Abstract: Determination of equalizer coefficients from a sparse channel estimate begins by determining location of significant taps based on the sparse channel estimate of a multiple path communication channel. The sparse channel estimate indicates the positioning of signals received via the various multiple paths of the channel. The method then continues by determining feed-forward equalization coefficients based on the location of the significant taps. The method then continues by determining feedback equalization coefficients based on the feed-forward equalization coefficients and the sparse channel estimate.

Abstract: A communication device processes a preamble in the presence of impulse noise. The communication device receives a preamble sequence that includes a plurality of preamble symbols and determines that at least one preamble symbol of the plurality of preamble symbols has been adversely affected by impulse noise. Based upon this determination, the communication device masks the at least one preamble symbol of the plurality of preamble symbols to produce a subgroup of preamble symbols. Then, based upon the subgroup of preamble symbols, the communication device determines at least one of a frequency estimate for the subgroup of preamble symbols, a phase estimate for the subgroup of preamble symbols, and a gain estimate for the subgroup of preamble symbols. Based upon these estimates, the communication receiver corrects subgroup of preamble symbols and uses the result to perform channel estimation, to correct subsequently received symbols carrying data, etc.

Abstract: A communication device constructed according to the present invention detects impulse noise in a preamble sequence. In detecting impulse noise in the preamble sequence the communication device first receive a preamble sequence that includes a plurality of preamble symbols. The communication device then divides the plurality of preamble symbols by at least one known preamble symbol to produce a plurality of preamble gains and/or a plurality of preamble phases corresponding to the plurality of preamble symbols. Finally, the communication device determines, based upon the plurality of preamble gains and/or the plurality of preamble phases, that at least one preamble symbol has been adversely affected by impulse noise. The communication device may discard at least one preamble symbol that has been adversely affected by impulse noise from the plurality of preamble symbols.

Abstract: Cancellation of interference in a communication system with application to S-CDMA. A relatively straight-forward implemented and computationally efficient approach of selecting a predetermined number of unused codes is used to perform weighted linear combination selectively with each of the input spread signals in a multiple access communication system. If desired, the predetermined number of unused codes is always the same in each implementation. Alternatively, the predetermined number of unused codes is selected from within a reordered code matrix using knowledge that is shared between the two ends of a communication system, such as between the CMs and a CMTS. While the context of an S-CDMA communication system having CMs and a CMTS is used, the solution is generally applicable to any communication system that seeks to cancel narrowband interference. Several embodiments are also described that show the generic applicability of the solution across a wide variety of systems.

Abstract: Successive interference canceling for CMDA. ICI may result from a signal's multipath effects, or by filtering/suppression of some of the component energy of the signaling waveforms. Energy component attenuation destroys orthogonality of CDMA symbols thereby causing ICI. An ICF suppresses frequency domain portions (attenuates ingress), but also introduces ICI. Following the ICF, the signal is de-spread, sliced, re-spread and convolved with the ICF echoes (except first tap echoes). Convolving re-spread hard decisions with delayed ICF taps is equivalent to partially re-modulating the first-pass hard decisions to efficiently “add-back-in” the signal energy which was blanked/subtracted by the ICF. Alternatively, parameter estimation de-rotates and re-rotates soft symbols and hard decisions, respectively, compensating for undesirable symbol rotation. The convolved signal is subtracted from a delayed version of the ICF output signal.

Abstract: Iterative data-aided carrier CFO estimation for CDMA systems. Any communication receiver may be adapted to perform the iterative data-aided carrier CFO estimation. The iterative data-aided carrier CFO estimation is performed using a high accuracy method. The operation may be described as follows: a received signal is despread and buffered. Using the received preamble sequence, an initial estimate of the CFO is obtained. This estimate is used to correct the whole despread data. The corrected data using the initial CFO estimate is sliced. Each despread data symbol is divided by the corresponding sliced data decision. The obtained sequence is then averaged across different codes to obtain a less noisy sequence, which is then used to estimate the CFO again. The procedure can be repeated (iterated) to obtain a more accurate carrier frequency offset estimate; the number of times in which the procedure is repeated may be programmable or predetermined.

Abstract: Multi-Input-Multi-Output (MIMO) Optimal Decision Feedback Equalizer (DFE) coefficients are determined from a channel estimate h by casting the MIMO DFE coefficient problem as a standard recursive least squares (RLS) problem and solving the RLS problem. In one embodiment, a fast recursive method, e.g., fast transversal filter (FTF) technique, then used to compute the Kalman gain of the RLS problem, which is then directly used to compute MIMO Feed Forward Equalizer (FFE) coefficients gopt. The complexity of a conventional FTF algorithm is reduced to one third of its original complexity by choosing the length of a MIMO Feed Back Equalizer (FBE) coefficients bopt (of the DFE) to force the FTF algorithm to use a lower triangular matrix. The MIMO FBE coefficients bop are computed by convolving the MIMO FFE coefficients gopt with the channel impulse response h. In performing this operation, a convolution matrix that characterizes the channel impulse response h extended to a bigger circulant matrix.

