Qualcomm Incorporated

Vanitha Aravamudhan Kumar

Shailesh Maheshwari

Gavin Bernard Horn

Uppinder Singh Babbar

Vishal Dalmiya

Vaibhav Kumar

Kuo-Chun Lee

Arnaud Meylan

Aziz Gholmieh

Leena Zacharias

Gang Xiao

Alok Mitra

Arunn Coimbatore Krishnamurthy

Srinivasan Balasubramanian

Xipeng Zhu

Daniel Amerga

Yu-Ting Yu

Vaishakh Rao

Hariharan Sukumar

Srividhya Krishnamoorthy

Vinod Harimohan Kaushik

Neven Klacar

Muralidhar Coimbatore Krishnamoorthy

Roshan Thomas Pius

Andrei Danaila

Rajat Prakash

Tom Chin

Sitaramanjaneyulu Kanamarlapudi

Amit Mahajan

Yue Yang

Srinivas Reddy Mudireddy

Ashwini Raina

Taesang Yoo

Ozcan Ozturk

Sai Yiu Duncan Ho

Arvind Vardarajan Santhanam

Sivaramakrishna Veerepalli

Marcello Vincenzo Lioy

Thomas Klingenbrunn

Punyaslok Purkayastha

Luis Fernando Brisson Lopes

Bhupesh Manoharlal Umatt

Rajeev Kumar

Bao Vinh Nguyen

Shankar Krishnan

Arun Prasanth Balasubramanian

Eren Balevi

Kurt William Otte

Vikas Nagpal

Yateesh S Gowda

Linhai He

Parag Arun Agashe

Soo Bum Lee

Fatih Ulupinar

Francesco Grilli

Ravindra Manohar Patwardhan

Jonathan Kies

Arvind Swaminathan

Vikram Singh

Victor Kulik

Satashu Goel

Scott Hoover

Junsheng Han

Jean-Marie Tran

Gurvinder Singh Chhabra

Idreas Mir

Vinay Paradkar

Irfan Anwar Khan

Carl Hardin

Uzma Khan Qazi

Akshay Kumar

Udayan Murli Bhawnani

Xing Chen

Samson Jim

Mathias Kohlenz

Madhup Chandra

Vivek Venkatesh Ramachandran

Thomas James Christol

Anurag Vardhan

Kannan Muthuraman

Sriram Narayan

Krishna Chaitanya Bellam

Swaminathan Sureshchandran

Sudhir Halbhavi

Nirupama Locanindi

Steve Hannagan

Karthik Thirukannan

Sathish Kumar Nallamanti

Bin Qiu

Gautham Kumar Reddy Adireddy

Kurt Otte

Manmeet Singh

Udayan Bhawnani

Gang A Xiao

Harimohan Kaushik Vinod

Shailesh Maheswari

Irfan A Khan

Jean-Marie Qd Tran

In some implementations, a mobile device may determine a set of target orientations of the mobile device in which an antenna lobe of the mobile device is pointed toward the satellite, the set of target orientations based on: an orientation of the antenna lobe relative to the mobile device, and a location of the satellite relative to the mobile device. The mobile device may determine a current orientation of the mobile device. The mobile device may provide, at a user interface (UI) of the mobile device, guidance for rotating the mobile device from the current orientation to an orientation within the set of target orientations.

Mobile device orientation guidance for satellite-based communications

Aspects disclosed in the detailed description include power saving techniques in computing devices. In particular, as data is received by a modem processor in a computing device, the data is held until the expiration of a modem timer. The data is then passed to an application processor in the computing device over a peripheral component interconnect express (PCIe) interconnectivity bus. On receipt of the data from the modem processor, the application processor sends data held by the application processor to the modem processor over the PCIe interconnectivity bus. The application processor also has an uplink timer. If no data is received from the modem processor before expiration of the uplink timer, the application processor sends any collected data to the modem processor at expiration of the uplink timer. However, if data is received from the modem processor, the uplink timer is reset.

Power saving techniques in computing devices

Methods, systems, and devices for wireless communications are described. In some examples, a wireless communications system may support machine learning and may configure a user equipment (UE) for machine learning. The UE may transmit, to a base station, a request message that includes an indication of a machine learning model or a neural network function based at least in part on a trigger event. In response to the request message, the base station may transmit a machine learning model, a set of parameters corresponding to the machine learning model, or a configuration corresponding to a neural network function and may transmit an activation message to the UE to implement the machine learning model and the neural network function.

Configuring a user equipment for machine learning

Certain aspects of the present disclosure relate to methods and apparatus for reliable transmission of system information (SI). In some cases, a UE may send an indication to request SI in an on-demand manner. For example, a method for wireless communications by a UE may include determining system information (SI) desired by the UE is not currently being broadcast. The method for further include sending, in response to the determination, a first indication to request the SI, and sending a second indication to confirm reception of the requested SI or to indicate the UE has not received the requested SI after a time period.

