Efficient time delay estimation and compensation applied to the cancellation of acoustic echo

The system identification problem is notably dealt with using adaptive filtering approaches. In many applications the unknown system response consists of an initial sequence of zero-valued coefficients that precedes the active part of the response. The presence of these coefficients introduces a flat delay in the incoming signals which can take significantly large values. When most adaptive approaches attempt to model such a system, the presence of flat delay impairs their operation and performance. The approach introduced in this thesis aims to model the flat delay and active part of the unknown system separately. An efficient system for time delay estimation (TDE) is introduced to estimate the flat delay of an unknown system. The estimated delay is then compensated within the adaptive system thus allowing the latter to cover the active part ofthe unknown system. The proposed system is applied to the Acoustic Echo Cancellation (ABC) problem

Algorithms and structures for long adaptive echo cancellers

The main theme of this thesis is adaptive echo cancellation. Two novel independent approaches are proposed for the design of long echo cancellers with improved performance. In the first approach, we present a novel structure for bulk delay estimation in long echo cancellers which considerably reduces the amount of excess error. The miscalculation of the delay between the near-end and the far-end sections is one of the main causes of this excess error. Two analyses, based on the Least Mean Squares (LMS) algorithm, are presented where certain shapes for the transitions between the end of the near-end section and the beginning of the far-end one are considered. Transient and steady-state behaviours and convergence conditions for the proposed algorithm are studied. Comparisons between the algorithms developed for each transition are presented, and the simulation results agree well with the theoretical derivations. In the second approach, a generalised performance index is proposed for the design of the echo canceller. The proposed algorithm consists of simultaneously applying the LMS algorithm to the near-end section and the Least Mean Fourth (LMF) algorithm to the far-end section of the echo canceller. This combination results in a substantial improvement of the performance of the proposed scheme over both the LMS and other algorithms proposed for comparison. In this approach, the proposed algorithm will be henceforth called the Least Mean Mixed-Norm (LMMN) algorithm. The advantages of the LMMN algorithm over previously reported ones are two folds: it leads to a faster convergence and results in a smaller misadjustment error. Finally, the convergence properties of the LMMN algorithm are derived and the simulation results confirm the superior performance of this proposed algorithm over other well known algorithms

An elementary quantum network of entangled optical atomic clocks

Demonstration of entanglement-enhanced frequency comparison of two optical atomic clocks based on the 674nm quadrupole transition of 88Sr+ ions, which are linked by a quantum-optical fibre link (≈2 m long). We show that the use of an entangled state reduces the measurement uncertainty by nearly √2 , the value expected for the Heisenberg Limit. Today's optical clocks are typically limited by dephasing of the probe laser; in this regime, we find that entanglement yields a factor 2 reduction in the measurement uncertainty compared to conventional correlation spectroscopy techniques. We demonstrate this enhancement for the measurement of a frequency shift applied to one of the clocks

Theory, design and application of gradient adaptive lattice filters

SIGLELD:D48933/84 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Estimation and detection of transmission line characteristics in the copper access network

The copper access-network operators face the challenge of developing and maintaining cost-effective digital subscriber line (DSL) services that are competitive to other broadband access technologies. The way forward is dictated by the demand of ever increasing data rates on the twisted-pair copper lines. To meet this demand, a relocation of the DSL transceivers in cabinets closer to the customers are often necessary combined with a joint expansion of the accompanying optical-fiber backhaul network. The equipment of the next generation copper network are therefore becoming more scattered and geographically distributed, which increases the requirements of automated line qualification with fault detection and localization. This scenario is addressed in the first five papers of this dissertation where the focus is on estimation and detection of transmission line characteristics in the copper access network. The developed methods apply model-based optimization with an emphasis on using low-order modeling and a priori information of the given problem. More specifically, in Paper I a low-order and causal cable model is derived based on the Hilbert transform. This model is successfully applied in three contributions of this dissertation. In Paper II, a class of low-complexity unbiased estimators for the frequency-dependent characteristic impedance is presented that uses one-port measurements only. The so obtained characteristic impedance paves the way for enhanced time domain reflectometry (a.k.a. TDR) on twisted-pair lines. In Paper III, the problem of estimating a nonhomogeneous and dispersive transmission line is investigated and a space-frequency optimization approach is developed for the DSL application. The accompanying analysis shows which parameters are of interest to estimate and further suggests the introduction of the concept capacitive length that overcomes the necessity of a priori knowledge of the physical line length. In Paper IV, two methods are developed for detection and localization of load coils present in so-called loaded lines. In Paper V, line topology identification is addressed with varying degree of a priori information. In doing so, a model-based optimization approach is employed that utilizes multi-objective evolutionary computation based on one/two-port measurements. A complement to transceiver relocation that potentially enhances the total data throughput in the copper access network is dynamic spectrum management (DSM). This promising multi-user transmission technique aims at maximizing the transmission rates, and/or minimizing the power consumption, by mitigating or cancelling the dominating crosstalk interference between twisted-pair lines in the same cable binder. Hence the spectral utilization is improved by optimizing the transmit signals in order to minimize the crosstalk interference. However, such techniques rely on accurate information of the (usually) unknown crosstalk channels. This issue is the main focus of Paper VI and VII of this dissertation in which Paper VI deals with estimation of the crosstalk channels between twisted-pair lines. More specifically, an unbiased estimator for the square-magnitude of the crosstalk channels is derived from which a practical procedure is developed that can be implemented with standardized DSL modems already installed in the copper access network. In Paper VII the impact such a non-ideal estimator has on the performance of DSM is analyzed and simulated. Finally, in Paper VIII a novel echo cancellation algorithm for DMT-based DSL modems is presented