King Fahd University of Petroleum and Minerals

King Abdulaziz City for Science and Technology

Tareq Yousuf Al-Naffouri

Ahmed Abdul Quadeer

Naofal Al-Dhahir

Muhammad Saqib Sohail

Giuseppe Caire

Syed Faraz Ahmed

Eprahim B Al-Safadi

Samir Al-Ghadhban

Mohammed E Eltayeb

Zahid Saleem

A Low-Complexity Minimum Mean Square Error (MMSE) method for estimation of impulse response or channel response of Impulse-Radio Ultra-Wideband (IR-UWB) wireless channels which exploits the sparsity of the received signal profile and the structure of the sensing matrix. The method comprises of first sub-sampling a received signal profile; second finding a minimum mean square error estimate of the impulse-radio ultra-wideband communication channel by Bayesian estimation according to priori channel statistics; and third identifying one or more substantially orthogonal clusters in the received signal profile. Impulse response of the impulse-radio ultra-wideband communication channel is the sum of the total number of resolvable multipath components, each with a real valued fading gain, and delay, relative to the arrival of the first path and impulse is the Dirac delta function.

Low-complexity method for estimating impulse-radio UWB wireless channels

The peak detection method using blind source separation extracts true peaks from noisy peaks in a more robust way that does not require any a priori information. Information regarding true peak location is obtained by thresholding the output of a wavelet transform. The value of the threshold is dependent on noise variance. While noise variance is normally unknown, the present method implements a blind source separation technique to calculate the noise variance. The blind source separation technique does not require information of the incoming signal or the channel noise, and hence is suitable for CR (cognitive radio) peak detection.

Peak detection method using blind source separation

The method of performing structure-based Bayesian sparse signal reconstruction is a Bayesian approach to sparse signal recovery that has relatively low complexity and makes a collective use of: a priori statistical properties of the signal and noise; sparsity information; and the rich structure of the sensing matrix &#x3a8;. The method is used with both Gaussian and non-Gaussian (or unknown) priors, and performance measures of the ultimate estimate outputs are easily calculated.

Method of performing structure-based bayesian sparse signal reconstruction

The method for mitigating interference in Orthogonal Frequency Division Multiplexing (OFDM) communications systems uses comb-type pilot signals in a doubly selective channel where the pilot signals are calculated to have zero correlation sequences in order to maintain orthogonality where there is a high Doppler effect to mitigate intercarrier interference. The pilot signals may be precomputed, stored in a look-up table, and selected based upon total power constraints of the pilot signals. The steps of the method may be performed by a Finite Impulse Response (FIR) equalizer.

Method for mitigating interference in OFDM communications systems

The OFDM peak-to-average power ratio reduction apparatus and method provides a compressive sensing algorithm that estimates the sparsity pattern of a sparse vector by a limited number of measurements. When the positions of the clipped peaks are known beforehand by, e.g., a genie-augmented receiver, then the algorithm optimally performs amplitude estimation utilizing a least squares estimation technique. When the cardinality of the peak-reducing signal is known at the receiver at initialization, the receiver optimizes the estimated peak-reducing signal by using least squares.

OFDM peak-to-average power ratio reduction method

The OFDM channel estimation and Inter-Carrier Interference (ICI) cancellation method uses a few pilots within Orthogonal Frequency Division Multiplexing (OFDM) systems in general, and mobile OFDM systems in particular. The frequency domain channel is estimated using an eigenvalue based model reduction technique with high accuracy. A Minimum Mean Square Error (MMSE) based Finite Impulse Response (FIR) equalizer is then used to obtain an ICI free estimate of the transmitted signal.

OFDM inter-carrier interference cancellation method

The present invention relates to impulse noise estimation and removal in orthogonal frequency division multiplexing (OFDM) transmissions, and particularly to transmissions in power line communications and digital subscriber line (DSL) transmissions. The method includes the steps of: modulating data to be transmitted; performing an inverse fast Fourier transform; inserting a cyclic prefix into the data; transmitting the data as a set of OFDM symbols via a channel; receiving the set of OFDM symbols; removing the cyclic prefix; performing a fast Fourier transform; estimating impulse noise; canceling the impulse noise based upon the estimated impulse noise to produce a set of impulse noise-free data; estimating the channel; and demodulating and detecting the data transmitted based upon the estimated channel and the set of impulse noise-free data.

Method of estimating and removing noise in OFDM systems

The cyclic prefix-based enhanced data recovery method retains the cyclic prefix (CP) upon reception and routes the CP to a data detection module to enhance the operation of the orthogonal frequency division multiplexed (OFDM) receiver whether operating in the blind, semi-blind, training, or perfectly known channel modes. Processing of the OFDM symbol and the CP is performed in the data detector and obtains data recovery by computing a maximum likelihood estimation based on the CP and the OFDM symbols.

Growing community of inventors

Dhahran, Saudi Arabia

Tareq Yousuf Al-Naffouri