Telefonaktiebolaget Lm Ericsson (publ)

Mohammad Mozaffari

Yi-Pin Eric Wang

Yutao Sui

Mehrnaz Afshang

Xingqin Lin

Andreas Höglund

Johan Mikael Bergman

Kittipong Kittichokechai

Luca Feltrin

Jung-Fu Cheng

Dennis Hui

Anders Wallén

Talha Khan

Yi-Ju Chen

Yun Chen

Mattias Frenne

Olof Liberg

Riikka Susitaival

Stefan Wänstedt

Oscar Ohlsson

Jonas Kronander

Dominique Everaere

Saeedeh Moloudi

Istiak Hossain

Zhilan Xiong

Hamza Khan

Tahla Khan

There is provided techniques for determining INACTIVE eDRX configurations for UEs. The method is performed by a core network node. The method comprises performing an iterative learning process with the access network nodes to determine the INACTIVE eDRX configurations. The iterative learning process comprises transmitting a global parameter vector of a machine learning model to the access network nodes for determining the INACTIVE eDRX configurations of the UEs. The global parameter vector defines coefficients for the machine learning model for the current iteration. The iterative learning process comprises receiving local model parameter vectors with locally updated coefficients for the machine learning model from the access network nodes. The iterative learning comprises updating the global parameter vector for the next iteration as a function of all received local model parameter vectors until a stopping criterion is fulfilled.

Determination of inactive EDRX configurations for user equipment

A method is disclosed herein for reducing energy consumption in a wireless device. A wireless device (e.g., a user equipment) can provide an indication to a network node (e.g., a base station) to indicate that the wireless device will prioritize energy consumption reduction over some network requirements (e.g., latency and/or scheduling flexibility requirements). Accordingly, the wireless device can perform certain power-saving actions to reduce energy consumption. The network node, upon receiving the indication from the wireless device, can perform certain network-related actions to assist the wireless device in reducing energy consumption. As a result, it is possible for the wireless device to reduce energy consumption and complexity, thus helping to prolong battery life in the wireless device.

Methods and devices for reducing UE energy consumption

Systems and methods are disclosed herein for Control Resource Set (CORESET) enhancements for initial access. In one embodiment, a method performed by a wireless communication device comprises receiving and decoding a Physical Downlink Control Channel (PDCCH) transmission in a CORESET in accordance with at least a portion of a Control Channel Element (CCE) to Resource Element Group (REG) mapping. The PDCCH transmission comprises one or more CCEs. The CCE to REG mapping comprises an interleaved portion that maps the one or more CCEs to a first set of REGs that are spread across a bandwidth of the CORESET, and a second portion that maps at least a portion of an additional CCE to at least a REG in a frequency gap between two REGs in the first set of REGs, the additional CCE corresponding to one of the CCEs mapped to the first set of REGs.

Coreset enhancement for reduced bandwidth UEs initial access

A method by a reduced capability wireless device includes receiving system information from a network node. The system information comprising information specific to the reduced capability wireless device. The reduced capability wireless device performs an operation using at least the information specific to the reduced capability wireless device received in the system information.

Methods for enabling a low bandwidth wireless device to access a new radio cell via a wideband control resource set

There is disclosed a method of operating a radio node in a wireless communication network, the method including communicating based on a signaling structure, the signaling structure including a number R of long symbols and/or a number Nsym of regular symbols, wherein R and/or Nsym is based on the subcarrier spacing associated to the signaling structure and/or a cyclic prefix length of a long symbol and/or a cyclic prefix length of a regular symbol. The disclosure also pertains to related devices and methods.

Signaling structure for wireless communication network

There is provided a method performed by a wireless device for communicating with a network node in a wireless communication network. The method includes using a field in a Master Information Block (MIB) received by the wireless device, as an indication of a presence of an extended MIB (eMIB) and identifying which candidate resource of at least one candidate resource that contains the eMIB based on the indication of the presence of the eMIB. There is also provided a corresponding wireless device for communicating with a network node, a method perform by a network node, and a network node.

Master information block extension in a New Radio cell

According to some embodiments, a method performed by a network node for mobility management comprises obtaining data samples for modeling a wireless network environment that comprises a plurality of cells and building a machine learning model of the wireless network using the obtained data samples. The machine learning model is trained to determine a sequence of handovers for a wireless device among the plurality of cells for the wireless device to traverse from a source cell to a destination cell. The method further comprises receiving mobility information for a wireless device, determining one or more handover operations for the wireless device based on the mobility information, and transmitting the one or more handover operations to the wireless device.

Efficient 3D mobility support using reinforcement learning

A method and network node for flexible indication of resources in LTE-M using bitmaps are disclosed. According to one aspect, a method includes indicating to the wireless device a set of reserved resources for machine communications in compatibility with a broadband radio access technology sharing resources in a time frame and frequency band that encompasses the set of reserved resources, the indicating using a two level bitmap operating in the time-domain, a first bitmap level of the two level bitmap indicating a first set of subframes containing reserved resources, and a second bitmap level of the two level bitmap indicating reserved symbols within an indicated subframe.

Long term evolution-M resource reservation using bitmap

A method performed by a User Equipment (UE) for handling a Control Resource Set (CORESET) from a network node in a wireless communications network is provided. The UE operates with a reduced bandwidth. The UE detects a CORESET from the network node, and that a bandwidth of the CORESET is larger than the bandwidth of the UE. Physical Downlink Control Channel (PDCCH) candidates are transmitted in the CORESET. The UE determines which part of the CORESET to skip, to make the bandwidth of the CORESET equal or smaller than the bandwidth of the UE, such that the UE is capable of receiving the CORESET. The part of the CORESET to be skipped is determined based on a predicted decoding performance of the PDCCH candidates in the CORESET.

User equipment, network node and methods in a wireless communications network

A wireless device () or a radio network node () is configured to communicate in a wireless communication network (). The wireless device () or radio node in this regard transmits or receives a signal on an Narrowband Internet-of-Things, NB-IoT, carrier (). The NB-IoT carrier () is within a bandwidth of a New Radio, NR, carrier (), has a frequency center () whose position satisfies a requirement on that position relative to a channel raster (), and has two or more subcarriers which each align in frequency with a respective subcarrier of the NR carrier ().

NR and NB-IoT coexistence

A method and apparatus for design and optimization of a network are described. A first deep neural network is used to obtain a function that represents a relationship between design parameters of the network and network performance metrics of the network. A second deep neural network is used to obtain a subset of one or more candidate network deployment configurations that optimize the performance metrics for the network. An optimal candidate network deployment configuration for the network is selected from the subset of candidate network deployment configurations wherein the optimal candidate network deployment configuration maximizes performance of the network as defined based on the performance metrics.

Network design and optimization using deep learning

In one aspect, a method for communicating in a wireless communication network includes transmitting or receiving () using an LTE-M carrier within the bandwidth of an NR carrier such that the LTE-M carrier overlaps at least a portion of NR guard band. The transmitting or receiving may be subject to aligning subcarriers in LTE-M and NR on the same grid and subject to raster placement. The LTE-M carrier may be positioned within the NR carrier so as to minimize the number of NR resource blocks occupied by the LTE-M carrier.

Growing community of inventors

San José, CA, United States of America

Mohammad Mozaffari