Lucent Technologies Inc.

Alcatel Lucent

Future Wei Technologies, Inc.

Huawei Technologies Co., Limited

Nandu Gopalakrishnan

Ashok N Rudrapatna

Ganapathy Subramanian Sundaram

Achilles George Kogiantis

Farooq Khan

Srinivas R Kadaba

Teck H Hu

Ashwin Sampath

Pantelis Monogioudis

Yan Xin

Jung-Tao Liu

Jin Yang

Yongxi Tan

Wenfeng Zhang

Yirui Hu

Arnab Das

Krishna Balachandran

Joseph H Kang

Tomas S Young

Yanjie Fu

Mehmet Oguz Sunay

Niranjan S Joshi

James Matthew

Sanjiv Nanda

Hongwei Kong

Harish Viswanathan

Alexei Ashikhmin

Adriaan J De Lind Van Wijngaarden

Francis Dominique

Anil M Rao

Stanley Vitebsky

Walid Elias Nabhane

Emina Soljanin

Jaehyeong Kim

James Paul Seymour

Pengfei Zhu

Mark Michael Clougherty

Danny De Vleeschauwer

Andre Beck

Gang Li

Naresh Sharma

Dandan Wang

Iyad Alfalujah

James Mathew

Sudhir Ramakrishna

Kamalaharan Dushyanthan

Danny De Vleesschawuer

Steve A Benno

Niranjan Sudhir Joshi

Baoling Sheen

System and method embodiments are provided for adaptive anomaly detection based predictor for network data. In an embodiment, a computer-implemented method in a network component for predicting values of future network time series data includes receiving, with one or more receivers, network time series data; determining, with one or more processors, whether an anomaly is detected in the network time series data; generating, with the one or more processors, a prediction associated with the network data according to a primary predictor when no anomaly is detected in the network time series data; generating, with the one or more processors, the prediction associated with the network data according to an alternative predictor when an anomaly in the network time series data is detected; and sending, with one or more transmitters, the prediction to a network controller, wherein the network controller uses the prediction to adjust network parameters.

Future network condition predictor for network time series data utilizing a hidden Markov model for non-anomalous data and a gaussian mixture model for anomalous data

Techniques for optimizing configuration parameters in a wireless network may iteratively adjust one or more wireless configuration parameters during a first stage of an adjustment period until either a cost increase during a single iteration exceeds an upper cost threshold or (ii) the number of successive iterations exhibiting a per-iteration cost increase between the upper cost threshold and a lower cost threshold exceeds a threshold number of iterations. This may trigger the AP proceed to a second stage of the adjustment period, where the AP may adjust the same wireless configuration parameter in an opposite direction, maintain a value of the wireless parameter, or adjust a different wireless configuration parameter during the second stage. Progression between successive adjustment periods may be at least partially coordinated between APs in a group of APs.

Self-learning, adaptive approach for intelligent analytics-assisted self-organizing-networks (SONs)

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)

An anomaly detection apparatus, method, and computer program product are provided using a probabilistic latent semantic analysis (PLSA). In use, data is received, and a PLSA is performed, based on the data. Further, one or more anomalies are detected in the data, based on the PLSA. Still yet, information identifying the one or more anomalies is stored and/or displayed.

Anomaly detection apparatus, method, and computer program using a probabilistic latent semantic analysis

A method includes receiving an anomaly data point and comparing the anomaly data point to a magnitude bounding box to produce a first comparison. The method also includes comparing the anomaly data point to a principal component analysis (PCA) bounding box to produce a second comparison and classifying the anomaly data point in accordance with the first comparison and the second comparison to produce a classification.

System and method for anomaly root cause analysis

Adjusting cell specific antenna configuration parameters includes receiving, at each of a plurality of radio access nodes in a network, measurement reports from a plurality of user equipment devices. Base incremental adjustments to configuration parameters of one or more antennas are performed at each radio access node in response to the measurement reports. Additional measurement reports are received from the plurality of user equipment devices after the incremental adjustments. Base incremental adjustments to the configuration parameters of the one or more antennas at the radio access nodes continue to be performed in response to the measurement reports after previous incremental adjustments until an improvement limit has occurred. Biased random adjustments to the configuration parameters of the one or more antennas at the radio access nodes are performed in response to the improvement limit until a desired optimum result is achieved.

