Abstract:
A RAKE receiver is adapted to receive input from at least a first and a second antenna (104a, 104b). The RAKE receiver comprises a despreading unit (303) adapted to allocate a number (Nf) of despreading fingers to a number of delay positions of a signal which is transmitted over a channel. The RAKE receiver further comprises a delay position selection unit (305) which estimates an antenna correlation (formula 1) between the at least first and second antenna (104a, 104b) and controls the despreading unit (303) according to a first strategy for allocating the number (Nf) of fingers if the antenna correlation (formula 1) is below a predetermined threshold, and according to a second strategy otherwise. The threshold (formula 2) is selected based on at least one of the following: number of available finger in the RAKE receiver (Nf), dispersion of the channel, range of direction of arrivals (Δφ).
Abstract:
Methods and apparatus for adaptively transmitting data in a wireless communication network are disclosed, in which channel conditions between a mobile terminal and two or more base stations in an active set are evaluated and used to select a transmission mode from a set of available downlink transmission modes including a non-interference-coordinated point-to-point transmission mode as well as at least one of a multi-cell single-frequency-network transmission mode and an interference-coordinated point-to-point transmission mode. Using the dynamic transmission mode selection described herein, a higher cell-edge throughput in HSDPA systems may be achieved.
Abstract:
The teachings herein disclose interference cancellation processing that uses hard decision logic for simplified estimation of interfering signals, in combination with soft scaling of the hard decisions for better interference cancellation performance, particularly in low signal quality conditions. In one aspect, the soft scaling may be understood as attenuating the amount of interference cancellation applied by a receiver, in dependence on the dynamically changing received signal quality at the receiver. More attenuation is applied at lower signal quality because the hard decisions are less reliable at lower signal qualities, while less (or no) attenuation is applied at higher signal qualities, reflecting the higher reliability of the hard decisions at higher signal qualities. Signal quality may be quantized into ranges, with a different value of soft scaling factor used for each range, or a soft scaling factor may be calculated for the continuum of measured signal quality.
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 wireless communication apparatus compensates for timing misalignment in its received signal processing. In at least one embodiment, the apparatus estimates a set of path delays for a received signal and sets processing delays on the estimated path delays. The apparatus jointly hypothesizes combinations of fractional timing offsets for two or more paths, and computes a decision metric for each joint hypothesis that indicates the accuracy of the joint hypothesis. As non-limiting examples, the decision metric may be a signal quality metric, or a distance metric (such as between a measured net channel response and an effective net channel response reconstructed as a function of the combination of fractional timing offsets included in the joint hypothesis). The apparatus evaluates the decision metrics to identify a best estimate of timing misalignment, and correspondingly compensates coherent processing of the received signal.
Abstract:
The teachings herein disclose methods and apparatus that simplify impairment correlation estimation for received signal processing, based on determining, for any given processing interval, which impairment contributors should be considered in the estimation of overall received signal impairment correlations. These simplifications reduce computational processing requirements, allowing reduced circuit complexity and/or reduced operating power, and improve receiver performance. A corresponding transmitter and transmission method include transmitting multiple information streams to targeted receivers according to ongoing scheduling, and controlling the ongoing scheduling to reduce the number of impairment contributors considered in impairment correlation estimation at the targeted receivers. In one embodiment, a receiver identifies which impairment contributors to consider based on receiving control information. In another embodiment, the receiver identifies the impairment contributors to consider based on background processing, e.g., background determination of parametric model fitting parameters for a plurality of impairment contributors, and observing those model fitting parameters over time.
Abstract:
In one or more embodiments, an over-sampling method and corresponding over-sampling circuit efficiently generate an over-sampled signal by determining sampling phases in the over-sampled signal that are unused by downstream processing of the over-sampled signal, and skipping the generation of output values for the over-sampled signal that correspond to the unused sampling phases. In a communication receiver embodiment, determining the unused sampling phases comprises, with respect to currently estimated multipath delays of a received communication signal from which the over-sampled signal is derived, determining which sampling phases in the over-sampled signal will not be used by a downstream processing circuit having known processing delay assignment constraints. The known delay assignment constraints comprise Rake finger placement constraints or channel equalizer tap placement constraints, for example.
Abstract:
In one or more embodiments, an over-sampling method and corresponding over-sampling circuit efficiently generate an over-sampled signal by determining sampling phases in the over-sampled signal that are unused by downstream processing of the over-sampled signal, and skipping the generation of output values for the over-sampled signal that correspond to the unused sampling phases. In a communication receiver embodiment, determining the unused sampling phases comprises, with respect to currently estimated multipath delays of a received communication signal from which the over-sampled signal is derived, determining which sampling phases in the over-sampled signal will not be used by a downstream processing circuit having known processing delay assignment constraints. The known delay assignment constraints comprise Rake finger placement constraints or channel equalizer tap placement constraints, for example.
Abstract:
A subset of modeled impairment correlation terms are selected for use in received signal processing. According to one embodiment, a subset of modeled impairment correlation terms is selected and a composite impairment correlation term is determined based on the subset of modeled impairment correlation terms. The composite impairment correlation term may be determined by scaling the modeled impairment correlation terms included in the subset by respective model fitting parameters. The scaled modeled impairment correlation terms are then combined to form the composite impairment correlation term. The subset of modeled impairment correlation terms may be selected based on their respective model fitting parameters. In one embodiment, the modeled impairment terms having a model fitting parameter that satisfy a threshold are included in the subset while those that do not are excluded. The composite impairment correlation term may be used for received signal processing, e.g., demodulation or signal-to-interference estimation.
Abstract:
A method of determining a noise-corrected power delay profile includes determining a power delay profile and calculating a noise-corrected power delay profile. The step of calculating the noise-corrected power delay profile includes using a biased noise-floor power estimate, the power delay profile, and a noise-scaling factor.