Abstract:
A method and arrangement for estimating a DC offset for a signal received in a radio receiver. The received signal includes a digitally modulated signal component, a DC offset component, and a noise component. When the signal is of a known type, such as a Gaussian Minimum Shift Keying (GMSK)-modulated signal with constant amplitude in a GSM/EDGE cellular radio system, the method exploits the known characteristics of the statistical distribution for the known type of signal to obtain a better estimate of the DC offset. The statistical distribution of the received digitally modulated signal component is first analyzed. That statistical distribution is then compared to the known statistical distribution for the known type of signal to identify differences. The differences are then used to estimate the DC offset. Additional iterations may be performed to further improve the DC estimate.
Abstract:
A device and method in a radio receiver for generating synchronization and channel estimation information based on three parameters consisting of a synchronization position, at least one whitening filter parameter, and a channel estimate. A spatially and temporally stacked signal model is generated by stacking successive samples of temporally adjacent received signal vectors and corresponding training vectors. Initial estimates of a first one or two of the three parameters are then generated based on the spatially and temporally stacked signal model. The rest of the three parameters are then computed based on the initial estimates of the first one or two parameters. If a stopping criterion is met, the method ends and the parameters are used to process the signal. If the stopping criterion is not met, additional iterations are performed to improve the synchronization and estimation information.
Abstract:
In a method of enabling model order selection for joint channel synchronization and noise covariance estimation of at least one received signal in a wireless communication network, generating S0 a spatially and temporally stacked signal model by stacking successive samples of temporally adjacent received signal vectors and corresponding training vectors, computing S1 a noise variance matrix for each hypothesized synchronization position, channel length and stacking order, based on the stacked training symbols: determining S2 a best synchronization position for the received signal, based on the stacked training vectors, by jointly determining the best synchronization position for the received signal and estimating a channel length and a stacking order for said signal model based on the stacked training vectors.
Abstract:
The present invention provides a method and apparatus for channel estimation when the amplitude of a received signal is hard-limited. A channel estimator computes amplitude estimates for the received signal based on the phase samples of the received signal and previous channel estimates. The amplitude estimates may comprise the expected values of the amplitude given the phase samples and the initial channel estimates. The channel estimator then computes revised channel estimates based on the amplitude estimates and the phase samples. The process may be performed iteratively to refine the channel estimates during each iteration.
Abstract:
Pre-coder techniques disclosed herein are based on long-term statistical channel information for reducing channel feedback overhead and transmitter complexity. In an embodiment, a receiver includes two or more receive antennas spaced approximately λ/2 apart and a baseband processor. The baseband processor computes channel correlations for different combinations of transmit antennas and each receive antenna and averages the channel correlations over the different receive antennas to form a frequency-independent channel correlation matrix. The baseband processor also computes a scalar representing noise variance at the receive antennas and feeds back the frequency-independent channel correlation matrix and the scalar for use in performing transmitter pre-coding computations.
Abstract:
Multi-antenna transmission control presented herein involves generating a set of virtual channel realizations at the transmitter that shares the same second-order statistics as the actual channel realizations observed for a targeted receiver. By making the control-related quantities of interest at the transmitter depend on the long-term statistics of the channel, the actual channel realizations are not needed for transmission control, e.g., for accurate Multiple-Input-Multiple-Output (MIMO) preceding. As such, the use of virtual channel realizations enables transmission control that approaches the “closed-loop” channel capacity that would be provided by full feedback of the (instantaneous) actual channel realizations, without requiring the overhead signaling burden that attends full feedback.
Abstract:
A method of computing an inversion (X) of a nearly Toeplitz n by n matrix (A). A perturbation matrix (E) is first determined such that the sum of the nearly Toeplitz matrix (A) and the perturbation matrix (E) is a Toeplitz matrix (T). The inversion is solved by solving the equation X=T−1(B+EX), where B is a vector or matrix of dimension n by m. An initial estimate X(0) is selected and estimates of the inversion X are iteratively computed through the recursion X(n−1)=T−1(B+EX(n)). The initial estimate X(0) may be equal to an inversion (T−1) of the Toeplitz matrix (T). The present invention may be utilized in a radio receiver to efficiently compute (1) a least-squares (LS) channel estimate, (2) minimum mean squared error (MMSE) prefilter coefficients for a decision feedback equalizer (DFE), or (3) an autoregressive (AR) noise-spectrum estimation from a finite number of observed noise samples.
Abstract:
Channel Quality Indicator (CQI) tables are tailored to one or more cells of interest. Tailoring CQI tables to individual cells permits devices such as radio base stations to more reliably and accurately allocate radio resources to those cells since channel conditions vary from cell to cell. According to one embodiment, a table of CQI values is composed by analyzing information indicating channel quality in a cell of interest and generating at least one table of CQI values tailored to the cell of interest based on the information analyzed. The tailored CQI table may be deployed to another device for use in reporting channel quality information. The device may report channel quality by accessing the tailored CQI and identifying the range of CQI values that includes a channel quality estimate derived by the device. The device generates a channel quality information message based on the identified range of CQI values.
Abstract:
A method and apparatus blindly detects a received signal's modulation type characterizing an impairment component of the received signal for each postulated modulation type by determining spatial correlations between In-phase and Quadrature components of the received signal. The blind detection circuit then detects the modulation type based on the characterized impairment component. A metric generator generates a postulation metric for each postulated modulation type based on the characterized impairment component. After evaluating the postulation metrics, an evaluation circuit identifies the postulated modulation type having the best postulation metric as the modulation type of the received signal. According to an exemplary embodiment, the blind detection circuit determines a whitened noise estimate for each postulated modulation type and generates the postulation metrics based on the whitened noise estimate to reduce interference effects in the postulation metrics.
Abstract:
A method and apparatus for offsetting the frequency of a local oscillator in a receiver are disclosed. The local oscillator frequency is offset with an offset frequency that depends on the training sequence used. Training symbols are inputted to the control unit. The control unit then provides an offset frequency depending on the training symbol received. A rotation of the baseband signal, proportional to the offset frequency, is introduced which later is digitally compensated for. Upon reception of the signal, a DC offset is introduced in the radio part. The digital compensation transforms this DC offset, in the baseband signal, to a rotating signal. The rotating DC offset signal is then subtracted in the baseband processing.