN) including a base station node (BSN) device connected to a tower in a geographic area and multiple home access node (HAN) relay devices located in a geographic area and separated from one another by a distance. First set, second set, and third set of HAN relay devices are organized in a first hexagon pattern, a second hexagon pattern, and a third hexagon pattern, respectively, forming a base unit of the WMN. The BSN device is communicatively coupled to a first HAN relay device of the first set, a first HAN relay device of the second set, and a first HAN relay device of the third set and the BSN device is positioned within a geographic region defined by an outer perimeter of the base unit.

Hexagon pattern layouts of linear sub-mesh networks of a wireless mesh network for broadband connectivity

Technology for satellite-based content delivery network (CDN) is described. The satellite-based CDN uses a network architecture to provide global high-speed Internet service from above the sky through various aircrafts such as high-altitude airships, satellites, space stations, and eventually the lunar data centers by taking into consideration of the technology advancements in the RF and optical wireless communications. The satellite-based CDN provides content delivery over data networks, aviation, data storage, and edge caching. The satellite-based CDN supports both the delay-sensitive traffic such as interactive services, voice calls, and video calls that consume medium to low data bandwidth, and the more delay-tolerant but high bandwidth Internet content items such as streaming and background services (e.g. email, FTP). The satellite-based CDN can also support highly time sensitive applications that require near real-time responses such as professional gaming in selected areas covered by the high-altitude airships.

Satellite-based content delivery network (CDN) in an extraterrestrial environment

Methods and systems for providing data to a mobile device from multiple access points are described. The system may include multiple access points (APs) in communication with each other to form a network of APs. The network of APs may include a logical AP (LAP) that is discoverable as an individual physical access point by a mobile device, even though the LAP may be a logical construction involving multiple physical APs that communicate with the mobile device. The system may synchronize operations within the network of APs for effective and efficient data transmissions. The mobile device may request a data connection from the LAP or from an individual AP, wherein the data connection is between at least two APs. The data connection may have a throughput/bandwidth exceeding the maximum capacity of individual APs. The LAP may manage connections between the APs and connections between the mobile device and the APs.

Coordinated beamforming

A method includes receiving, by a first wireless device, first data indicative of channel properties of a first communication link between the first wireless device and a second wireless device, the first wireless device and the second wireless device being located in a same vicinity. The method further includes detecting, using a supervised machine learning (ML) model applied to the first data, human movement and presence of stationary objects within the same vicinity and activating, by the first wireless device in response to detection of the human movement, an ultrasonic signal. The method further includes receiving, by the first wireless device, a reflected component of the ultrasonic signal and confirming, by the first wireless device using the reflected component, presence of a human in the same vicinity.

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Saratoga, CA, United States of America

Jungtao Liu