Collision Communications, Inc.

Bae Systems Information and Electronic Systems Integration Inc.

Worcester Polytechnic Institute

Collison Communications, Inc.

Brandon P Hombs

Joseph Farkas

Sayak Bose

Sagar Dhakal

Barry West

Seyedmehdi S Nokhodberiz

John A Tranquilli, Jr

Scott A Kuzdeba

Daniel Massar

Joshua D Niedzwiecki

Rachel E Learned

Leonard E Russo

Jonathan P Beaudeau

Matthew Anderson

Alexander M Wyglinski

Peter J Kajenski

A method of assessing the effectiveness of an electronic countermeasure (ECM) applied against an unknown, ambiguous, or unresponsive radar threat includes monitoring changes in a radar-associated factor while applying the ECM and determining if the ECM is disrupting the hostile radar. The radar-associated factor can be a weapon that is controlled by the radar threat, and assessing the ECM can include determining whether the weapon is misdirected due to applying the ECM. Or the radar-associated factor can be a feature of an RF waveform emitted by the radar threat, and assessing the ECM can include determining if the feature is changed due to applying the ECM. Continuous changes in the feature can indicate unsuccessful attempts to mitigate the ECM. Return of the feature to a pre-threat state can indicate disruption of the radar. The ECM can be selected from a library of countermeasures pre-verified as effective against known threats.

Realtime electronic countermeasure assessment

A closed loop, real-time, cognitive Electronic Warfare (EW) system without a threat database includes an EW receiver for receiving radar threat signals; a Signal Analysis and Characterization module; a Pulse to Emitter Association sub-module; a Function De-interleaving Classifier sub-module; a Threat Behavior Model sub-module; a Countermeasures Synthesis module; a Capability, Severity, and Intent sub-module; a Countermeasure Selection sub-module; a Countermeasure Optimization sub-module; a Countermeasures Effectiveness Assessment module; a Resource Management module; and an EW transmitter.

Radar electronic countermeasures without a threat database

A method of selecting and optimizing a countermeasure for application against a novel, ambiguous, or unresponsive radar threat includes selecting a candidate countermeasure and an initial parameter set and varying at least one of the parameters while the effectiveness of the candidate countermeasure against the radar threat is assessed, for example by a human observer. Embodiments include repeating the process with additional candidate countermeasures. For an unresponsive radar threat, a previously effective countermeasure can be selected as the candidate countermeasure. For an ambiguous radar threat, at least one countermeasure previously verified as effective against a partially matching known threat can be selected as the candidate countermeasure. Correlated parameters can be simultaneously varied. An optimization surface and trajectory formed by a plurality of correlated parameters can be identified by machine intelligence, used to guide the parameter variations, and/or stored for use against the same or similar threats in the future.

Realtime electronic countermeasure optimization

Methods and systems are described for optimizing a predictive model for mobile network communications based on historical context information. In one aspect, historical context information is collected including at least one of communication environment, communication parameter estimates, mobile device statistics, mobile device transmit settings, base station receiver settings, past network statistics and settings, and adjacent network node information statistics and settings, the historical context information including data from communications of at least one mobile device. A predictive model for network communications is determined based on the historical context information. A communication context for a first mobile device different than the at least one mobile device is determined. The first device is scheduled and/or network parameters are set based on the determined predictive model and communication context.

Methods, systems, and computer program products for optimizing a predictive model for mobile network communications based on historical context information

Methods and systems are described for jointly processing multiple sectors in a wireless communication network. In one aspect, a first antenna serving a first sector is associated with a second antenna serving a second sector for joint processing. First and second antenna data is received. A plurality of wireless users associated with at least one of the first or second antenna data to model for channel estimation is determined, including an interfering wireless user connected via a third antenna serving a third sector not currently being jointly processed with the first or second antenna data. Channel estimates are determined for the plurality of wireless users. The first and second antenna data is jointly processed. Interference from the wireless user connected via a third antenna is suppressed based on a determined corresponding channel estimate for the wireless user and other received information for the wireless user.

Methods, systems, and computer program products for jointly processing multiple sectors in a wireless communication network

Methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO wireless network include receiving data corresponding to transmission of training signals from a plurality of users to a base station over a MIMO wireless network, determining a limited data set by limiting the received data in a time domain according to an estimated maximum delay spread, forming a well-conditioned low rank training matrix by identifying a channel model, estimating an active tap from the formed well-conditioned low rank training matrix, and subtracting a contribution of the selected active tap from the limited data set.

