Qualcomm Incorporated

Celona, Inc.

Psemi Corporation

Mehmet Yavuz

Farhad Meshkati

Sanjiv Nanda

Peerapol Tinnakornsrisuphap

Vinay Chande

Yeliz Tokgoz

Peter J Black

Chirag Sureshbhai Patel

Sumeeth Nagaraja

Damanjit Singh

Yan Zhou

Andrei Dragos Radulescu

Sharad Deepak Sambhwani

Srinivasan Balasubramanian

Bibhu P Mohanty

Aziz Gholmieh

Jen Mei Chen

Christophe Chevallier

Rohit Kapoor

Vansh Pal Singh Makh

Rajat Prakash

Mostafa Khoshnevisan

Ahmed Kamel Sadek

Danlu Zhang

Leonard Henry Grokop

Tamer Adel Kadous

Matthew Stuart Grob

Manoj Madhukar Deshpande

Nagi Jayaraman Mahalingam

Peter Hans Rauber

Varun Khaitan

Preethi Natarajan

Gavin Bernard Horn

Sourav Bandyopadhyay

Rajeev Shah

Ozcan Ozturk

Arnaud Meylan

Jay Kumar Sundararajan

Serafin Diaz Spindola

Yi Jiang

Vinay Anneboina

Mark Jan Dijkstra

Naga Bhushan

Ramin Rezaiifar

Mostafa El-Khamy

Mehmet Izzet Gurelli

Mingxi Fan

Satashu Goel

Siddharth Mohan

Cong Shen

Peter John Black

Suhas Mitra

Sarut Vanichpun

Joseph Binamira Soriaga

Piyush Gupta

Luca Blessent

Pavan Kumar Vitthaladevuni

Gerardo Giaretta

Rashid Ahmed Attar

Vinay Joseph

Chirag Dipak Patel

Ravindra Manohar Patwardhan

Rajesh K Pankaj

Rahul Dangui

Douglas Norman Knisely

Andrew Von Nagy

Aparna Jaiswal

Junyi Li

Juan Montojo

Wei Zeng

Nathan Edward Tenny

Vikram Makam Gupta

Parag Arun Agashe

Qiang Wu

Arjun Bharadwaj

Rashid Ahmed Akbar Attar

Chong Li

Jay Rodney Walton

Francesco Grilli

Nagabhushana T Sindhushayana

J Rodney Walton

Francesco Pica

Etienne Francois Chaponniere

Nachiappan Valliappan

Oronzo Flore

Yu-Chuan G Lin

Yibo Jiang

Lu Yuan

Lijun Zhao

Yichao Huang

Nagesh S Nandiraju

Edward G Tiedemann

Puneet Sethi

Matt Stuart Grob

Pooyan Amini

Rajeshwar Ponna

Lili Zhang

Fracesco Pica

Serafin Diaz

Keshav Sai Nanduri

A first referred to as Approach A has three 40 MHz BWPs. The first BWP of the BWP configuration 2, approach A referred to as 'BWP #1' resides in the top of the 100 MHz bandwidth. A second approach referred to as “BWP #2” resides in the middle portion of the 100 MHz band. A third approach referred to as “BWP #3” resides in the bottom portion of the 100 MHz band. BWP configuration 2, approach A allows overlaps between the BWP #1 and BWP #2 and also between BWP #2 and BWP #3. These overlaps can be leveraged to allow a diversity of users to be scheduled across BWPs #1 and #2 and between BWPs #2 and #3. In some embodiments, BWP #2 aligns with BWP Configuration 1 users.

Method and apparatus for wider bandwidth gNodeB operation with user equipment bandwidth restrictions

A method and apparatus for allocating radio resources in a RAN deployment in an Enterprise Network. Radio resource parameter allocation decisions for all the Base Stations and Access Points (BS/APs) in the deployment are made responsive to network graphs formed using predicted path loss. In one embodiment the predicted path loss values are simulated for a particular enterprise network deployment, network graphs are formed using the path loss values, and radio resources parameters are allocated responsive to the network graphs. Advantageously, the network graphs provide the network with the ability to quickly and efficiently allocate radio resources, which can be automated. In the initial installation, this reduces cost and time. During operation, quick and efficient resource re-allocation provides quick adaptation to resource changes, an advantage that is useful particularly in the context of a CBRS system in which previously-available channels can be terminated.

