Abstract: A process of wireless communication for obtaining channel quality information alignment includes predicting a channel state of a future downlink subframe of a signal. The process also includes providing a base station with a set of parameters based on the predicted channel state. For example, a user equipment (UE) can obtain a recommended transport block size (RTBS) from the predictor process, and return the RTBS to the base station as one of the set of parameters.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a multilayer perceptron neural network with Hammerstein structure by dividing an aggressor signal into real and imaginary components, augmenting the components by weight factors, executing a linear combination of the augmented components, and executing a nonlinear sigmoid function for the combined components at a hidden layer of multilayer perceptron neural network to produce a hidden layer output signal. At an output layer, hidden layer output signals may be augmented by weight factors, and the augmented hidden layer output signals may be linearly combined to produce real and imaginary components of an estimated jammer signal.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a multilayer perceptron neural network with Hammerstein structure by dividing an aggressor signal into real and imaginary components, augmenting the components by weight factors, executing a linear combination of the augmented components, and executing a nonlinear sigmoid function for the combined components at a hidden layer of multilayer perceptron neural network to produce a hidden layer output signal. At an output layer, hidden layer output signals may be augmented by weight factors, and the augmented hidden layer output signals may be linearly combined to produce real and imaginary components of an estimated jammer signal.

Abstract: The various embodiments include methods and apparatuses for cancelling nonlinear interference during concurrent communication of dual-technology wireless communication devices. Nonlinear interference may be estimated using a multilayer perceptron neural network by augmenting aggressor signal(s) by weight factors, executing a linear combination of the augmented aggressor signals, and executing a nonlinear sigmoid function for the combined aggressor signals at a hidden layer of multilayer perceptron neural network to produce a hidden layer output signal. Multiple hidden layers may repeat the process for the hidden layer output signals. At an output layer, hidden layer output signals may be augmented by weight factors, and the augmented hidden layer output signals may be linearly combined to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal. The weight factors may be trained based on a determination of an error of the estimated nonlinear interference.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a multi-model radial basis function neural network with Hammerstein structure by executing a radial basis function on aggressor signals at a hidden layer of the radial basis function neural network with Hammerstein structure to obtain hidden layer outputs, augmenting aggressor signal(s) by weight factors, infusing the hidden layer outputs by infusion factors, and, executing a linear combination of the augmented output, at an intermediate layer to produce a combined hidden layer outputs. At an output layer, a linear filter function may be executed on the hidden layer outputs to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a radial basis function neural network with Hammerstein structure by executing a radial basis function on aggressor signals at a hidden layer of the radial basis function neural network with Hammerstein structure to obtain hidden layer outputs, augmenting aggressor signal(s) by weight factors and, executing a linear combination of the augmented output, at an intermediate layer to produce a combined hidden layer outputs. At an output layer, a linear filter function may be executed on the hidden layer outputs to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a mixed-model block least squares/radial basis function neural network by generating aggressor kernels from the aggressor signals, augmenting the aggressor kernels by weight factors and executing a linear combination of the augmented output, at an intermediate layer to produce intermediate layer outputs. At an output layer, a linear filter function may be executed on the intermediate layer outputs to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a support vector regression interference filter by generating one or more aggressor kernels, augmenting the one or more kernels by weight factors, and executing a regression function of the augmented components, to produce an estimated jammer signals. At an output layer, estimated jammer signals may be linearly combined to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.

Abstract: The various embodiments include methods and apparatuses for cancelling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a minimum mean squares interference filter by generating aggressor kernels from the aggressor signals, augmenting the aggressor kernels by weight factors and executing a linear combination of the augmented output, at an intermediate layer to produce intermediate layer outputs. At an output layer, a linear filter function may be executed on the intermediate layer outputs to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a radial basis function neural network with Hammerstein structure by executing a radial basis function on aggressor signals at a hidden layer of the radial basis function neural network with Hammerstein structure to obtain hidden layer outputs, augmenting aggressor signal(s) by weight factors and, executing a linear combination of the augmented output, at an intermediate layer to produce a combined hidden layer outputs. At an output layer, a linear filter function may be executed on the hidden layer outputs to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a block least squares function interference filter by generating aggressor kernel matrices from the aggressor signals, augmenting the aggressor kernel matrices by weight factors and executing a linear combination of the augmented output, at an intermediate layer to produce intermediate layer outputs. At an output layer, a linear filter function may be executed on the intermediate layer outputs to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.

Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a multi-layer perceptron neural network with Hammerstein structure by dividing an aggressor signal into real and imaginary components, augmenting the components by weight factors, executing a linear combination of the augmented components, and executing a nonlinear sigmoid function for the combined components at a hidden layer of multi-layer perceptron neural network to produce a hidden layer output signal. At an output layer, hidden layer output signals may be augmented by weight factors, and the augmented hidden layer output signals may be linearly combined to produce real and imaginary components of an estimated jammer signal.

Abstract: Apparatus, methods, and computer program product for wireless communication, including receiving a plurality of chips in a time division synchronous code division multiple access (TD-SCDMA) network; performing channel matched filtering, despreading, and descrambling on the plurality of chips to determine a plurality of received symbols for each of a plurality of cells; performing symbol-level inter-cell interference cancellation on the plurality of received symbols to determine a plurality of serving cell symbol estimates; and performing multi-user detection on the plurality of serving cell symbol estimates to determine a plurality of detected serving cell symbols.

Abstract: Methods and apparatus for managing interference are described and may include updating a covariance inverse value of a linear function to remove an effect on the linear function of a first set of channels associated with a first network entity, wherein the first set of channels are cancelled in response to performing a first cancellation procedure. Methods and apparatus for managing interference may further include performing a second cancellation procedure to cancel a second set of channels associated with a second network entity based at least in part on the updated covariance inverse value of the linear function.

Abstract: Apparatus and methods for wireless communication include receiving, in a time division synchronous code division multiple access (TD-SCDMA) network, a first number of symbols before a midamble, the midamble, and a second number of symbols after the midamble; determining first forward and backward probabilities for a first subset of the first number of symbols and second forward and backward probabilities for a second subset of the second number of symbols; determining first posterior probabilities for the first subset of the first number of symbols and second posterior probabilities for the second subset of the second number of symbols; determining a first target posterior probability and a second target posterior probability; detecting a first target symbol and a second target symbol; and determining a first channel estimate corresponding to the first target symbol and a second channel estimate corresponding to the second target symbol.

Abstract: A process of wireless communication for obtaining channel quality information alignment includes predicting a channel state of a future downlink subframe of a signal. The process also includes providing a base station with a set of parameters based on the predicted channel state. For example, a user equipment (UE) can obtain a recommended transport block size (RTBS) from the predictor process, and return the RTBS to the base station as one of the set of parameters.

Abstract: Systems and methods of receiving data in a communication system are disclosed. The methods include equalizing a plurality of samples to suppress intersymbol interference and provide a first set of detected bits based on a first set of reference bits comprising a training sequence on a first iteration. The methods further include suppressing co-channel interference in the plurality of input samples and provide a set of suppressed samples based on a second set of reference bits comprising the first set of detected bits on a second iteration. The methods further include equalizing the set of suppressed samples to suppress intersymbol interference and provide a second set of detected bits based on the second set of reference bits on the second iteration.

Abstract: This disclosure provides systems, methods and apparatus for finite rate of innovation channel estimation. In one aspect an apparatus for equalizing received signals is provided. The apparatus comprises a signal per-processing unit configured to process received pilot signals transmitted through a sparse channel into at least one composite signal. The at least one composite signal further includes a plurality of signal peaks. The apparatus further comprises a Fourier transform unit configured to transform the at least one composite signal into frequency-domain data and a channel estimation unit configured to estimate at least one delay value and at least one peak value from the frequency-domain data.

Abstract: Apparatus and methods for channel estimation in time division synchronous code division multiple access (TD-SCDMA) based on a signal received from one or more Node Bs include determining least squares channel metric estimates based on the received signal, identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations of the least squares channel metric estimates or composite hypothesis testing on the least squares channel metric estimates, and updating an interference buffer based on the signal taps and the noise taps.

Abstract: Apparatus and methods for channel estimation includes determining two streams corresponding to odd and even samples of a received signal that is sampled at a first chip rate, performing least squares successive interference cancellation on each of the two streams to obtain odd and even raw channel estimates, interlacing the odd and even raw channel estimates to obtain interlaced channel estimates, interpolating additional samples in the interlaced channel estimates to create higher chip rate channel estimates, identifying a first set of tap positions based on the higher chip rate channel estimates, and applying matching pursuit to the first set of tap positions to identify a second set of tap positions, wherein the second set of tap positions includes fewer tap positions than the first set of tap positions.