Abstract: A relatively straight-forward implemented, and computationally efficient approach of selecting a predetermined number of unused codes is used to perform weighted linear combination selectively with each of the input spread signals in a multiple access communication system. If desired, the predetermined number of unused codes is always the same in each implementation. Alternatively, the predetermined number of unused codes are selected from within a reordered code matrix using knowledge that is shared between the two ends of a communication system, such as between the CMs and a CMTS. While the context of an S-CDMA communication system having CMs and a CMTS is used, the solution is generally applicable to any communication system that seeks to cancel narrowband interference. Several embodiments are also described that show the generic applicability of the solution across a wide variety of systems.

Abstract: A novel approach of repeated adaptation is provided that can be applied to either one or both of channel estimation and/or equalization. From an incoming data packet that includes data and a training sequence, a modified data packet is generated that includes the data, the training sequence, and at least one additional copy of the training sequence. From the format of this modified data packet, the same training sequence can be used over and over again a desired number of times to perform channel estimation and subsequent calculation of equalizer tap coefficients. Alternatively, the same training sequence can be used over and over again a desired number of times to converge the equalizer coefficient taps directly without doing any preliminary channel estimation. Generally, either of these approaches can be characterized as a cyclic adaptation operation that provides improved performance without incurring any reduction in throughput of the communication channel.

Abstract: A method and apparatus that provides an accurate estimate of the time and amplitude of arrival of the first arriving overlapping multipath components (rays) in wireless locating finding systems. Overlapping fading multipath components for mobile-positioning are resolved by exploiting the fact that multipath components fade independently. Although fast channel fading is usually considered a challenge to the location finding process, it is used as an additional tool to detect and resolve overlapping multipath rays. A projection technique is also provided that exploits all possible a-priori channel information into a adaptive filtering algorithm, thus providing needed robustness to divergence of the adaptive algorithm that might result from possible severe data matrix ill-conditioning and high noise levels, which are common in wireless location applications.

Abstract: Optimal Decision Feedback Equalizer (DFE) coefficients are determined from a channel estimate h by casting the DFE coefficient problem as a standard recursive least squares (RLS) problem, e.g., the Kalman gain solution to the RLS problem. A fast recursive method, e.g., fast transversal filter (FTF) technique, for computing the Kalman gain is then directly used to compute Feed Forward Equalizer (FFE) coefficients gopt. The complexity of a conventional FTF algorithm is reduced to one third of its original complexity by choosing the length of a Feed Back Equalizer (FBE) coefficients bopt (of the DFE) to force the FTF algorithm to use a lower triangular matrix. The FBE coefficients bopt are then computed by convolving the FFE coefficients gopt with the channel impulse response h. In performing this operation, a convolution matrix that characterizes the channel impulse response h extended to a bigger circulant matrix.

Abstract: Determination of equalizer coefficients from a sparse channel estimate begins by determining location of significant taps based on the sparse channel estimate of a multiple path communication channel. The sparse channel estimate indicates the positioning of signals received via the various multiple paths of the channel. The method then continues by determining feed-forward equalization coefficients based on the location of the significant taps. The method then continues by determining feedback equalization coefficients based on the feed-forward equalization coefficients and the sparse channel estimate.

Abstract: Sparse channel equalization may be achieved by receiving a signal via a multi-path communication channel. The equalization then continues by extracting sparse information regarding the multiple path communication channel from the signal. Such sparse information generally indicates the position of the signals received via each of the multiple paths. The equalization then continues by estimating a channel response of the multiple path communication channel based on the sparse information. The equalization then continues by generating equalization taps (or coefficients) based on the channel response. The equalization then continues by equalizing the signal based on the equalization taps.

Abstract: A communication device processes a preamble in the presence of impulse noise. The communication device receives a preamble sequence that includes a plurality of preamble symbols and determines that at least one preamble symbol of the plurality of preamble symbols has been adversely affected by impulse noise. Based upon this determination, the communication device masks the at least one preamble symbol of the plurality of preamble symbols to produce a subgroup of preamble symbols. Then, based upon the subgroup of preamble symbols, the communication device determines at least one of a frequency estimate for the subgroup of preamble symbols, a phase estimate for the subgroup of preamble symbols, and a gain estimate for the subgroup of preamble symbols. Based upon these estimates, the communication receiver corrects subgroup of preamble symbols and uses the result to perform channel estimation, to correct subsequently received symbols carrying data, etc.

