Future Wei Technologies, Inc.

At&t Intellectual Property I, L.p.

Iyad Alfalujah

Cornelius Dawid Janse Van Rensburg

Kamalaharan Dushyanthan

Milap V Majmundar

Salam Akoum

Nandu Gopalakrishnan

Yan Xin

Suman Das

Jin Yang

Mark Ernest Newbury

Yongxi Tan

Yanjie Fu

James Mathew

Aspects of the subject disclosure may include, for example, identifying a first value corresponding to a constraint pertaining to a number of beams, conveying the first value to at least one communication device, and obtaining, based on the conveying, at least one report from the at least one communication device, wherein an at least a second value corresponding to a number of the beams referenced in the at least one report is less than or equal to the first value. Other embodiments are disclosed.

Apparatuses and methods for facilitating an upper bound in respect of a spatial domain beam selection

A base station is configured to perform a method for communicating with a plurality of user device (UD) multi-user multi-input multi-output (MU-MIMO) wireless system. The method includes receiving an indication of a selected beam from each of at least two UDs; determining, based on the indication of selected beam, a selected beam for each of the at least two UDs; generating a virtual UD for each combination of each selected beam; estimating a data rate for each virtual UD corresponding to the selected beam and the UD that selects the selected beam; estimating a power gradient for each selected beam; determining a power for each of the selected beams based on the power gradient for each of the selected beams; and scheduling outgoing radio frequency transmissions.

Method and apparatus for scheduling user device in multi-user multi-input multi-output wireless system

Convergence times associated with simulated annealing based (SA-based) optimization in wireless networks can be reduced by introducing an additional local or cell-level evaluation step into the evaluation of global solutions. In particular, new local solutions may be evaluated based on local performance criteria when the new solutions are in a global solution deemed to have satisfied a global performance criteria. New local solutions that satisfy their corresponding local performance criteria remain in the new global solution. New local solutions that do not satisfy their corresponding local performance criteria are replaced with a corresponding current local solution from a current global solution, thereby modifying the new global solution. The resulting modified global solution includes both new local solutions and current local solutions prior to being accepted as the current global solution for the next iteration.

Autonomous, closed-loop and adaptive simulated annealing based machine learning approach for intelligent analytics-assisted self-organizing-networks (SONs)

Embodiments are provided for calibration, preprocessing, and segmentation for user localization and network traffic density estimation. The embodiments include sending, from a network component, a request to a plurality of user equipment (UEs) to participate in reporting localization data. Reports for localization data including no-lock reports are received from at least some of the UEs. The no-lock reports indicate indoor UEs among the UEs. The network preprocesses the localization data by eliminating, from the localization data, data that increases the total noise to signal ratio. The localization data is then processed using a model that distinguishes between different buildings. This includes associating, according to a radio map, radio characteristics in the localization data with corresponding bins in a non-uniform grid of coverage. The non-uniform grid is predetermined to maximize uniqueness between the radio characteristics. The indoor UEs are associated with corresponding buildings using the no-lock reports data.

System and method for localization and traffic density estimation via segmentation and calibration sampling

An eNB is configured to perform a method for coordinating downlink power per layer at an eNB in a multiple-input, multiple-output (MIMO) network. The method includes receiving feedback from at least one UE; calculating a plurality of MIMO gradients based on the received feedback; changing a power per layer according to the calculated MIMO gradients; and exchanging gradient power information between the eNB and at least one neighboring eNB.

System and method for coordinated MIMO switching (CMS) in TDD/FDD-LTE

Growing community of inventors

Bedminster, NJ, United States of America

Iyad Alfalujah