Method and apparatus for radio area network resource allocation in an enterprise wireless communication network

Method and apparatus for scalable machine learning (ML)-based frameworks for resource planning and recommendations for Enterprise Networks are disclosed. In some embodiments, a method for determining network health assessment and providing network planning and recommendations in wireless enterprise networks is provided. The method quantifies resource health of a plurality of network elements operating within the enterprise network by calculating a plurality of distance metrics between acceptable health parameters and observed network resource utilization values associated and corresponding to each selected network element. The method ranks each of the network elements based upon the distance metrics calculated for each network element. Factors that negatively impact the resource health of the network elements are ranked in accordance to how severely they impact the performance of the network elements. The method and apparatus provide suggestions and recommendations to improve network performance of the network elements. An apparatus for scalable machine-learning (ML)-based frameworks for resource planning in enterprise networks is also disclosed.

Method and apparatus for scalable ML-based frameworks for resource planning in enterprise networks

Methods and apparatus for autoconfiguring microslices in enterprise wireless communication networks using a microslice knowledgebase in a remotely located orchestration platform. Microslices are independent end-to-end logical networks operating on a shared physical infrastructure, which ensure certain Quality of Service (QoS) and Service Level Objective (SLO) requirements are met for different service types or applications. Any of the enterprise networks may be a Citizen's Broadband Radio Service (CBRS) system. A microslice knowledgebase unit in the orchestration platform configures microslices for the enterprise networks based upon communication requirements of applications, devices, and groups of devices such as service type, bandwidth requirements, using machine learning and artificial intelligence to learn communication requirements of each enterprise deployment. The microslice configuration unit in the knowledgebase may develop microslice templates based upon enterprise type, which can be used to better make recommendations to enterprise networks during initial deployment and afterwards.

Method for autoconfiguring microslices in a wireless enterprise network

A method and apparatus for defining, configuring, operating, monitoring, and modifying microslices in an enterprise network is described. Microslices provide an end-to-end logical network through multiple networks, which allows efficient arrangement of data flows in the enterprise network with a defined Quality of Service (QoS). Various embodiments of a system for creating and implementing microslice instances in a wireless communications network are disclosed. A microslice instance can connect a UE in the enterprise network with an external server. In some embodiments, the enterprise network administrator can define Service Level Objectives (SLOs), device groups, service types, and user application groups, and associate them with one or more microslices. An orchestrator can configure the microslice with an appropriate amount of network resources to be allocated to the microslice, and then set-up, operate, monitor, and modify the microslice instance to adapt to current network conditions.

Method and apparatus for microslicing wireless enterprise communication networks using microslice profiles

Time Division Duplex (TDD) Configuration Selection for CBRS operation with TDD Configuration Mismatch methods and apparatus are disclosed. The methods and apparatus allocate CBRS bandwidth and select TDD configurations in a manner that allows maximum cooperation between GAA and PAL CBSDs, and includes procedures that avoid forcing the procedures into a fallback mode whenever a TDD configuration mismatch occurs. The methods and apparatus allocate an appropriate TDD configuration across all of the CBSDs (BS/APs) in the CBRS network so that there is minimal interreference between the CBSDs and so that there is uniform usage of the bandwidth in terms of use cases across all of the CBSDs in a given CBRS network. The disclosed methods and apparatus determine how to select the correct TDD configurations for the CBSDs (or BS/APs) based on the constitution of the CBSDs, and taking the GAA and PAL CBSD requirements into account.

Time division duplex configuration selection for citizen band radio service operation with TDD configuration mismatch

A method and apparatus for enhancing load balancing within wireless networks and, in particular, within wireless networks operating within Enterprise Networks is disclosed. The method and apparatus efficiently balance the load that is shouldered by each BS/AP within the wireless network. This is particularly advantageous within wireless networks operating within an Enterprise Network. Improved BS/AP deployments in Enterprise Networks that maintain high system throughput in the EN while optimizing the performance of UEs (with regard to battery utilization and service) are disclosed. Improved EN deployments for UE mobility that reduces measurement scans required of and performed by the UEs are disclosed.

Load balancing for enterprise deployments

A method and apparatus for seamless real-time transitions across LTE and Wi-Fi networks are disclosed. The disclosed method and apparatus relate to determining which communications networks to use when communicating between a UE and a network within an Enterprise Network (EN). In some embodiments, a Communications Client Application (CCA) operates within a selected UE and a Communications Server Application (CSA) operates on the network side of the Enterprise Network. Both the CCA and the CSA act together in concert to coordinate the transmission of packets between the UE and the network using either LTE or Wi-Fi networks. For seamless communications, some embodiments use a single VPN tunnel through which to transmit data packets. In other embodiments, for seamless communications, two VPN tunnels are used, one for LTE packet transfers, and one for Wi-Fi packet transfers.

