Abstract:
A communication device is provided that includes a receiver configured to receive a signal. The communication device further includes a circuit configured to determine an interference reference signal based on an interference signal, to multiply the received signal with the interference reference signal in the time domain to form a multiplication signal and to filter the multiplication signal to form a filtered signal.
Abstract:
A method for estimating noise and interferer parameters includes receiving a signal comprising a noise and interference signal contribution. Noise and interference power samples are generated based on the signal. The noise and interference power samples are quantized into quantization levels. The occurrences of noise and interference power samples are accumulated for each quantization level during an observation period. Noise and interferer parameters are estimated based on the number of occurrences of noise and interference power samples per quantization level during the observation period.
Abstract:
The disclosure relates to a cluster detection device for detecting clusters in a beam-formed transmission, the cluster detection device comprising: a receiver, configured to receive a radio signal comprising time-frequency resources, wherein the time-frequency resources comprise a plurality of reference signals; a delay profile detector, configured to detect a set of delay profiles based on frequency-direction filtering of the plurality of reference signals; a Doppler profile detector, configured to detect a set of delay-Doppler profiles based on time-direction filtering of the set of delay profiles; and a cluster detection postprocessor, configured to derive a set of cluster parameters from the set of delay-Doppler profiles.
Abstract:
A method for estimating noise and interferer parameters includes receiving a signal comprising a noise and interference signal contribution. Noise and interference power samples are generated based on the signal. The noise and interference power samples are quantized into quantization levels. The occurrences of noise and interference power samples are accumulated for each quantization level during an observation period. Noise and interferer parameters are estimated based on the number of occurrences of noise and interference power samples per quantization level during the observation period.
Abstract:
A method (700) for processing resource blocks in a receiver may include receiving (701) a signal comprising transmissions from a plurality of radio cells, wherein received samples of the signal are arranged in a plurality of resource blocks (300); forming (702) a plurality of clusters ({xi,jN}) based on a similarity criterion with respect to the plurality of resource blocks (300); and assigning (703) each resource block of the plurality of resource blocks (300) to one cluster of the plurality of clusters ({xi,jN}).
Abstract:
Embodiments provide improved interference classification and parameter estimation at a User Equipment (UE) that uses received scheduling information associated with interfering cells from a network node together with parameters associated with interfering cells generated locally to the UE to generate an interference mapping data set that may be used to adjust subsequent interference classification and parameter estimation processing in the UE.
Abstract:
A method of generating channel estimates of a communication channel in an OFDM system includes receiving references symbols from at least one time frequency observation block of a predetermined block size in frequency and time; generating subspace-transformed reference symbols from the received reference symbols; and subspace filtering the subspace-transformed reference symbols to generate a channel estimate for a communication channel target time; wherein a latency between a communication channel time instant of a currently received reference symbol and the communication channel target time is smaller than the observation block size in time.
Abstract:
A channel estimation coefficients generator (200) for generating channel estimation coefficients for channel estimation filtering includes: a parameter acquisition unit (205) configured to acquire a first set of input parameters (208) and to acquire a second set of input parameters (209), wherein a time variability of the first set of input parameters (208) is smaller than a time variability of the second set of input parameters (209); a first channel estimation coefficients generator (201) configured to generate a prototype set of channel estimation coefficients (202) based on the first set of input parameters (208); and a second channel estimation coefficients generator (203) configured to generate a refined set of channel estimation coefficients (204) based on the prototype set of channel estimation coefficients (202) and based on the second set of input parameters (209).
Abstract:
A communication device is provided that includes a receiver configured to receive a signal. The communication device further includes a circuit configured to determine an interference reference signal based on an interference signal, to multiply the received signal with the interference reference signal in the time domain to form a multiplication signal and to filter the multiplication signal to form a filtered signal.
Abstract:
A communication terminal is described comprising a receiver configured to receive pilot signal samples via a plurality of communication channels and to determine an interference matrix which includes, for each pilot signal sample, interference information representing an amount of interference included in the pilot signal sample and a channel estimator configured to determine a channel autocorrelation matrix for the plurality of communication channels and to determine a linear transformation which diagonalizes or triagonalizes the autocorrelation matrix, to transform the interference matrix by the transformation and to reduce the transformed interference matrix by discarding components corresponding to predetermined eigenvectors of the autocorrelation matrix, to determine filter weights for the signal samples based on the reduced interference matrix and to determine channel estimates by filtering the pilot signal samples using the determined filter weights.