Method and apparatus for optimizing cell specific antenna configuration parameters

A method for determining cell states to adjust antenna configuration parameters includes receiving, at a radio access nodes in a network, measurement reports from a plurality of user equipment devices. The radio access node performs a weak coverage analysis in response to the measurement reports to determine whether a cell provided by the radio access node is assigned a good coverage state or a weak coverage state. The radio access node performs an overshooting analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned an overshooter state or a non-overshooter state. The radio access node performs an interference analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned an interferer state or a non-interferer state. The radio access node performs a quality analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned a good quality state or a bad quality state. Adjustments are made to antenna configuration parameters of the cell provided by the radio access node in response to the various states assigned to the cell.

Method and apparatus for determining cell states to adjust antenna configuration parameters

A method of allocating resources for transmitting content from a network element in a communications network to one or more mobile devices each in communication with the network element may include receiving, at the network element, characteristic information corresponding to each of the one or more mobile devices; and generating one or more adaptive guaranteed bit rate (AGBR) values at the network element corresponding to each of the one or more mobile devices, respectively. The AGBR values may be GBR values generated for each of the one or more mobile devices based on the corresponding characteristic information. A first scheduling algorithm may be executed at the network element based on the one or more AGBR values; and resources may be allocated to the one or more mobile devices based on an output of the scheduling algorithm.

Method and apparatus for improving adaptive streaming video quality by optimizing resource allocation

The present invention provides a method of providing rate tiers in a wireless communication system. Embodiments of the method include forming, at a network element in the wireless communication system, a statistical representation of resource usage for a user in the wireless communication system as a function of location and/or time using measurements of the user's resource usage at a plurality of locations. Embodiments of the method also include defining, at the network element, a plurality of rate tiers based on the statistical representation. Each rate tier indicates a rate for a different level of resource usage offered to the user.

Method of providing rate tiers in wireless communication systems

A system and method for a partner network sharing architecture is provided. In an embodiment a piece of user equipment that is part of a partner network is handed off or otherwise attached to a wholesale network. The identification of the partner network that the piece of user equipment originated from is determined by an ordering of a list of PLMN IDs that is transmitted to the wholesale network.

System and method for partner network sharing architecture

A method is provided a wireless system for reliably transmitting context information in robust header compression at low signal energies. More particularly, the methodology of the invention provides an elongated virtual Transmission Time Interval (Super TTI) for the first few (in particular, the first) non-compressed packet (that includes upper layer headers) of a packet stream transmitted using ROHC compression. Improved reception reliability for the uncompressed packet, in particular to decode the headers, results by application to the Super TTI of a combination of TTI Bundling techniques, RLC segmentation and association with multiple HARQ processes and use of enough HARQ rounds.

Method for improved robust header compression with low signal energy

The present invention provides a method of scheduling guaranteed bit rate and/or maximum bit rate applications. Embodiments of the method may include setting, for a mobile node during a time interval, a first weight equal to a sum of a previous first weight associated with the mobile node during a previous time interval and a correction factor that is a linear function of a difference between a first bit rate and an indication of a throughput of the mobile node. Embodiments of the method may also include scheduling communication with the mobile node based on the first weight.

Method of scheduling and admission control for guaranteed bit rate and/or maximum bit rate services

A system and method for wireless communication includes multiplexing an EUDC downlink control channel so that it is transmitted like a downlink dedicated channel (DL-DPCH). The EUDC downlink control channel can be multiplexed with the DL-DPCH by code or by both code and time. The EUDC downlink control channel may be multiplexed with a downlink dedicated physical data channel (DL-DPDCH), a downlink dedicated physical control channel (DL-DPCCH), or both. In one embodiment, the EUDC downlink control channel is multiplexed by adding a multicode channel to a current DL-DPCH and treating the EUDC downlink control channel as a dedicated channel with power control functionality.

Method for carrying downlink control information for an enhanced uplink dedicated channel

Improved ranking and grouping techniques are disclosed for communication systems such as a multiple input multiple output system. For instance, techniques are disclosed for ranking and grouping users that are eligible for single-user and/or multiple-user transmissions. In one case, ranking and grouping are performed independently and, in another case, ranking and grouping are performed jointly.

Ranking and grouping of transmissions in communication system

Growing community of inventors

Chatham, NJ, United States of America

Nandu Gopalakrishnan