Nokia Solutions and Networks Oy

Motorola Mobility LLC

Motorola Corporation

Google Inc.

Nokia Siemens Networks Oy

Nokia Technologies Oy

Northwestern University

Rajeev Agrawal

Anand Bedekar

Suresh Kalyanasundaram

Venkat Gopikanth

Vishnu Ram Ov

Hua Xu

Guang Han

Hans Juergen Kroener

Rangsan Leelahakriengkrai

Vijay G Subramanian

Balamurali N Natarajan

Xiaoyi Wang

Jamil Shihab

Ian Dexter Garcia

Naveen Arulselvan

Chandrashekhar Thejaswi

Francis Dominique

Randall Berry

Klaus Ingemann Pedersen

Michael Mao Wang

Tyler A Brown

Surender Kumar

Troels Emil Kolding

Avinash Joshi

Ivan Vukovic

Eugene Visotsky

Sivakumar Muthuswamy

Shirish Nagaraj

Ruth S Gayde

Bishwarup Mondal

Jay P Jayapalan

Afef Feki

Veronique Capdevielle

Roy Yang

Paul Boudreaux

Jani Matti Johannes Moilanen

Chandrasekar Sankaran

Ajoy Kumar Singh

Igor Filipovich

Richa Gupta

Shalini Gulati

Claudiu Mihailescu

Stavros Tzavidas

Deepak Kumar Nayak

Yogesh Bhatt

Xiangyang Chen

Eric Desorbay

Deepak Pengoria

Rajeev Ranjan

Anand S Bedekar

Karthik Kuntikana Shrikrishna

Jinesh P Nair

Ram O V Vishnu

Jiawei Huang

Boris Kouassi

Sheshachalam B S

Hans Kroener

Different solutions, in which uplink data streams are whitened and after that combined, are disclosed. The whitening is performed by applying whitening parameters received in a downlink control information. The whitening parameters are based on predictions on channel conditions.

Whitening uplink data streams

Methods and apparatuses are provided for hardware acceleration for a frequency domain scheduler. An example method includes receiving an instruction from a processor core to process a job for determining an allocation of a set of resources to one or more users, the set of resources corresponding to a transmission layer in a transmission time interval; processing the job by determining which of the one or more users is to be allocated on each of the respective resources in the set based on a first array stored in a memory associated with a metric of each of one or more users for each of the resources in the set, and a second array stored in the memory associated with a buffer size of each of the one or more users; and in response to successfully completing the job, sending an indication of the determined allocation to the processor core.

Hardware acceleration for frequency domain scheduler in wireless networks

An apparatus, method and computer program is described above: determining a coupling gain for a user device within a cell of a mobile communication system; comparing the determined coupling gain with a coupling gain threshold; setting the user device to operate in a device-specific CSI-RS mode of operation in the event that the determined coupling gain is less than the coupling gain threshold, wherein, in the device-specific CSI-RS mode of operation, the user device is configured to use device-specific reference signal transmissions for the determination of channel state information; and setting the user device to operate in a cell-specific CSI-RS mode of operation in the event that the determined coupling gain is not less than the coupling gain threshold, wherein, in the cell-specific CSI-RS mode of operation, the user device is configured to use cell-specific reference signal transmissions for the determination of channel state information.

Method and apparatus for controlling operation of user device

Systems, methods, apparatuses, and computer program products for multi-user (MU) multiple-input multiple-output (MIMO) user pairing selection are provided. One method may include selecting multi-user multiple input multiple output (MU MIMO) candidate beams using deep neural network(s) (DNNs), and selecting paired users based on the selected beams. The deep neural network(s) (DNNs) are trained to maximize multi-user priority metric (MU-PM) or a heuristic of the multi-user priority metric (MU-PM).

Methods and apparatuses of multi-user multiple-input multiple-output beam selection and user pairing using deep learning

Inter-radio access technology (inter-RAT) load balancing under multi-carrier dynamic spectrum sharing (SS) context is provided. One method may include splitting shared radio-frequency resources into orthogonal resource pool shares. The method may include receiving a load metric for each of a plurality of radio access technologies. The method may include assigning, based on the load metric, one of the resource pool shares to each of the plurality of radio access technologies. In addition, the method may include dynamically adjusting a proportion of the assigned resource pool shares based on the load metric of each of the plurality of radio access technologies at corresponding carriers. The method may include assigning a primary carrier to a user equipment based on the load metric, the resource pool share, a coverage of the carriers' physical channels, and a type of multi-carrier operation for each of the plurality of radio access technologies.

Inter-radio access technology load balancing under multi-carrier dynamic spectrum sharing

An apparatus includes a beam selection hardware accelerator for determining a set of beams to be used for data scheduling by a wireless node for a transmission time interval, the beam selection hardware accelerator being configured to: receive a beam information and information indicating an angular separation of beams for a set of selected beams; create a graph based on the beam information and the minimum angular separation; select a set of beams, out of a plurality of beams, as a maximum weight independent set of beams based on the created graph; and provide a notification of the selected set of beams.

Beam selection accelerator for wireless node scheduler

Systems, methods, apparatuses, and computer program products for determining a grid-of-beams (GoB) are provided. One method may include collecting network data for training a neural network, train the neural network, using the collected data, to learn a non-discounted cumulative reward Q that evaluates a benefit of including a given beam into a grid-of-beams (GoB), iteratively applying the trained neural network to select at least one optimal beam to include in the grid-of-beams (GoB), and selecting one or more beams from the grid-of-beams (GoB) to transmit to a user equipment or to receive transmission from the user equipment.