Abstract: A communication device constructed according to the present invention detects impulse noise in a preamble sequence. In detecting impulse noise in the preamble sequence the communication device first receive a preamble sequence that includes a plurality of preamble symbols. The communication device then divides the plurality of preamble symbols by at least one known preamble symbol to produce a plurality of preamble gains and/or a plurality of preamble phases corresponding to the plurality of preamble symbols. Finally, the communication device determines, based upon the plurality of preamble gains and/or the plurality of preamble phases, that at least one preamble symbol has been adversely affected by impulse noise. The communication device may discard at least one preamble symbol that has been adversely affected by impulse noise from the plurality of preamble symbols.

Abstract: Multi-user CFO Correction for CDMA Systems. Any communication receiver may be adapted to perform the multi-user CFO correction for CDMA. One embodiment assumes a diagonal CFO matrix to decouple the different codes' soft symbol decisions, and each soft symbol decision is independently corrected to obtain hard decisions. Another embodiment employs direct CFO matrix inversion and multiplies it by a despread soft symbol decision vector to obtain corrected soft symbol decisions. Another embodiment first performs a single-user correction on the despread soft symbol decisions; these soft symbol decisions are then sliced to obtain initial hard decisions. In the next step of this embodiment, the initial hard decisions are multiplied by the CFO coefficients to obtain an estimate for the undesired ICI, which is then subtracted from the despread soft symbol decisions to obtain cleaner soft symbol decisions. The cleaner soft symbol decisions are sliced to obtain higher-order hard decisions.

Abstract: Successive interference canceling for CMDA. ICI may result from a signal's multipath effects, or by filtering/suppression of some of the component energy of the signaling waveforms. Energy component attenuation destroys orthogonality of CDMA symbols thereby causing ICI. An ICF suppresses frequency domain portions (attenuates ingress), but also introduces ICI. Following the ICF, the signal is de-spread, sliced, re-spread and convolved with the ICF echoes (except first tap echoes). Convolving re-spread hard decisions with delayed ICF taps is equivalent to partially re-modulating the first-pass hard decisions to efficiently “add-back-in” the signal energy which was blanked/subtracted by the ICF. Alternatively, parameter estimation de-rotates and re-rotates soft symbols and hard decisions, respectively, compensating for undesirable symbol rotation. The convolved signal is subtracted from a delayed version of the ICF output signal.

Abstract: Carrier frequency offset (CFO) estimation from preamble symbols. Any communication receiver may be adapted to perform the CFO estimation. The CFO estimation is performed using a low complexity, high accuracy CFO estimation method. The operation may be described as follows: each element of a received sequence is divided by the corresponding preamble element, the resulting sequence is divided into N subgroups, and each subgroup is then averaged. The phase differential of the resulting sequence is computed, averaged, and used to compute an estimate of the carrier frequency offset. This approach to performing CFO estimation is of relatively high estimation accuracy and of relatively low computational complexity.

Abstract: Optimal Decision Feedback Equalizer (DFE) coefficients are determined from a channel estimate by casting the DFE coefficient problem as a standard recursive least squares (RLS) problem and solving the RLS problem. In one embodiment, a fast recursive method, e.g., fast transversal filter (FTF) technique, is used to compute the Kalman gain of the RLS problem, which is then directly used to compute MIMO Feed Forward Equalizer (FFE) coefficients. The FBE coefficients are computed by convolving the FFE coefficients with the channel impulse response. Complexity of a conventional FTF algorithm may be reduced to one third of its original complexity by selecting a DFE delay to force the FTF algorithm to use a lower triangular matrix. The length of the DFE may be selected to minimize the tap energy in the FBE coefficients or to ensure that the tap energy in the FBE coefficients meets a threshold.

Abstract: Iterative data-aided carrier CFO estimation for CDMA systems. Any communication receiver may be adapted to perform the iterative data-aided carrier CFO estimation. The iterative data-aided carrier CFO estimation is performed using a high accuracy method. The operation may be described as follows: a received signal is despread and buffered. Using the received preamble sequence, an initial estimate of the CFO is obtained. This estimate is used to correct the whole despread data. The corrected data using the initial CFO estimate is sliced. Each despread data symbol is divided by the corresponding sliced data decision. The obtained sequence is then averaged across different codes to obtain a less noisy sequence, which is then used to estimate the CFO again. The procedure can be repeated (iterated) to obtain a more accurate carrier frequency offset estimate; the number of times in which the procedure is repeated may be programmable or predetermined.