Telefonaktiebolaget Lm Ericsson (publ)

Ericsson Gmbh

Tracy Lawrence Fulghum

Ali S Khayrallah

Gregory Edward Bottomley

Yi-Pin Eric Wang

Douglas Allan Cairns

Rajaram Ramesh

Carmela Cozzo

Elias Jonsson

R David Koilpillai

Jung-Fu Cheng

Stephen J Grant

William O Camp, Jr

Sandeep Chennakeshu

Nikolaus Klemmer

Nils Rutger Rydbeck

Andreas Cedergren

Gregory D Bottomley

Yi-Ping Eric Wang

A transmitter, channel coder, and method for coding and transmitting a sequence of symbols in a digital communication system utilizing soft pilot symbols. In one embodiment, the transmitter transmits a set of soft pilot symbols with higher reliability than the remaining symbols in the sequence by modulating the soft pilot symbols with a lower order modulation such as BPSK or QPSK while modulating the remaining symbols with a higher order modulation such as 16 QAM or 64 QAM. The transmitter shares the modulation type and location (time/frequency/code) of the soft pilot symbols with a receiver. Unlike traditional fixed pilots, the soft pilots still carry some data. Additionally, the soft pilots are particularly helpful in establishing the amplitude reference essential in demodulating the higher order modulation symbols. In another embodiment, soft pilot symbols are inserted by low-level puncturing of channel encoded bits and replacing the punctured bits with known bit patterns.

Transmitter and method for transmitting soft pilot symbols in a digital communication system

Interference, such as inter-symbol interference, from a symbol of interest in a RAKE receiver is reduced. The RAKE receiver comprises a plurality of RAKE fingers, a processor, and a combiner. The plurality of RAKE fingers despread symbols received over multiple paths of a multi-path channel. The processor determines cross-correlations between symbol waveforms from different symbols and multiple paths. The combiner combines the despread symbols using the cross-correlations to reduce interference from the symbol of interest.

Method and apparatus for DS-CDMA interference suppression using code-specific combining

Methods and apparatus for determining an impairment covariance matrix for use in an interference-suppressing CDMA receiver are disclosed. In several of the disclosed embodiments, precise information regarding signal propagation delays is not needed. An exemplary method includes the selection of a plurality of processing delays for processing a received CDMA signal. Net channel coefficients for the processing delays are estimated and used to calculate an impairment covariance matrix. The impairment covariance matrix is calculated as a function of the estimated net channel coefficients and the processing delays, without estimating a propagation medium channel response for the received signal.

Method and apparatus for efficient estimation of interference in a wireless receiver

A parallel interference cancellation (PIC) receiver incrementally removes interference from signals in parallel modules in successive stages. For each desired signal, as interfering signals are removed, corresponding updates to a data covariance matrix are modeled as computationally tractable rank-one updates to a root matrix of the covariance matrix. Processing of signals and/or covariance information may be initiated, continued, and/or halted at various stages, e.g., in response to signal or data quality. The PIC receiver using root matrix updates is applicable to a variety of demodulation techniques.

System and method for parallel interference cancellation with covariance root processing

A receive station of the present invention despreads a received signal over both long and short despreading periods to determine individual channel estimates over each symbol period of an extended period for multiple pilot signals. As a result, the present invention provides channel estimates sufficient for both slow and fast fading conditions. The receive station determines an average channel estimate for each of the pilot signals over the extended period by despreading the received signal over the extended period using mutually orthogonal extended spreading sequences. The receive station further determines a combined channel estimate for the pilot signals over each symbol period of the extended period by despreading the received signal over each symbol period using a common spreading sequence. Based on the average and combined channel estimates, the receive station determines individual channel estimates for each pilot signal over each symbol period of the extended period.

MIMO/transmit diversity channel estimation

In one of its aspects, the technology concerns a method of processing a signal which includes physical data channels which have been channelized using spreading codes. The method comprises (1) despreading unoccupied spreading codes (e.g., codes which are essentially unobscured by traffic data) included in the signal to obtain unoccupied code despread values, (2) using the unoccupied code despread values to form an impairment covariance matrix; and (3) using the impairment covariance matrix along with a channel estimate to form a processing parameter. The processing parameter can be one of combining sets and a signal quality estimate. In another of its aspects, the technology concerns a coherent, linear equalizer apparatus configured to process a signal which includes physical data channels which have been channelized using spreading codes. The equalizer apparatus comprises plural delay fingers () configured to despread unoccupied spreading codes included in the signal to obtain unoccupied code despread values, and a generator () configured to use the unoccupied code despread values to form an impairment covariance matrix.

Method and apparatus for estimating impairment covariance matrices using unoccupied spreading codes

In a parametric G-Rake receiver, a method an apparatus computes initial estimates of one or more scaling parameters and initial combining weights for the parametric G-Rake receiver; estimates the SINR of a received signal based on a mean pilot symbol estimate and the initial combining weights; computes revised estimates for one or more scaling parameters based on the estimated SINR and the initial combining weights; and computes revised combining weights based on one or more revised scaling parameter estimates.