Method and system for compressed sensing joint channel estimation in a cellular communications network

A method and system are described for improving operating efficiency and QoS in a cellular communications network. According to an exemplary embodiment, the method includes predicting background interference levels due at least partly to signals generated in neighboring cells, and transmitting operating parameters to user equipment that include power, frequency, and/or spectral efficiency parameters. The operating parameters are selected according to the predicted background interference to provide acceptable quality of service while also optimizing use of available bandwidth. The method further includes updating the background interference predictions, and transmitting revised operating parameters to the user equipment according to rules that minimize changes to operating parameters that strongly affect background interference in neighboring cells, such as power levels and frequencies, thereby minimizing background interference fluctuations. Power levels for user equipment entering the cell can be initially minimized, and then slowly ramped to an optimal level. SPS can be implemented.

Method and system for improving efficiency in a cellular communications network

An improved receiver design implements a method for modeling users in SIC turbo loop multiuser detection architectures that reduces the number of implementation cycles, and thereby reduces the computational overhead associated with computing the inverse of the received signal covariance matrix, by efficiently reusing components of a QR decomposition. By reusing some of the computational results from the previous turbo loop's equalizer calculation, the disclosed receiver significantly reduces the computational burden of updating the linear equalizer on each turbo loop. Depending on the embodiment, this reduction can be accomplished in at least two different ways, depending on the dimensionality and other aspects of the implementation.

Wireless receiver for turbo loop multiuser detection incorporating reuse of QR component

An improved receiver design implements a practical method for modeling users in SIC turbo loop multiuser detection architectures, wherein in each loop unsubtracted estimation errors from previous loops are used to appropriately scale the error covariance matrix for each user, thereby accurately representing the remaining residual interference in the data stream for each desired user. The effect of estimation errors in previous interference cancellation operations is thereby minimized, and symbol estimations in successive turbo loops are improved, for example during multiuser MMSE, multiuser MMSE with interference rejection combining (MMSE-IRC), sample matrix inversion (SMI), or any of their adaptive variants (least mean-square, recursive least square, Kalman filter etc.). The estimated residual symbol energy can be computed per symbol, and then applied to entire data streams, to groups of symbols, or to each symbol separately.

Wireless receiver for multiuser detection incorporating residual estimation errors

Methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO wireless network include receiving training signals from a plurality of users, estimating a maximum delay spread for the received data according to a coherence bandwidth of the received data, limiting the received data in the time domain to the estimated maximum delay spread, selecting and estimating an active tap from the limited data set, and subtracting a contribution of the selected active tap from the reduced data set. These steps can be repeated until the residual signal falls below a specified minimum. The network can be a C-RAN network. The training data can be SRS or DMRS data. Limiting the received data ensures that only a few significant taps are analyzed, so that the system is not under determined and can be analyzed for accurate channel estimation using any of several existing algorithms.

Methods and systems are described for parameter estimation in a wireless communication network based on historical context information. In one aspect, a communication context for a first mobile device is determined, wherein the determined communication context includes at least a determined current location of the first mobile device within a portion of a cell of the communications system. The communication context is compared to a stored historical communication context of at least one other mobile device that was determined to previously be located in the portion of the cell. Parameters for communicating with the first mobile device are estimated based on the comparison. The first mobile device is communicated with using the estimated parameters.

Methods, systems, and computer program products for parameter estimation based on historical context information

Methods and systems for obtaining improved channel estimates for frequency-multiplexed data transmissions such as OFDM, OFDMA, or SC-FDMA transmissions overcome the limitations of the static assumption by using a polynomial or other fitting function to fit and model the frequency dependence of the channel coefficients, so that estimates can be applied to larger subcarrier groups. Some embodiments provide channel estimates for a singular signal source, while other embodiments provide joint channel estimates for a plurality of signal sources. In embodiments, selection of the fitting functions is influenced by all previously determined channel estimates. In some embodiments, a tracking algorithm allows use of the lowest possible order of polynomial or other fitting function to model the frequency dependence of the channel coefficients, whereby the channel estimate is continually shifted in frequency while the order of the polynomial or other fitting function remains low.

Polynomial mixture for frequency domain multiuser channel estimation and tracking in a wireless communication network

Methods and systems for obtaining improved joint channel estimates for a multi-user, frequency-multiplexed data transmission such as SC-FDMA or OFDM begins by estimating separate contributions of users (and/or other signal sources) to the received signal based on joint frequency domain channel estimates. A reduced data set is obtained by subtracting contributions of one or more users from the received data, leaving only the estimated contributions of the remaining users, with noise and residual estimation error signal. Time domain joint channel estimation is then performed on the reduced data set, which is feasible because the number of users has been reduced. In exemplary embodiments, the reduced data set includes only one estimated user contribution. This process is repeated to obtain channel estimates for all of the users. The method can be repeated by using the channel estimates to re-estimate the user contributions and calculate revised channel estimates.

Growing community of inventors

Nashua, NH, United States of America

Brandon P Hombs