Reliable delivery of system information

Certain aspects of the present disclosure provide techniques for packet buffering. A method that may be performed by a receiving node includes dynamically determining one or more time durations to buffer packets. The one or more time durations can be different than a time duration of a configured timer for buffering the packets. The receiving node may input one or more parameters to a machine learning algorithm and obtain, as output of the machine learning algorithm based on the input one or more parameters, one or more time durations to buffer packets. The receiving node buffers packets for the determined one or more time durations. The receiving node may use machine learning to dynamically determine the one or more time durations to buffer packet. The buffering may be at a radio link control (RLC) reassembling buffer and/or a packet data convergence protocol (PDCP) buffer.

Dynamic packet buffering duration

Methods, systems, and devices for wireless communications are described. A system may support techniques for triggering user equipment (UE) assistance information (UAI) based on mobility, wake up signal (WUS) configuration, or both. In some cases, a UE may communicate with a network node (e.g., a base station) on a first channel according to a discontinuous reception (DRX) configuration. The UE may determine that a speed of the UE satisfies a mobility threshold and may transmit UAI requesting one or more updated DRX configuration parameters based on the speed of the UE satisfying the mobility threshold. Additionally or alternatively, the UE may receive signaling configuring the UE to monitor for WUSs and may transmit UAI requesting one or more updated DRX configuration parameters based on the WUS configuration. The UE may receive control signaling configuring the DRX configuration with the one or more requested parameters in response to the UAI.

Triggering user equipment (UE) assistance information based on mobility and wake up signal (WUS) configuration

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may communicate on a first set of carriers in a first frequency range (FR) and a second set of carriers in a second FR. The UE may detect a radio link control (RLC) discontinuity on at least one of the first set of carriers or the second set of carriers. The UE may identify one or more FRs, of the first FR and the second FR, in which the RLC discontinuity occurred. The UE may transmit an RLC status report based at least in part on the identified one or more FRs. Numerous other aspects are described.

Carrier aggregation for mixed frequency ranges

A method of wireless communication, by a user equipment (UE), includes setting up a secondary cell group (SCG) with a second radio access technology (RAT) that differs from a first RAT associated with a master cell group (MCG). The method also includes communicating wirelessly via the secondary cell group and the master cell group. The method further includes predicting a radio link failure (RLF) for the secondary cell group based on multiple inputs to a machine learning model. The method still further includes routing data transmission from the secondary cell group to the master cell group, after predicting the SCG RLF.

Secondary cell group (SCG) failure prediction and traffic redistribution

A delta configuration is signaled for handover of a wireless communication device (e.g., a user equipment, UE) from a first form of connectivity to a second form of connectivity. For example, a UE with master cell group (MCG) connectivity may be handed-over to multiple radio access technology-dual connectivity (MR-DC). In some examples, a UE with standalone (SA) connectivity may be handed-over to non-standalone (NSA) connectivity (e.g., dual connectivity). In conjunction with this handover the UE may be signaled as to whether the UE is to reuse a configuration from the first connectivity mode during the second connectivity mode.

Signaling of delta configuration for handover

Certain aspects of the present disclosure provide techniques for dynamically determining an uplink data split threshold for communicating using one or more radio link control (RLC) entities of a split bearer configuration. A method that may be performed by a user equipment (UE) includes inputting a first set of parameters to a machine learning algorithm, obtaining, as an output of the machine learning algorithm based at least in part on the inputted first set of parameters, a value for a data split threshold, and transmitting the data using at least one of a first RLC entity or the second RLC entity based on the value for the data split threshold and the amount of data the apparatus has to transmit.

Dynamic uplink data split threshold

Various embodiments include methods for autonomous beam switching by a wireless device. A processor of the wireless device may measure signal parameters of signals received from a first synchronization signal block (SSB) beam of a base station monitored by the wireless device and other SSB beams of the base station, determine whether a difference in measured signal parameters of signals received from the first SSB beam and another SSB beam of the base station satisfies a signal quality difference threshold, and autonomously switching to the second SSB beam as the serving beam in response to determining that the difference in the measured signal parameters of signals received from the first SSB beam and a second SSB beam satisfies the signal quality difference threshold. The signal quality difference threshold may be listed in a table in memory or determined via machine learning.

Autonomous beam switching

Certain aspects of the present disclosure provide techniques for predicting an amount of uplink data to report in a buffer status report (BSR). A method that may be performed by a user equipment (UE) includes predicting a value of a parameter related to transmission of uplink data from the UE; determining an amount of uplink data to report in the BSR based on at least the predicted value of the parameter, and transmitting the BSR including an indication of the determined amount of uplink data.

Buffer status report prediction

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San Diego, CA, United States of America

Vanitha Aravamudhan Kumar