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:
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:
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:
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.
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:
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:
Apparatus and methods for channel estimation include 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, 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, and determining a third set of tap positions by clustering each tap position included in the second set of tap positions.