Abstract:
A method and apparatus for use in data estimation in wireless communication are provided. A wireless communications signal is received and transformed to produce a received vector. The received vector is processed using a sliding window based approach that includes processing each of a plurality of windows. For each window, an approximate circulant channel response matrix is produced for use in estimating a data vector corresponding to the window.
Abstract:
A receiver or an integrated circuit (IC) incorporated therein includes a fast Fourier transform (FFT)-based (or hybrid FFT-based) sliding window block level equalizer (BLE) for generating equalized samples. The BLE includes a noise power estimator, first and second channel estimators, an FFT-based chip level equalizer (CLEQ) and a channel monitor unit. The noise power estimator generates a noise power estimate based on two diverse sample data streams. The channel estimators generate respective channel estimates based on the sample data streams. The channel monitor unit generates a first channel monitor signal including truncated channel estimate vectors based on the channel estimates, and a second channel monitor signal which indicates an approximate rate of change of the truncated channel estimate vectors. The FFT-based CLEQ generates the equalized samples based on the noise power estimate, one-block samples of the first and second sample data streams, the channel estimates and the monitor signals.
Abstract:
A receiver which suppresses inter-cluster multipath interference by processing an impulse channel response consisting of two multipath clusters, each cluster having groups of signals with multiple delays. In one embodiment, the receiver includes a single antenna and parallel-connected delay units used to align the groups of signals before being input into respective sliding window equalizers. The outputs of the equalizers are combined at chip level via a combiner which provides a single output. In another embodiment, a cluster multipath interference suppression (CMIS) circuit is incorporated into the receiver. The CMIS circuit includes a hard decision unit and a plurality of signal regeneration units to generate replicas of the multipath clusters. The replicas are subtracted from the respective outputs of the delay units and the results are input to the respective sliding window equalizers. In another embodiment, multiple antennas are used to receive and process the clusters.
Abstract:
Data estimation is performed in a wireless communication system using both oversampling and multiple reception antennas. A receive vector is produced for each antenna at a sampling interval which is a multiple of the chip rate of the received signal. A channel response matrix is produced for each antenna at a preferred multiple of the sampling rate. Each receive vector is processed using a sliding window based approach, where a plurality of successive windows are processed. For each window, a combined circulant channel response matrix is produced using the channel response matrices. Using the combined circulant channel response matrix and a combined received vector comprising each received vector in a discrete Fourier transform based approach to estimate a data vector corresponding to that window; and combining the data vector estimated in each window to form a combined data vector.
Abstract:
The present invention has many aspects. One aspect of the invention is to perform equalization using a sliding window approach. A second aspect reuses information derived for each window for use by a subsequent window. A third aspect utilizes a discrete Fourier transform based approach for the equalization. A fourth aspect relates to handling oversampling of the received signals and channel responses. A fifth aspect relates to handling multiple reception antennas. A sixth embodiment relates to handling both oversampling and multiple reception antennas.
Abstract:
A receiver which suppresses inter-cluster multipath interference by processing an impulse channel response consisting of two multipath clusters, each cluster having groups of signals with multiple delays. In one embodiment, the receiver includes a single antenna and parallel-connected delay units used to align the groups of signals before being input into respective sliding window equalizers. The outputs of the equalizers are combined at chip level via a combiner which provides a single output. In another embodiment, a Cluster Multipath Interference Suppression (CMIS) circuit is incorporated into the receiver. The CMIS circuit includes a hard decision unit and a plurality of signal regeneration units to generate replicas of the multipath clusters. The replicas are subtracted from the respective outputs of the delay units and the results are input to the respective sliding window equalizers. In another embodiment, multiple antennas are used to receive and process the clusters.
Abstract:
A receiver which suppresses inter-cluster multipath interference by processing an impulse channel response consisting of two multipath clusters, each cluster having groups of signals with multiple delays. In one embodiment, the receiver includes a single antenna and parallel-connected delay units used to align the groups of signals before being input into respective sliding window equalizers. The outputs of the equalizers are combined at chip level via a combiner which provides a single output. In another embodiment, a Cluster Multipath Interference Suppression (CMIS) circuit is incorporated into the receiver. The CMIS circuit includes a hard decision unit and a plurality of signal regeneration units to generate replicas of the multipath clusters. The replicas are subtracted from the respective outputs of the delay units and the results are input to the respective sliding window equalizers. In another embodiment, multiple antennas are used to receive and process the clusters.
Abstract:
A sliding window based data estimation is performed. An error is introduced in the data estimation due to the communication model modeling the relationship between the transmitted and received signals. To compensate for an error in the estimated data, the data that was estimated in a previous sliding window step or terms that would otherwise be truncated as noise are used. These techniques allow for the data to be truncated prior to further processing reducing the data of the window.
Abstract:
Data estimation is performed in a wireless communication system using both oversampling and multiple reception antennas. A receive vector is produced for each antenna at a sampling interval which is a multiple of the chip rate of the received signal. A channel response matrix is produced for each antenna at a preferred multiple of the sampling rate. Each receive vector is processed using a sliding window based approach, where a plurality of successive windows are processed. For each window, a combined circulant channel response matrix is produced using the channel response matrices. Using the combined circulant channel response matrix and a combined received vector comprising each received vector in a discrete Fourier transform based approach to estimate a data vector corresponding to that window; and combining the data vector estimated in each window to form a combined data vector.
Abstract:
A receiver or an integrated circuit (IC) incorporated therein includes a fast Fourier transform (FFT)-based (or hybrid FFT-based) sliding window block level equalizer (BLE) for generating equalized samples. The BLE includes a noise power estimator, first and second channel estimators, an FFT-based chip level equalizer (CLEQ) and a channel monitor unit. The noise power estimator generates a noise power estimate based on two diverse sample data streams. The channel estimators generate respective channel estimates based on the sample data streams. The channel monitor unit generates a first channel monitor signal including truncated channel estimate vectors based on the channel estimates, and a second channel monitor signal which indicates an approximate rate of change of the truncated channel estimate vectors. The FFT-based CLEQ generates the equalized samples based on the noise power estimate, one-block samples of the first and second sample data streams, the channel estimates and the monitor signals.