Telefonaktiebolaget Lm Ericsson (publ)

Ericsson Gmbh

Sas Institute Inc.

Douglas Allan Cairns

Gregory Edward Bottomley

Elias Jonsson

Yi-Pin Eric Wang

Andres Reial

Stephen J Grant

Tracy Lawrence Fulghum

Ali S Khayrallah

Anders Rosenqvist

Oskar Drugge

Muhammad Ali Kazmi

Jung-Fu Cheng

Anders Wallén

Carmela Cozzo

Karl James Molnar

Leonid Krasny

Andreas Cedergren

Kazuyoshi Uesaka

L Scott Bloebaum

Jaroslaw Niewczas

David Bruce Elsheimer

Xilong Chen

Jan Chvosta

Håkan B Eriksson

Mathias Riback

Yoshitaka Murata

Gunce Eryuruk Walton

Ming-Chun Chang

Göran Bergman

Yang Zhao

Hiroaki Watabe

Håkan Bjorkegen

Stephen Fraleigh

Michael Thomas Lamm

Gregory B Bottomley

Yi-Pin-Eric Wang

Hakan Bengt Bjorkegren

Yi-Ping Eric Wang

Goeran Bergman

A treatment model that is a first neural network is trained to optimize a treatment loss function based on a treatment variable t using a plurality of observation vectors by regressing t on x,z. The trained treatment model is executed to compute an estimated treatment variable value {circumflex over (t)}for each observation vector. An outcome model that is a second neural network is trained to optimize an outcome loss function by regressing y on xand an estimated treatment variable t. The trained outcome model is executed to compute an estimated first unknown function value {circumflex over (&#x3b1;)}(x) and an estimated second unknown function value {circumflex over (&#x3b2;)}(x) for each observation vector. An influence function value is computed for a parameter of interest using {circumflex over (&#x3b1;)}(x) and {circumflex over (&#x3b2;)}(x). A value is computed for the predefined parameter of interest using the computed influence function value.

Causal inference and policy optimization system based on deep learning models

Exemplary embodiments relate to the problem of determining measurements in a distributed computing environment in which observations relating to the measurements are distributed amongst two or more nodes. Each node, which stores a number of node-specific observations, makes available its observation count and a number of observation sketches. The observations are merged into an array, and the sketches from each node are combined into overall summary sketches representing a summary of the observations across all the nodes. The summary sketches may then be used to approximate the measurement. The described techniques allow for the computation of arbitrary measurements (i.e., measurements that are not predetermined and for whose calculation the environment is not preconfigured) in a grid computing environment with a technical advantage of having very few rounds of data communication (e.g., two or less) required between the nodes in the computing grid.

Efficient computations and network communications in a distributed computing environment

A computing device determines upper and lower bounds of a largest singular value for an approximate decomposition of a dataset. An approximate decomposition is computed using either a principal components or a singular value decomposition algorithm. A lower bound of a largest singular value is computed for the computed approximate decomposition using a first linear approximation to a function of a singular value ratio. A first set of coefficients for a second linear approximation to an error function is computed for the function of the singular value ratio using the computed approximate decomposition. A second set of coefficients for a third linear approximation is computed using the computed first set of coefficients. An upper bound of the largest singular value is computed using the computed second set of coefficients. The upper bound and the lower bound are output to provide an estimate of a quality of the decomposition.

Analytic system for selecting a decomposition description of sensor data

A method and apparatus for determining operating modes in a receiver is described herein. A delay searcher in the receiver detects a signal image in the received signal. When the receiver is a RAKE receiver, a plurality of RAKE fingers coherently combine time-shifted versions of the received signal at different delays. Alternatively, when the receiver is a chip equalization receiver, an FIR filter coherently pre-combines the signal images in the received signal. A processor determines delays. In particular, the processor generates a first signal quality metric for a single-delay receiver mode, and generates a second signal quality metric for a multi-delay receiver mode. Based on a comparison of the first and second signal quality metrics, the processor selects the single-delay or the multi-delay receiver mode for processing the signal image.

Adaptive timing recovery via generalized RAKE reception

A receiver and method for receiving and processing a sequence of transmitted symbols in a digital communication system utilizing soft pilot symbols. A set of soft pilot symbols are transmitted with higher reliability than the remaining symbols in the sequence by modulating the soft pilot symbols with a lower order modulation such as BPSK or QPSK while modulating the remaining symbols with a higher order modulation such as 16 QAM or 64 QAM. The receiver knows the modulation type and location (time/frequency/code) of the soft pilot symbols, and demodulates them first. The receiver uses the demodulated soft pilot symbols as known symbols to estimate parameters of the received radio signal. Unlike traditional fixed pilots, the soft pilots still carry some data. Additionally, the soft pilots are particularly helpful in establishing the amplitude reference essential in demodulating the higher order modulation symbols.

Receiver and method for processing radio signals using soft pilot symbols

A wireless communication receiver is configured to suppress interference with respect to a received signal of interest on a selective basis responsive to evaluating whether the receiver currently is or is not operating in a colored noise/interference environment. For example, an exemplary Code Division Multiple Access (CDMA) mobile station activates or deactivates interference suppression responsive to determining and evaluating an orthogonality factor, which, in this context, serves as a measure of how much downlink power gets converted into same-cell interference via multipath propagation. The orthogonality factor thus serves as an indicator of noise plus interference coloration. In one or more exemplary embodiments, then, an exemplary receiver circuit is configured to determine the orthogonality factor, evaluate it, and selectively enable or disable received signal whitening based on that evaluation. The exemplary receiver circuit and associated selective whitening method can be applied to various receiver architectures and signal types.