Apparatus and method for designing a grid-of-beams using machine learning

A server associated with a core network may include a memory storing computer-readable instructions; and at least one processor coupled to the memory, the at least one processor configured to execute the computer-readable instructions to, generate a list of preferred instances of a first network function, transmit the list of the preferred instances to a server associated with a third network function, and receive a request to establish a communication session with a selected instance selected from the list of the preferred instances, if the server is associated with a selected instance of a second network function associated with the selected instance of the first network function.

Methods, apparatuses and computer-readable storage mediums for coordinated selection of RAN and core user plane components in a wireless communications network

An apparatus is disclosed, comprising means for identifying a plurality of user equipment (UE), each transmitting one or more uplink packets for decoding at a base station associated with a given cell of a radio network. The apparatus further comprises means for clustering the identified user equipment into joint processing groups, each joint processing group comprising the identities of two or more user equipment as clustered and means for performing, in a first processing stage, joint processing of the uplink data streams for identified user equipment within common joint processing groups using one or more first processing algorithms to produce corresponding first processed uplink data streams. The apparatus further discloses means for performing one or more subsequent processing stages on the first processed uplink data streams, subsequent to the joint processing, to produce decoded uplink data streams, the one or more subsequent processing stages using one or more second processing algorithms, different from the first processing algorithm.

Processing of uplink data streams

According to an example embodiment, a method may include receiving, by a controller from a radio access network (RAN) node within a wireless network, at least one of a neural network support information, and a measurement information that includes one or more measurements by the radio access network node or one or more measurements by a wireless device that is in communication with the radio access network node; determining, by the controller based on the at least one of the neural network support information and the measurement information, a configuration of a neural network for the radio access network node; an sending, by the controller to the radio access network node, neural network configuration information that indicates the configuration of the neural network for the radio access network node.

Configuration of a neural network for a radio access network (RAN) node of a wireless network

Methods, devices, and computer program products concerning accommodating ultra-reliable low latency communications (URLLC) traffic by making a determination of which mobile broadband (MBB) user equipment (UE) to puncture, where in response to an indication that URLLC traffic needs to be scheduled in the midst of ongoing MBB transmissions in a wireless communications network, the determination is made from a plurality of MBB UEs with the ongoing MBB transmissions, of a set of the plurality scheduled for transmission in a slot required by the URLLC traffic. From that set of MBB UEs, a subset of MBB UEs for puncturing is chosen, where that choice is made at least in relation to accommodating a reliability constraint of the URLLC traffic, maximizing a sum proportional fairness metric of the plurality of MBB UEs, and minimizing a block error rate in a computation of a proportional fairness metric for each UE of the subset.

Determining the MBB UE to puncture to accommodate URLLC traffic

This document discloses a solution for selecting a transmission direction in a cell. A method comprises: determining, by a controller associated with a cell of a cellular communication system, a traffic asymmetry metric for the cell, the traffic asymmetry metric representing asymmetry between uplink and downlink traffic in the cell; comparing, by the controller, the traffic asymmetry metric with a threshold; upon determining, by the controller on the basis of the comparison, that the traffic asymmetry metric is one of greater and lower than the threshold, selecting a first transmission direction for a time interval; upon determining, by the controller on the basis of the comparison, that the traffic asymmetry metric is the other one of greater and lower than the threshold, selecting for the time interval a second transmission direction different from the first transmission direction, wherein the second transmission direction is a nominal transmission direction determined as common to a cell cluster comprising the cell and a set of neighboring cells, and wherein the controller determines the nominal transmission direction on the basis of traffic condition metrics acquired for the cell and for the set of neighboring cells; and causing data communication to the selected transmission direction in the cell during the time interval.

Adaptive transmission direction selection in cellular network

As radio access network (RAN) architecture evolves and evolved packet core deployments get more distributed, there is an opportunity to provide significant optimizations of latency and processing. Certain embodiments can provide these and other benefits using vertical aggregation of radio access network and evolved packet core functionalities. A method can include operating a network element as a per-user-equipment control plane entity. The method can also include operating the network element as a first user plane entity (for example, a per-user-equipment user plane entity). The method can further include operating the network element as a second user plane entity. The method can additionally include operating the network element as a per-cell control plane entity. The method can also include operationally interconnecting the per-user-equipment control plane entity, the first user plane entity, the second user plane entity, and the per-cell control plane entity via interfaces.

Architecture for radio access network and evolved packet core

The present invention addresses method, apparatus and computer program product for dynamic cell clustering for Coordinated Multipoint operation. Clustering metric information defining relevant metrics for making cell clustering decision for Coordinated Multipoint operation are received from a network element serving a neighboring cell, and based on the received clustering metric information, it is decided whether to include the neighboring cell to a cluster for Coordinated Multipoint operation.

Dynamic cell clustering for coordinated multipoint operation

Systems, methods, apparatuses, and computer program products relating to coordinated scheduling with adaptive muting are provided. One method comprises transmitting, by a network element, calculated impact information for a cell of the network element when taking an action related to a cell of the network element and/or taking an action related to a cell of a second network element. The method may also comprise transmitting a request for taking the action related to the cell of the second network element under certain circumstances.

Coordinated scheduling with adaptive muting

Growing community of inventors

Northbrook, IL, United States of America

Rajeev Agrawal