K.-D. Kammeyer’s research while affiliated with University of Bremen and other places

In this contribution objective measures for quality assessment of speech signals are evaluated for listening-room compensation algorithms. Dereverberation of speech signals by means of equalization of the room impulse response and reverberation suppression has been an active research topic within the last years. However, no commonly accepted objective quality measures exist for assessment of the enhancement achieved by those algorithms. This paper discusses several objective quality measures and their applicability for dereverberation of speech signals focusing on algorithms for listening-room compensation.

In this contribution objective measures for quality assessment of speech signals are evaluated for listeningroom compensation algorithms. Dereverberation of speech signals by means of equalization of the room impulse response and reverberation suppression has been an active research topic within the last years. However, nocommonly accepted objective quality measuresexist forassessment of the enhancement achieved by those algorithms. This paper discusses several objective quality measures and their applicability for dereverberation of speech signals focusing on algorithms for listening-room compensation.

Equalization of room impulse responses is an attractive approach for dereverberation of speech signals in a hands-free scenario. In this contribution we address the choice of the delay which has to be introduced in leastsquares

Usually the primary goal for the application of optimization algorithms is convergence to the global optimum, and the secondary goal is to use the least computational effort. By application of different stopping criteria the achievement of both objectives is influenced: If an optimization run is terminated too early, convergence may not be reached, but on the other hand computational resources may be wasted if the optimization run is stopped late. Because the two criteria that are applied mostly in evolutionary algorithms literature have some drawbacks, several stopping criteria are analyzed in this work, using the Differential Evolution algorithm. In contrast to a prior study a constrained optimization problem is used here. It consists of optimizing the power allocation for a CDMA (Code Division Multiple Access) system that includes a parallel interference cancellation technique.

Hands-free telecommunication systems usually employ subsystems for acoustic echo cancellation (AEC), listening-room compensation (LRC) and noise reduction in combination. This contribution discusses a combined system of a two-stage AEC filter and an LRC filter to remove reverberation introduced by the listening room. An inner AEC is used to achieve initial echo reduction and to perform system identification needed for the LRC filter. An additional outer AEC is used to further reduce the acoustic echoes. The performance of proportionate filter update schemes such as the so-called proportionate normalized least mean squares algorithm (PNLMS) or the improved PNLMS (IPNLMS) for system identification of equalized impulse response (IR) are shown and the mutual influences of the subsystems are analyzed. If the LRC filter succeeds in shaping a sparse overall IR for the concatenated system of LRC filter and room impulse response (RIR), the PNLMS performs best since it is optimized for the identification of sparse IRs. However, the equalization may be imperfect due to channel estimation errors in periods of convergence and due to the so-called tail-effect of AEC, i.e. the fact that only the first part of an RIR is identified in practical systems. The IPNLMS is more appropriate in this case to identify the equalized IR.

In general, the unequal RF circuitry in the transmit and receive chains at the base station (BS) prevents the exploitation of the uplink (UL) channel estimate for proper pre-equalization in time division duplex (TDD) systems. To avoid additional transceiver hardware costs for matching networks, the idea of relative calibration was introduced to cope with the different effective channel impulse responses of UL and downlink (DL) by means of signal processing. However, multiple-input multiple-output (MIMO) transmission in frequency-selective channels does not allow for classical frequency-domain calibration principles based on total least squares (TLS) approaches. Consequently, more complex structured total least squares (STLS) problems must be solved. In this paper the application of the signal property mapping principle is introduced to iteratively solve the STLS calibration problem. Exemplified by simulation results for single-carrier frequency-domain pre-equalization (SC-preFDE) systems the algorithm indicates good and fast convergence behavior and effectively exploits noisy UL and DL channel measurements for system calibration.

Currently evolving communication standards, especially those using multi-antenna (MIMO) multicarrier modulation techniques, are based on the exploitation of channel state information (CSI) at the transmitter. The utilization of adaptive transmission schemes comes with a more sensitive behavior with respect to front-end imperfections. Direct-conversion architectures in turn allow for low-cost transceiver solutions but introduce higher imbalances of the in-phase (I) and quadrature (Q) branches. For adaptive systems with high data rates severe performance losses are observed with respect to bit error rates (BER). In this paper the influence of transmitter side I/Q imbalances is investigated with respect to a MIMO hardware demonstrator, which applies adaptive Orthogonal Frequency Division Multiplexing (OFDM) strategies. An enhanced algorithm for blind online pre-compensation is presented. Comparable single-tone low-IF measurement results indicate an improved image signal suppression and higher convergence robustness while the system shows decreased downlink BER after compensation.

In multi-user orthogonal frequency division multiplexing (MU-OFDM) systems operating in time division duplex (TDD) mode downlink pre-equalization can be applied relying on channel state information (CSI) from the uplink direction. Unfortunately, the prerequisite of channel reciprocity is usually not fulfilled due to non-reciprocal transceivers. Hence, this paper deals with a comparison of robust pre-equalization schemes and a calibration approach to enhance the necessary uplink-downlink link equivalence for MU-MISO-OFDM systems applying linear and non-linear pre-equalization techniques and strong forward error correction (FEC). Performance evaluations concerning coded bit error rate results show that robust pre-equalizers exclusively improve the performance in moderate non-reciprocity conditions. In contrast, only calibration helps in dealing with severe transceiver mismatch.

Subcarrier selection mitigates the need for suppression of one sideband at the transmitter side for Intensity Modulation/Direct Detection OFDM systems caused by group velocity dispersion of the fiber and thus reduces optical hardware efforts.