Uplink channel estimation for a block-synchronous chip-asynchronous DS/CDMA system as proposed for the time-division duplex option of 3rd generation cellular systems is considered. Training midambles are employed for joint channel estimation of all users. The standard unstructured approach based on modeling the e ective user channels as unknown FIR lters is compared with two structured methods ...

In this paper, we consider a sampling and remote estimation problem, where samples of a Wiener process are forwarded to a remote estimator via a channel with queueing and random delay. The estimator reconstructs an estimate of the realtime signal value from causally received samples. We obtain the jointly optimal sampling and estimation strategy that minimizes the mean-square estimation error s...

inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. in this paper, we derive the horvitz-thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. we then introduce an alternative unbiased estimator, corresponding to post-str...

Cleaning of noise from signals is a classical and long-studied problem in signal processing. Algorithms for this task necessarily rely on an a-priori knowledge about the signal characteristics, along with information about the noise properties. For signals that admit sparse representations over a known dictionary, a commonly used denoising technique is to seek the sparsest representation that s...

In this paper, we investigate the modulation-domain Kalman filter (MDKF) and compare its performance with other time-domain and acoustic-domain speech enhancement methods. In contrast to previously reported modulation domain-enhancement methods based on fixed bandpass filtering, the MDKF is an adaptive and linear MMSE estimator that uses models of the temporal changes of the magnitude spectrum ...

In this paper a time-frequency estimator for enhancement of noisy speech signals in the DFT domain is introduced. This estimator is based on modeling the time-varying correlation of the temporal trajectories of the short time (ST) DFT components of the noisy speech signal using autoregressive (AR) models. The timevarying trajectory of the DFT components of speech in each channel is modeled by a...

Deep Neural Networks (DNNs) are becoming widely accepted in automatic speech recognition (ASR) systems. The deep structured nonlinear processing greatly improves the model’s generalization capability, but the performance under adverse environments is still unsatisfactory. In the literature, there have been many techniques successfully developed to improve Gaussian mixture models’ robustness. In...

This paper proposes a Self-interference (SI) cancellation system model of Underwater acoustic (UWA) communication for in-band full-duplex (IBFD) technology. The SI channel is separated from the Far by exploiting concurrently orthogonal pilot estimation technique using two frequency-division multiplexing (OFDM) blocks to establish orthogonality between them based on unitary matrix. Compared half...

This paper presents a new algorithm for frequency offset estimation for Polynomial Cancellation Coded Orthogonal Frequency Division Multiplexing with symbols overlapped in the time domain (Overlap PCC-OFDM). The algorithm exploits the Subcarrier Pair Imbalance (SPI) caused by frequency offset. The estimation is performed in the frequency domain. No training symbols or pilot tones are required. ...