Multi-pass parameter estimation for G-Rake receiver

A receive station of the present invention despreads a received signal over multiple successive symbol periods of an extended measurement period to determine individual channel estimates over each symbol period of an extended period for multiple pilot signals. In one example, the extended measurement period comprises two extended periods, each of which comprise two symbol periods. As a result, the present invention provides channel estimates sufficient for both slow and fast fading conditions. The receive station determines a combined channel estimate for the pilot signals over each symbol period of an extended period by despreading the received signal over each symbol period of an extended measurement period using a common spreading sequence. Based on the combined channel estimates, the receive station determines individual channel estimates for each pilot signal over each symbol period of the extended period.

According to a method and apparatus taught herein, the computation of intermediate combining weights considers impairment correlations common to two received signal streams, but does not account for cross-stream interference attributable to channel reuse between the two streams. Excluding consideration of channel reuse cross-stream interference from the computation of intermediate combining weights simplifies intermediate combining weight computation and increases computational robustness. Further, final combining weights, such as for Generalized Rake combining or equalization combining, may be obtained efficiently from the intermediate combining weights through the use of weight scaling factors, which do account for channel reuse cross-stream interference. Moreover, in at least some instances, the intermediate combining weights are of interest. For example, signal quality estimates for one or both streams may be computed from the corresponding intermediate combining weights.

Method and apparatus for determining combining weights for MIMO receivers

Methods and apparatus for processing a composite communication signal comprising two or more received signals of interest are disclosed. An interference-suppressing receiver, which may comprise a G-Rake receiver or a linear chip equalizer, utilizes a square-root covariance matrix in processing received signals, where the square-root covariance matrix represents impairment covariance or data covariance for the composite communication signal. In an exemplary method, a receiver detects symbols, corresponding to a signal of interest, from the composite communication signal, using processing weights calculated from a square-root covariance matrix and a net channel response for the signal of interest. The method further comprises calculating a reconstructed version of the signal of interest from the detected first symbols, generating an updated communication signal by subtracting the reconstructed version of the first signal of interest from the composite communication signal, and updating the square-root covariance matrix to obtain an updated square-root covariance matrix.

Method and apparatus for successive interference subtraction with covariance root processing

A wireless communication device includes at least two antennas with at least two corresponding receive chains. Selectively activating and deactivating the receivers as needed for a desired quality of reception controls the performance and power consumption of the wireless communication device. The wireless communication device may operate in a single receiver mode or a dual receiver diversity mode. In the dual receiver diversity mode, the wireless communication device may selectively control the gain of one or more antennas and/or reconfigure one or more receive chains to minimize power consumption while maintaining a desired performance.

Multiple antenna receiver

A method and apparatus for a multi-branch wireless receiver for periodically sampling first and second received signals corresponding to first and second receiver branches at first and second sample times to generate offset sample streams. The offset sample streams are then combined in a combining circuit to reduce interference present in the received signals. In an exemplary embodiment, a multi-branch wireless receiver includes an offset circuit to generate first and second offset sample times. A first sampler periodically samples the first received signal at the first sample time to generate a first sample stream and a second sampler periodically samples the second received signal at the second sample time to generate a second sample stream offset from the first sample stream. The combining circuit comprises a RAKE receiver that reduces the interference by scaling and combining despread values generated from the offset sample streams.

Method and apparatus for interference cancellation in wireless receivers

A method of processing a received communication signal comprises calculating a traffic-to-pilot scaling factor by relating data correlations determined from despread traffic values obtained from the received communication signal-to-noise correlations determined from despread pilot values obtained from the received communication signal, and generating traffic symbol estimates by combining corresponding ones of the despread traffic values using combining weights calculated from the data correlations. Generating combining weights in this manner provides, among other things, Minimum Mean Square Error (MMSE) estimations for the received traffic symbols that inherently are properly scaled in amplitude relative to symbol values in a reference modulation constellation. By obtaining proper scaling as part of combining weight generation, the receiver need not make an explicit estimate of symbol power to obtain proper soft value information, and the estimated traffic symbols may be compared directly with the reference constellation.

Method and apparatus for received communication signal processing

A wireless communication device includes a Generalized RAKE (G-RAKE) receiver circuit that is configured to determine a traffic-to-pilot gain scaling parameter as part of the impairment correlation determination process that underlies (G-RAKE) combining weight generation. In this manner, the receiver circuit conveniently and accurately accounts for gain differences between the pilot channel of a received CDMA signal, as used for channel estimation, and the traffic channel(s) of the CDMA signal, which carry received data to be recovered. The gain difference accounting enables proper demodulation of amplitude-modulated traffic signals. By way of non-limiting example, such gain scaling may be used for demodulating/decoding High Speed Downlink Packet Access (HSDPA) signals used in Wideband Code Division Multiple Access (W-CDMA) systems.

Method and apparatus for QAM demodulation in a generalized rake receiver

Exemplary received signal processing may be based on maintaining a model of received signal impairment correlations, wherein each term of the model is updated periodically or as needed based on measuring impairments for a received signal of interest. An exemplary model comprises an interference impairment term scaled by a first model fitting parameter, and a noise impairment term scaled by a second model fitting parameters. The model terms may be maintained based on current channel estimates and delay information and may be fitted to measured impairment by adapting the model fitting parameters based on the measured impairment. The modeled received signal impairment correlations may be used to compute RAKE combining weights for received signal processing, or to compute Signal-to-Interference (SIR) estimates. Combined or separate models may be used for multiple received signals. As such, the exemplary modeling is extended to soft handoff, multiple antennas, and other diversity situations.

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Durham, NC, United States of America

Tracy Lawrence Fulghum