Intel Corporation

Apple Inc.

Rakesh Kalathil

Vishnusudhan Raghupathy

Feng Xue

Venkatesan Nallampatti Ekambaram

Candy Yiu

Shilpa Talwar

Techniques are described for improving handover performance in the context of UEs incorporated into unmanned aerial vehicles (UAVs, a.k.a., drones). A database is constructed that relates locations in a three-dimensional flying space to handover information that may include optimum scanning directions, optimum handover parameters, and/or optimum target cells to be monitored for possible handover.

Handover for unmanned aerial vehicles

Systems and methods of determining a device position are described. GPS and cellular signals, in addition to VIO displacement are used to determine the device position via a loose or tight coupling algorithm. Both algorithms iteratively linearize base station position equations around an intermediate position that changes each iteration based on VIO displacement and solves the linearized solutions until convergence. The loose coupling algorithm uses the GPS fix as an initiation position, linearizing and solving using the base station equations only. The tight coupling algorithm linearizes both the base station and GPS position equations, using an arbitrary initial position. To account for multipath effects, the linearization and solution are performed for multiple random sets of measurements and the position with the smallest error metric is selected.

System and method of location determination using multiple location inputs

At least three different techniques are presented that facilitate cluster formation in clusterable devices such as drones. The techniques facilitate power saving in the individual clusterable devise as well as for the entirety of the cluster. The first technique utilizes a NAN application based cluster formation decision. The second technique initiates a cluster grade merging evaluation based on a 'merge allowed' field in a synchronization beacon set by the discovery engine. The third technique involves a discovery engine managing cluster formation with pre-set cluster grade information.

Enhancing Wi-Fi aware protocol and algorithms for drone cluster formation

System and techniques for unmanned aerial vehicle navigation are described herein. A plurality of transmission beams may be established. Here, each beam in the plurality of transmission beams is a focused photonic propagation directed to a fixed geographic area and a travel route intersects the fixed geographic areas of the plurality of transmission beams. Cell entry may be received for a vehicle transceiver entering a geographic area for a transmission beam in the plurality of beams. Scrambling codes corresponding to the plurality of transmission beams may be provided to the vehicle. A course parameter, decodable by a scrambling code of the scrambling codes, may be transmitted to the vehicle via the plurality of transmission beams.

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San Diego, CA, United States of America

Rakesh Kalathil