Apparatus for seamless realtime transitions across LTE/WI-FI

A method and apparatus for planning a wireless communication network operating in a spectrum-controlled radio band and determining spectrum availability at an enterprise location. A plurality of network models are generated using machine learning techniques, the network models are provided to a network planner unit, input is received regarding intended deployment, and spectrum availability is determined responsive to the enterprise location. The number of BS/APs needed is estimated, and an enterprise network may be planned and deployed. The enterprise network is monitored, and if network operation is not meeting expected performance, the models may be retrained and the network planner updated. Spectrum availability is determined by registering a discovery group with an SAS at a location to provide spectrum availability, and repeating for each location. The method may be periodically performed to generate a time series of data which may be analyzed to provide spectrum availability.

Method and apparatus for CBRS network planning and operating in an enterprise network

Methods and apparatus are disclosed for determining spectrum availability within a radio band managed by a Spectrum Management Entity (SME), and allocating available spectrum to Base Station/Access Points (BS/APs) of an Enterprise Network (EN). The EN includes a domain proxy that sends a registration request to the SME indicating a maximum EIRP for the BS/APs. After receiving registration, the Domain Proxy sends a spectrum inquiry and receives a response specifying available spectrum. If less than the entire requested spectrum is available, then the maximum EIRP indication is reduced, and a next iteration is performed re-registering the BS/APs and requesting spectrum. Iterations are repeated until the entire requested spectrum is available, and then spectrum is allocated to the BS/APs. Each iteration of channel availability is stored, and channels are allocated utilizing a Self-Organizing Network (SON) technique responsive to the stored channel availability. The EN may comprise a CBRS Network.

Method and apparatus for determining spectrum availability and allocating spectrum in a spectrum controlled network

A credential management system for enterprise networks (ENs) that allows credential storage in different levels and enables individual enterprises to manage the sets of credentials for the SIM cards used in their respective networks. Central management of credentials is provided by a remote cloud-based, centralized orchestration network (O-Net) that receives SIM cards from a SIM Provisioning Platform (SPP) and distributes the credentials to the ENs, which store the credentials in an enterprise global database and assign the SIM cards to the UEs. The credentials can be associated with specific policies and user groups so that the enterprise can control the type and quality of access allowed to UEs. Each EN may have a plurality of campus locations and at each location, a local credential database may be provided to act as a cache for quick efficient access to credentials by the UEs.

Hierarchical database architecture for subscriber credential management in enterprise networks

A User Equipment (UE) device, such as a cellular telephone, configured to store Higher Priority Public Land Mobile Network (HPPLMN) timer setting values and enterprise geofence information associated with the entries on its Equivalent Home Public Land Mobile Network (EHPLMN) list is disclosed. When the UE is camped on an EHPLMN, the UE may search/scan for higher priority EHPLMNs using the HPPLMN timer setting values associated with the entries on the list that have higher priority than the current EHPLMN. The rate of the scans may be set based on the shortest HPPLMN timer entry of the higher priority entries on the EHPLMN list. The UE may also or instead be configured to search for geofenced EHPLMNs on the list for which entrance criteria are currently satisfied, even when the current EHPLMN has higher priority than the geofenced EHPLMNs.

Enhancements to EHPLMN scans in cellular networks

A method and apparatus for managing wireless Enterprise Networks (EN) for greater efficiency by developing inactivity timers for packet streams on bearers, monitoring the packet streams of UEs on the bearers, and if inactivity is found determining whether or not to release or modify a bearer, or maintain the current status of the UE considering factors such as congestion, expected lull time, reconstruction cost, and UE type and location. Accordingly, UEs can be more efficiently allocated the EN's available resources. To learn the timers, packet streams are monitored over a period of time, the packet streams are sorted by service type and bearer (and optionally time), and an inter-burst packet arrival time is determined. Timers are developed that provide inactivity time limits and an expected lull time that predicts the behavior of the packet streams based on service type and bearer, and optionally time.

Method and apparatus for selectively releasing user equipment devices to efficiently operate an enterprise wireless communication network

A method and apparatus for managing network loading and adjusting admission, and/or congestion and service types based on real-time analytics in an enterprise wireless communication network that includes Base Stations/Access Points (BS/APs) in communication with a number of User Equipment devices (UEs) within the coverage area at a campus location. The system dynamically learns the parameterizations for the control system, and adapts the parameters as the network usage evolves, which is useful for an efficient self-managed network. Such a system can provide a greater QoS across users and other efficiencies. The system simplifies deployment at the enterprise's campus locations because load heatmaps and service patterns are learned based on the actual campus locations.

Method and apparatus for load control of an enterprise network on a campus based upon observations of busy times and service type

Growing community of inventors

San Diego, CA, United States of America

Mehmet Yavuz