Microsoft Technology Licensing, LLC

Gursharan Singh Sidhu

Sharad Agarwal

Kuansan Wang

Humayun Mukhtar Khan

Michael D Malueg

Anish Desai

Mansoor Jafry

John David Bruner

Sandeep Singhal

Jeffrey B Kay

Noah Horton

Vishal Soni

Ranveer Chandra

Thomas W Kuehnel

Rod G Fleck

Todd R Manion

David T Jones

Mahendra D Sekaran

Aaron Wesley Cunningham

Scott C Forbes

John Mark Miller

Ruchir Astavans

Rao Salapaka

Jie Jerry Liu

Xuedong D Huang

David Milstein

Patrice Lynn Miner

Venkata N Padmanabhan

Nissanka Arachchige Bodhi Priyantha

Lin Zhong

Jyh-Han Lin

David Chiyuan Chu

Jai Srinivasan

Sankaran Narayanan

Linda Criddle

Jonathan Jay Cadiz

David Andrew Howell

Namendra Kumar

Marieke Iwema Watson

Krishna Chintalapudi

Krishnan Ananthanarayanan

Abhilash Chandrasekharan Nair

Pradipta Kumar Basu

Kerry Woolsey

Eric S Hamilton

Eliot John Flannery

Bill Begorre

Ganapathy V Raman

Gaurav Pancholi

Ray Froelich

Sindhura Bandhakavi

Eugen Pajor

Anshul Rai

Tony Bell

Ken Wolfe

Rijurekha Sen

Jie Liu

A device identifies signals it receives at a particular point in time, such as Wi-Fi signals and cell tower signals. The device records data indicating these identified signals, as well as data used to determine the position of the device at that particular point in time. The position of the device is determined using dead reckoning, which is separated into two stages. In the first stage, a distance and direction of movement is determined at the device based on data from various inertial sensors of the device. In the second stage, various filters, maps, and/or other techniques are used at another device (e.g., a crowd sourcing data service) thus alleviating the device of the burden of performing the second stage.

Multi-stage dead reckoning for crowd sourcing

An identification is made as to when a device is at an anchor location, which can be a proximity zone along an edge of a dead zone or a location where a signal from a beacon is detected. In response to the device being at the anchor location, one or more inertial sensors can be activated and data from the one or more inertial sensors collected to determine a position of the device using dead reckoning. Alternatively, in response to the device being at the anchor location, a determination is made as to when to deactivate one or more inertial sensors from which data is collected to determine the position of the device using dead reckoning.

Activating and deactivating sensors for dead reckoning

Signaling from a mobile device is transparently tunneled through a cellular voice network to a Voice over Internet Protocol ('VoIP') core network so that multi-party calls, including conference calls and call waiting, can be managed entirely within the VoIP core network. The tunneled signals enable call control to be implemented in the VoIP core network and also establish a way to communicate requests, instructions, and call state. The signaling is transparent to the cellular network because that network does not receive and interpret the signaling. Instead, the cellular network's existing and unmodified control plane is repurposed by the mobile device by placing new, brief outgoing calls through the cellular network to the VoIP core network where the called party number (i.e., the caller-ID) encodes specific information. The VoIP core network immediately releases the new cellular call once the caller-ID is received and the encoded information is interpreted.

Tunneling VoIP call control on cellular networks

A continual learning process is applied to a class of risk estimate-based algorithms and associated risk thresholds used for deciding when to initiate a handoff between different types of network connections that are available to a mobile device having telephony functionality. The process is implemented as a virtuous loop providing ongoing tuning and adjustment to improve call handoff algorithms and risk thresholds so that handoffs can be performed with the goals of minimizing dropped calls and unacceptable degradation in call quality as well as avoiding premature handoffs. Device characteristics, environmental context, connection measurements, and outcomes of call handoff decisions are crowd-sourced from a population of mobile devices into a cloud-based handoff decision enabling service. The service evaluates potentially usable handoff decision algorithms and risk thresholds against archived crowd-sourced data to determine how they would have performed in real world situations and delivers improved algorithms and risk thresholds to the mobile devices.

Call handoff initiation in hybrid networks

The description relates to mobile device location. One example can identify global navigation satellite system (GNSS) satellites expected to be in line-of-sight of a mobile device. This example can detect differences between received GNSS data signals and expected GNSS data signals from the expected GNSS satellites. The example can also determine a direction from the mobile device of an obstruction that is causing at least some of the detected differences.

