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Achieving high resolution time-of-arrival (TOA) estimation in multipath propagation scenarios from bandlimited observations of communication signals is challenging because the multipath channel impulse response (CIR) is not bandlimited. Modeling the CIR as a sparse sequence of Diracs, TOA estimation becomes a problem of parametric spectral inference from observed bandlimited signals. To increase resolution without arriving at unrealistic sampling rates, we consider multiband sampling approach, and propose a practical multibranch receiver for the acquisition.


The knowledge of the downlink (DL) channel spatial covariance matrix at the BS is of fundamental importance for large-scale array systems operating in frequency division duplexing (FDD) mode. In particular, this knowledge plays a key role in the DL channel state information (CSI) acquisition. In the massive MIMO regime, traditional schemes based on DL pilots are severely limited by the covariance feedback and the DL training overhead. To overcome this problem, many authors have proposed to obtain an estimate of the DL spatial covariance based on uplink (UL) measurements.


In this paper we study the tone reservation technique for the reduction of the peak to average power ratio (PAPR) in code division multiple access (CDMA) systems that employ the Walsh functions. In the tone reservation method, the available carriers are partitioned into two sets, the information set, which carries the information, and the compensation set, which is used to reduce the PAPR. Central questions are: What is the best possible reduction of the PAPR? What is the optimal information set that achieves this reduction, and how can it be found?


Large peak to average power ratios (PAPRs) are problematic for communication systems. One possible approach to control the PAPR is the tone reservation method. We analyze the tone reservation method for general complete orthonormal systems, and consider two solvability concepts: strong solvability and weak solvability. Strong solvability requires a rather strong control of the peak value of the transmit signal by the energy of the information signal, and thus might be to restrictive for practical applications.


In noisy and reverberant environments speech enhancement techniques such as the multi-channel Wiener filter (MWF) can be used to improve speech quality and intelligibility. Assuming that reverberation and ambient noise can be modeled as diffuse sound fields, such techniques require an estimate of the diffuse power spectral density (PSD). Recently a multi-channel diffuse PSD estimator based on the eigenvalue decomposition (EVD) of the prewhitened signal PSD matrix was proposed.