Abstract:
The invention relates to a Rake receiver of a CDMA system using IRC. The Rake receiver comprises at least two antenna branches (232A, 232B), at least one Rake finger (270A, 270B), and a delay estimator (290A). The delay estimator (290A) comprises a despreader (296A, 296B) and an allocator (264) for selecting at least one delay, by which delay a multipath propagated signal component is received, and allocating a Rake finger (270A, 270B) for processing the signal component found by informing the Rake finger (270A, 270B) of the delay found. The delay estimator (290A) further comprises: a channel estimator (292), an interference estimator (292) for generating an interference signal, a weighting coefficient part (292) for providing each antenna branch (232A, 232B) with weighting coefficients maximizing the Signal-to-Interference-and-Noise Ratio (SINR), a multiplier (294A, 294B) for multiplying the pilot part by a weighting coefficient, and an antenna branch summer (298A) for combining the despread pilot parts, received via the separate antenna branches (232A, 232B) and multiplied by the weighting coefficient, to one combined pilot signal, on which combined pilot signal the selection is based in the allocator (264).
Abstract:
An intermediate symbol buffer (ISB) configuration and method is provided such that the ISB memory comprises 15 portions, one for each HSDPA spreading code. Symbols associated with a spreading code are written to the memory portion associated with the same spreading code. When a covariance calculation is performed to obtain a more accurate channel estimate, only the symbols associated with spreading codes determined to be needed for the covariance calculation are written to the ISB by a buffer block and red from the ISB by a correlation core. The symbols associated with spreading codes that are not necessary for a covariance calculation may be masked from being written or read from the ISB. In some embodiments each memory portion is an individual memory block. In other embodiments a plurality of memory blocks may contain a plurality of memory portions, one memory partition designated, at least temporarily, or each spreading code.
Abstract:
A method for equalizing a received radio signal in a WCDMA system, comprises receiving (210), in a radio receiver, of a digital radio signal spread by scrambling codes. A channel estimation is performed (230) on the received digital radio signal for a plurality of channels. The received digital radio signal is in an equalizer equalized (240) into an equalized digital radio signal. This equalizing is performed by combining a plurality of part signals, deduced from the digital radio signal, with a respective delay and a respective combining weight. The equalizing (240) comprises provision of the combining weights based on a signal impairment matrix having elements compensated for systematic colouring caused by said scrambling codes.
Abstract:
A method for noise rise estimation in a wireless communication system comprises receiving (210) of radio signals. An interference whitening (212) is performed. A useful signal power for a first user after the interference whitening is determined (214) for a plurality of time instances. Furthermore, a first user noise floor compensation factor is derived (216) based on combining weights for the first user used in the interference whitening. A probability distribution for a compensated useful signal power for the first user is estimated (218). A conditional probability distribution of a noise floor measure is computed (220). A noise rise measure for the first user is then calculated (222) based at least on the compensated useful signal power for the first user and the conditional probability distribution of a noise floor measure.
Abstract:
A receiver and method for receiving and processing a sequence of transmitted symbols in a digital communication system utilizing soft pilot symbols. A set of soft pilot symbols are transmitted 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 16QAM or 64QAM. The receiver knows the modulation type and location (time/frequency/code) of the soft pilot symbols, and demodulates them first. The receiver uses the demodulated soft pilot symbols as known symbols to estimate parameters of the received radio signal. 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.
Abstract:
With a nonparametric G-Rake receiver, combining weights may be determined using a nonparametric mechanism in multiple-input, multiple-output (MIMO) scenarios. In an example embodiment, a method for a receiving device having a nonparametric G-Rake receiver entails calculating an impairment covariance matrix and determining combining weights. More specifically, the impairment covariance matrix is calculated based on a pilot channel using a nonparametric mechanism in a MIMO scenario in which a code-reuse interference term exists. The combining weights are determined for the nonparametric G-Rake receiver responsive to the impairment covariance matrix and by accounting for the code-reuse interference term.
Abstract:
According to the teachings presented herein, a method and apparatus for communication signal processing advantageously use a mix of parametric and non-parametric correlation estimation in communication signal processing. Non-parametric estimation generates an "overall" correlation estimate for a received communication signal, and parametric estimation generates a "component" correlation estimate. The component correlation estimate is removed from the overall correlation estimate to form a partial correlation estimate that is used to process the received communication signal at least initially, such as in a pre-equalization stage. The overall and component correlation estimates are generated as impairment and/or data correlation estimates.
Abstract:
A model-based technique for estimating impairment covariance associated with a MIMO signal is disclosed. In an exemplary method, an impairment model is constructed for a received composite information signal comprising at least a first data stream transmitted from first and second antennas according to a first antenna weighting vector. The impairment model includes first and second model terms corresponding to the first and second antennas, respectively, but does not include a cross-antenna interference term. In another embodiment, an impairment model for a received MIMO signal is constructed by computing an impairment model term for each antenna and an additional term to account for precoding interference in a single-stream MIMO transmission scenario. The impairment terms are grouped so that only two associated scaling terms are unknown; values for the scaling terms are estimated by fitting the model to measured impairment covariance values.
Abstract:
Teachings presented herein present a 'whitening' channel estimation method and apparatus that produce high-quality net channel estimates for processing a received signal, such as a received CDMA signal. Processing includes forming an initial least squares problem (for medium channel estimates) using known pilot values and corresponding pilot observations for the received signal, transforming the initial least squares problem using a whitening transformation term, and solving the transformed least squares problem to obtain whitened medium channel estimates. The whitening transformation term may be determined, for example, by carrying out a Cholesky factorization of a (traffic) data correlation matrix, which can be obtained from traffic data values for the received signal. Processing further includes converting the whitened medium channel estimates into whitened net channel estimates, which consider the effects of transmit/receive filtering.
Abstract:
A mobile receiver having a multi-mode interference suppression function and a way to estimate its speed utilizes a parametric approach to interference suppression at high speeds, and a nonparametric approach at low speeds. In particular, if the mobile receiver is currently operating in a nonparametric mode and its speed exceeds a first predetermined threshold, the mobile receiver switches to a parametric mode. Conversely, if the mobile receiver is currently in parametric mode and its speed is less than a second predetermined threshold, the mobile receiver switches to nonparametric mode. In one embodiment, the speed may be estimated by a Doppler frequency in the received signal, and the thresholds are Doppler frequencies. In one embodiment, the first and second thresholds are different, creating a hysteresis in the mode switching.