Estimating and predicting structures proximate to a mobile device

Methods and apparatus for executing a client-based, over-the-top (OTT) application, the client-based OTT application for maintaining communications with a second communication device, comprising, in one embodiment, a first transceiver for transmitting and receiving user traffic, a memory for storing processor-executable instructions, and a processor, coupled to the transceiver and the memory, for executing the processor-executable instructions that cause the wireless communication device to establish a first control plane connection, establish a second control plane connection, establish a first data plane for transporting the user traffic, the first data plane connection relating to the first control plane connection, establish a second data plane connection for transporting the user traffic if at least one predetermined event has occurred, the second data plane connection related to the second control plane connection, and to transmit and receive the user traffic over the second data plane connection via the first transceiver.

Optimization of over-the-top (OTT) services on carrier networks

Embodiments respond to a position inference request from a computing device to determine a location of a computing device. The position inference request received from the computing device identifies a set of beacons observed by the computing device. A geographic area is estimated in which the computing device is located using the set of beacons. At least one location method is selected to identify a location of the computing device within the geographic area. In some cases two or more location methods may be employed and their results combined using, for example, a weighting function. The location of the computing device is determined within the geographic area using the set of beacons and the selected location method(s). The location that is determined is communicated to the computing device.

Data driven composite location system using modeling and inference methods

An identification is made as to when a device is at an anchor location, which can be a proximity zone along an edge of a dead zone or a location where a signal from a beacon is detected. In response to the device being at an anchor location, recording of crowd sourcing data based on dead reckoning starts. Recording crowd sourcing data based on dead reckoning includes identifying one or more signals received by a device while the device is at each of multiple positions. For each of the multiple positions, both an indication of the position determined based at least in part on dead reckoning and an indication of the one or more signals received while the device is at that position are recorded.

Crowd sourcing based on dead reckoning

The functionality described herein allows a user device to determine an appropriate juncture at which to initiate processing within a global navigation satellite system (GNSS) dead zone in an energy-efficient manner. In one implementation, the functionality employs a sensor management module for determining when to activate a device movement sensor module provided by a user device. When activated, the user device uses the device movement sensor module to perform any environment-specific processing, such as a dead-reckoning process for determining incremental positions within the venue. Further, in a crowd-sourcing application, the user device may report the incremental positions together with beacon information to remote processing functionality.

Power efficient activation of a device movement sensor module

Voice call continuity is provided for calls that are carried over a hybrid network infrastructure in which access connections are distributed over loosely coupled network portions including a backend network such as a core VoIP (Voice over Internet Protocol) service network, one or more cellular mobile networks, and a public switched telephone network ('PSTN'). The calls are routed through the core VoIP network regardless of their points of origination or termination in other network portions so that signaling and call context are anchored in the core VoIP network. The conditions under which user equipment operate are continuously monitored so that when a connection is determined to have been unacceptably degraded or is likely to be interrupted, and/or a more optimal connection is available, a handover of the call to another connection is initiated so that call continuity is maintained using the lowest cost connection that provides acceptable call quality.

Voice call continuity in hybrid networks

Inferring location of a mobile computing device in an indoor environment and crowdsourcing radio frequency data are described herein. A location of the mobile computing device in the indoor environment is inferred based upon known physical constraints of the indoor environment and data from an inertial sensor of the mobile computing device, wherein an initial location in the indoor environment of the mobile computing device is unknown, a heading offset of the mobile computing device is arbitrary, and wherein a placement of the mobile computing device on a user is arbitrary.

Locating a mobile computing device in an indoor environment

A method and system for routing a call connection signal and corresponding contextual information to an appropriate destination is provided. A call center and at least one user may exchange signals, and/or contextual information during a call set-up phase. Relevant contextual information and other detailed information may be identified and collected from their corresponding sources. Based on the relevant contextual information and other detailed information, one or more appropriate routed destinations may be determined. In addition, contextual information may be tailored for each of the determined routed destinations. The call connection signal and the tailored contextual information are routed to each routed destination. In this manner, necessary contextual information may be readily available for the routed destination at the time of the call connection and thus the routed destination can provide a faster service.

Routing a VoIP call with contextual information

A session manager recognizes the creation of a new collaboration session and creates a new network connection to host the collaboration session using information about the new collaboration session. More specifically, an identifier for the new host network connection is based on the name given to the collaboration session. In this way, other computing devices can discover existing collaboration sessions by scanning the identifiers of existing network connections without actually having to connect to the available networks first.

Integrated network and application session establishment

Growing community of inventors

Seattle, WA, United States of America

Gursharan Singh Sidhu