Method and apparatus for controlling interference suppressing receivers

A multi-carrier linear equalization receiver, e.g., a RAKE receiver or chip equalization receiver, is described herein. The multi-carrier receiver distributes processing delays among a plurality of received carriers based on a dispersion determined for each carrier. The receiver initially allocates a minimum number of processing delays sufficient for light dispersion to each carrier. For the dispersive carriers, the receiver allocates one or more additional processing delays. In one embodiment, the additional processing delays are allocated to the dispersive carriers based on SIR.

Method and apparatus for allocating processing delays in multi-carrier systems

Channel estimation and/or equalization processing is performed in a wireless receiver in two stages. The first stage involves pre-filtering in the frequency domain to compact a grid-based representation of the net channel. The second stage involves implementing reduced-complexity time domain channel estimation and/or equalization. According to one embodiment, a received signal transmitted over a net channel is processed by pre-filtering the received signal in the frequency domain. The frequency domain pre-filtering compacts an N-tap effective grid-based representation of the net channel into a K-tap compacted grid-based representation of the net channel where K&#x3c;N. The pre-filtered received signal is equalized in the time domain based on the K-tap compacted grid-based representation of the net channel generated by pre-filtering the received signal in the frequency domain.

Joint time/frequency processing for wireless receivers

A transmitter, channel coder, and method for coding and transmitting a sequence of symbols in a digital communication system utilizing soft pilot symbols. In one embodiment, the transmitter transmits a set of soft pilot symbols with higher reliability than the remaining symbols in the sequence by modulating the soft pilot symbols with a lower order modulation such as BPSK or QPSK while modulating the remaining symbols with a higher order modulation such as 16 QAM or 64 QAM. The transmitter shares the modulation type and location (time/frequency/code) of the soft pilot symbols with a receiver. Unlike traditional fixed pilots, the soft pilots still carry some data. Additionally, the soft pilots are particularly helpful in establishing the amplitude reference essential in demodulating the higher order modulation symbols. In another embodiment, soft pilot symbols are inserted by low-level puncturing of channel encoded bits and replacing the punctured bits with known bit patterns.

Transmitter and method for transmitting soft pilot symbols in a digital communication system

A signal-to-interference estimate is generated using unknown data symbols in place of or in addition to pilot symbols. Data received over a data channel (traffic channel or control channel) are collected. The data symbols are then used to compute an observation metric based on deviations of the data symbols from a predetermined set of possible data symbols, wherein one of the data symbols and symbol constellation is normalized. A data channel signal-to-interference ratio is then computed based on the observation metric.

Data-aided SIR estimation

A method of operating a User Equipment (UE) for generating a second scrambling code group where the UE is configured for receiving downlink transmission from a Universal Mobile Telecommunications System Terrestrial Radio Access Network (UTRAN) on a set of at least two downlink carriers including an anchor carrier and at least a first secondary carrier includes: determining a first scrambling code group associated with a first cell on the anchor carrier and deriving the second scrambling code group associated with a second cell on said first secondary carrier using a predefined rule defining the relation between the second scrambling code group and the first scrambling code group.

Methods and devices for allocating scrambling codes

A CDMA receiver computes an accurate estimate of the data to pilot power ratio. First, a biased estimate of the data to pilot power ratio is obtained from the data channel. A multiplicative correction factor is then computed from the pilot channel, and applied to the biased data to pilot power ratio estimate.

Data to pilot ratio estimation

The computation of code-specific channel matrices for an Assisted Maximum Likelihood Detection (AMLD) receiver comprises separately computing high rate matrices that change each symbol period, and a low rate matrix that is substantially constant over a plurality of symbol periods. The high and low rate matrices are combined to generate a code-specific channel matrix for each receiver stage. The high rate matrices include scrambling and spreading code information, and the low rate matrices include information on the net channel response and combining weights. The low rate matrices are efficiently computed by a linear convolution in the frequency domain of the net channel response and combining weights (with zero padding to avoid circular convolution), then transforming the convolution to the time domain and extracting matrix elements. Where the combining weights are constant across stages, a common code-specific channel matrix may be computed and used in multiple AMLD receiver stages.

Method and apparatus for efficient AMLD matrix computations

The technology comprises method(s) and apparatus for operating a telecommunications system. In its basic form the method comprises providing plural channelization codes for potential use by an uplink receiver; using unused channelization codes of the plural codes to generate an estimate of an impairment covariance matrix; and using the estimate of the impairment covariance matrix to form a processing parameter. For example, the processing parameter can be one or more weight values which, in turn, are can be used for generating a combined output signal.

Efficient method for forming and sharing impairment covariance matrix

Adaptive reconfiguration of a wireless receiver is enabled based on channel geometry. According to an embodiment, the wireless receiver includes a geometry factor processing module and signal processing modules, e.g. such as but not limited to an SIR estimation module, a power estimation module, a despreading module, a low-pass filter, a combing weight generation module, a coefficient estimation module, a synchronization control channel interference canceller module, etc. The geometry factor processing module determines a geometry factor for the channel over which signals are transmitted to the wireless receiver, the geometry factor being a measure of the ratio of total transmitted power received by the wireless receiver to total interference plus noise power at the wireless receiver. One or more of the receiver signal processing modules are reconfigurable based on the geometry factor.

Growing community of inventors

Durham, NC, United States of America

Douglas Allan Cairns