Embodiments of the present invention provide a signal receiving method and a receiver. The signal receiving method includes: sequentially preprocessing a received first signal to obtain to-be-processed second signals; generating filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and filtering the corresponding second signals according to the filtering coefficients. Filtering can be performed according to different channel conditions and transmission requirements, thereby improving system performance of the receiver.

Disclosed in an embodiment of the disclosure is an interference rejection combining (IRC) method supporting transmit diversity, in which an N*N interference and noise covariance matrix corresponding to one subcarrier is generated from signals, in a transmit diversity mode, received at cell reference signal (CRS) resource positions via N receiving antennas, where N is greater than or equal to 3; Cholescy decomposition and upper triangular matrix inversion is performed on the N*N interference and noise covariance matrix to obtain an N*N block matrix; the N*N block matrix is expanded to a 2N*2N noise whitening matrix; and the received signals and channel estimation values are whitened according to the noise whitening matrix, and the whitened received signals and channel estimation values used to obtain a minimum mean square error-IRC (MMSE-IRC) processing result. Also disclosed are an IRC device supporting the transmit diversity, and a computer storage medium.

Embodiments of the present disclosure provide methods and apparatus for detection of radio signal. A method performed by a reception apparatus may comprise: obtaining (S101) time domain samples of a radio signal; processing (S102) the time domain samples by a plurality of match filters respectively, to generate a plurality of filtered results of the time domain samples; classifying (S103) a filtered result of the plurality of filtered results by a classifier; discarding (S104) a filtered result classified as being not associated to the code sequence; and determining (S105) whether the code sequence is used in the radio signal, when a filtered result of the radio signal is classified as being associated to the code sequence. Some processing procedures may be avoided based on the classification result of the detected radio signal, and computational complexity may be reduced.

Embodiments of the present disclosure provide a method and apparatus for determining a nonlinear characteristic and a system. The method for determining a nonlinear characteristic includes: determining a correction factor of a nonlinear item of a nonlinear model of a system to be measured according to an input and/or a parameter of the system to be measured; correcting the nonlinear item of a nonlinear model of the system to be measured by using the correction factor; and obtaining a nonlinear characteristic of the system to be measured according to the corrected nonlinear model. The nonlinear characteristic allows the input and/or the parameter of the system to be corrected to produce a corrected output. With the embodiments of the present disclosure, the nonlinear characteristic of the system to be measured under different inputs and/or parameters may be estimated, and accuracy of the estimation and applicability are improved.

To provide a phase noise optimization device and a phase noise optimization method which are capable of automatically measuring optimum phase noise according to an offset frequency. There is included a phase noise data generation unit 28 that generates at least two types of phase noise data corresponding to at least two low-pass filters (LPFs) 15a and 15b selected by a filter selection unit 16 in at least one measurement frequency range, set in advance, out of a plurality of measurement frequency ranges, a comparison unit 29 that compares at least two types of phase noise data, and a phase noise optimization unit 30 that generates optimized phase noise data based on a comparison result of the comparison unit 29.

A femtocell telecommunication system equipment comprising: a base apparatus structured to provide a first information signal and control signals; an electrical conductor based transmission line connected to said base apparatus; a bidirectional conversion apparatus adapted to receive/transmit from/on the transmission line the first signal and the control signals; the bidirectional apparatus comprising: a processing module structured to process the first signal to generate a second information signal and vice-versa; the second signal being adapted to be transmitted/received by an antenna device connectable to the bidirectional apparatus.

A method is for processing an analog signal coming from a transmission channel. The analog signal may include a useful signal modulated on a sub-set of carriers. The method may include analog-to-digital converting of the analog signal into a digital signal, and synchronization processing the digital signal. The synchronizing may include determining, in a time domain, a limited number of coefficients of a predictive filter from an autoregressive model of the digital signal, and filtering the digital signal in the time domain by a digital finite impulse response filter with coefficients based upon the limited number of coefficients to provide a filtered digital signal. The method may include detecting of an indication allowing a location in the frame structure to be identified, using the filtered digital signal and a reference signal.

Interference may affect numerous communication systems. Thus, certain wireless communication systems that rely on combining transmitted repetitions of information may benefit from interference removal techniques, such as those that provide pre-combiner interference removal. A method can include receiving, from a transmitter, multiple repetitions of a same information sent from the transmitter over a channel. The method can also include removing interference from the respective repetitions. The method can further include combining the interference-removed repetitions. The method can additionally include performing channel estimation based on the combined interference-removed repetitions. The method can also include retrieving information corresponding to the same information sent in the multiple repetitions based on the channel estimation and combined interference-removed repetitions.

Methods, systems, and devices for wireless communications are described. The described techniques provide for a user equipment (UE) to perform receiver-side noise statistics (Rnn) estimation and for an extended reality (XR) device to perform log likelihood ratio (LLR) scaling estimation. For example, the UE may transmit a first set of reference signals to the XR device. The XR device may sample the reference signals and transmit an indication of quantized samples such that the UE may perform Rnn estimations and generate a pre-equalization matrix. The UE may transmit a set of pre-equalized reference signals to the XR device such that the XR device may estimate LLR scaling coefficients. In some examples, the UE may determine the pre-equalization matrix by performing a filtering of reference signal measurements. The UE may apply whitening to account for momentary interference, and may indicate a whitening matrix to the XR device.

Methods, systems, and devices for wireless communications are described. The described techniques provide for a user equipment (UE) to perform receiver-side noise statistics (Rnn) estimation and for an extended reality (XR) device to perform log likelihood ratio (LLR) scaling estimation. For example, the UE may transmit a first set of reference signals to the XR device. The XR device may sample the reference signals and transmit an indication of quantized samples such that the UE may perform Rnn estimations and generate a pre-equalization matrix. The UE may transmit a set of pre-equalized reference signals to the XR device such that the XR device may estimate LLR scaling coefficients. In some examples, the UE may determine the pre-equalization matrix by performing a filtering of reference signal measurements. The UE may apply whitening to account for momentary interference, and may indicate a whitening matrix to the XR device.