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.

A multiple-input multiple-output (MIMO) receiver comprises a MIMO frequency-domain equalizer, which comprises a MMSE filter for mitigating inter-symbol interference and an adder for mitigating inter-antenna interference, a MIMO detector and a MIMO decoder for processing a received MIMO signal and for estimating transmit bits. The receiver comprises a feedback path from the decoder to the detector for providing soft-information on the transmit bits to the detector and an additional feedback path from the decoder to the MIMO frequency-domain equalizer for providing soft-information to the MMSE filter and to the adder of the equalizer.

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 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 filtering device includes a low-pass filter (LPF), a noise estimation circuit and a first combining circuit. The LPF receives and filters a pre-filtering signal to generate an output signal of the filtering device. The noise estimation circuit estimates an estimated noise signal according to the output signal and the pre-filtering signal. The first combining circuit subtracts the estimated noise signal from an input signal of the filtering device to generate the pre-filtering signal.

A method and system for performing quadrature amplitude modulation (QAM) decoding of a received signal includes finding for each layer a region in a first constellation diagram of the received signal, the region including a portion of the first constellation diagram, the portion having the same size of a second constellation diagram, and a first constellation order of the received signal is higher than a second constellation order of the second constellation diagram; and, for each layer: finding a first portion of bits based on bits that are constant among constellation points located in the region of the layer; decoding the received signal using a QAM decoder having the second constellation order to obtain a second portion of bits; adjusting the second portion of bits based on the region of the layer; and merging the first portion of bits with the second portion of bits to obtain a decoded symbol.

What is disclosed is a method for wireless communication comprising receiving a wireless communication via a receiver of the mobile communication device, deriving a demodulation reference signal from a first plurality of symbols of the wireless communication; creating a channel estimation matrix using the demodulation reference signal; inverting the channel estimation matrix to obtain a channel pseudo-inverse matrix; deriving a tracking reference signal from a second plurality of symbols of the wireless communication; calculating a phase shift for one or more additional symbols based on the tracking reference signal; determining a corrected channel pseudo-inverse matrix for the one or more additional symbols by adjusting the channel pseudo-inverse matrix according to the calculated phase shift; and controlling the receiver to accomplish data detection using the corrected channel pseudo-inverse matrix on one or more orthogonal frequency division multiplexing subcarriers.

A method and system for providing sub-band whitening are herein provided. According to one embodiment, a method estimating an interference whitening (IW) factor based on a legacy-long training field (LLTF) signal, updating the estimated IW factor during transmission of a data symbol, and scaling the data symbol based on the updated IW factor and the estimated IW factor.

A method to control an output component of an electronic system comprises (a) receiving a transmission from an input component of the electronic system, the transmission including a time stamp and at least one input signal; (b) storing content of the transmission including the time stamp and the at least one input signal; (c) selecting one of a plurality of noise-filtered signals based on the time stamp and on a reference time index, the selected one of the plurality of noise-filtered signals having a greatest signal-to-noise ratio among the noise-filtered signals defined at the reference time index; and (d) controlling an output component of the electronic system based in part on the selected noise-filtered signal.

A method and system for performing Maximum Likelihood Detector (MLD) preprocessing in a Multiple-Input Multiple-Output (MIMO) communication system, the method including, obtaining a received signal Y a corresponding channel matrix H and a vector of noise samples n; calculating a whitening filter L.sup.−H; whitening a channel matrix H; selecting one of a first calculation or a second calculation, based on estimated complexity of the calculations; and performing preprocessing of the received signal using the selected calculation. The first calculation includes: whitening the received signal and performing a Cordic based QR decomposition to the whitened channel matrix {tilde over (H)} and the whitened received signal {tilde over (Y)} to obtain triangular matrix R and Y=Q.sup.HL.sup.−HY. The second calculation includes: performing a Cordic based QR decomposition to the whitened channel matrix {tilde over (H)} and the whitening filter L.sup.−H to obtain triangular matrix R and Q.sup.HL.sup.−H, and multiplying the received signal Y by Q.sup.HL.sup.−H to obtain Y=Q.sup.HL.sup.−HY.

A method and apparatus for processing a signal to generate equalizer codes, which are used to control equalization of the signal, that comprises processing the signal to identify the eyes of the signal, and for each eye, calculating an eye height and calculating a noise value. For each eye, squaring the eye height to generate an eye height product and dividing the eye height product by the noise value to generate a Q.sup.2 value. Using the calculated Q.sup.2 values optimizing, through adaptation, the equalizer codes. Calculating the noise values may include calculating an ISI value for each band of the signal and then calculating the eye height for each eye as the difference between the adjacent upper average value and the adjacent lower average value. Then, for each eye, calculating a noise value by summing the ISI value for the band above the eye and the band below the eye.