Jürgen Freudenberger

Woven codes with outer warp: variations, design, and distance properties

We consider convolutional and block encoding schemes which are variations of woven codes with outer warp. We propose methods to evaluate the distance characteristics of the considered codes on the basis of the active distances of the component codes. With this analytical bounding technique, we derived lower bounds on the minimum (or free) distance of woven convolutional codes, woven block codes, serially concatenated codes, and woven turbo codes. Next, we show that the lower bound on the minimum distance can be improved if we use designed interleaving with unique permutation functions in each row of the warp of the woven encoder. Finally, with the help of simulations, we get upper bounds on the minimum distance for some particular codes and then investigate their performance in the Gaussian channel. Throughout this paper, we compare all considered encoding schemes by means of examples, which illustrate their distance properties.

Microphone diversity combining for in-car applications

This paper proposes a frequency domain diversity approach for two or more microphone signals, for example, for in-car applications. The microphones should be positioned separately to insure diverse signal conditions and incoherent recording of noise. This enables a better compromise for the microphone position with respect to different speaker sizes and noise sources. This work proposes a two-stage approach. In the first stage, the microphone signals are weighted with respect to their signal-to-noise ratio and then summed similar to maximum ratio combining. The combined signal is then used as a reference for a frequency domain least-mean-squares (LMS) filter for each input signal. The output SNR is significantly improved compared to coherence-based noise reduction systems, even if one microphone is heavily corrupted by noise.

A CONFIGURABLE BOSE–CHAUDHURI–HOCQUENGHEM CODEC ARCHITECTURE FOR FLASH CONTROLLER APPLICATIONS

Error correction coding (ECC) has become one of the most important tasks of flash memory controllers. The gate count of the ECC unit is taking up a significant share of the overall logic. Scaling the ECC strength to the growing error correction requirements has become increasingly difficult when considering cost and area limitations. This work presents a configurable encoding and decoding architecture for binary Bose–Chaudhuri–Hocquenghem (BCH) codes. The proposed concept supports a wide range of code rates and facilitates a trade-off between throughput and space complexity. Commonly, hardware implementations for BCH decoding perform many Galois field multiplications in parallel. We propose a new decoding technique that uses different parallelization degrees depending on the actual number of errors. This approach significantly reduces the number of required multipliers, where the average number of decoding cycles is even smaller than with a fully parallel implementation.

An algorithm for detecting unreliable code sequence segments and its applications

Let the Viterbi algorithm be applied for maximum-likelihood decoding of a terminated convolutional code using a trellis. We propose an additional procedure that permits a receiver to locate unreliable segments within an estimated code sequence. This reliability output may be used, for example, to request retransmissions, in systems with error concealment, or in channel-coding systems with unequal error protection.

A noise PSD and cross-PSD estimation for two-microphone speech enhancement systems

In this paper, we propose an efficient noise power and noise cross-power spectral density estimation method for distributed microphones. The proposal can be combined with coherence based two-microphone noise reduction systems. It utilizes a minimum statistic based noise PSD estimator for each channel and a joint voice activity detector. Evaluation results show that the voice activity detection significantly improves the individual estimates.

Partially concatenated convolutional codes

We present a new concatenated code construction. The resulting codes can be viewed as intermediate between parallel and serially concatenated convolutional codes. Proper partitioning of the outer code sequence provides a new degree of freedom for code design. Various methods are considered to analyze code properties.

New Coding Techniques for Codes over Gaussian Integers

This work presents block codes over Gaussian integers. We introduce Gaussian integer rings which extend the number of possible signal constellations over Gaussian integer fields. Many well-known code constructions can be used for codes over Gaussian integer rings, e.g., the Plotkin construction or product codes. These codes enable low complexity decoding in the complex domain. Furthermore, we demonstrate that the concept of set partitioning can be applied to Gaussian integers. This enables multilevel code constructions. In addition to the code constructions, we present a low complexity soft-input decoding algorithm for one Mannheim error correcting codes. The presented decoding method is based on list decoding, where the list of candidate codewords is obtained by decomposing the syndrome into two sub-syndromes. Considering all decompositions of the syndrome we construct lists of all possible errors of Mannheim weight two. In the last decoding step the squared Euclidean distance is used to select the best codeword from the list. Simulation results for the additive white Gaussian noise channel demonstrate that the proposed decoding method achieves a significant coding gain compared with hard-input decoding.

Blind-Matched Filtering for Speech Enhancement with Distributed Microphones

A multichannel noise reduction and equalization approach for distributed microphones is presented. The speech enhancement is based on a blind-matched filtering algorithm that combines the microphone signals such that the output SNR is maximized. The algorithm is developed for spatially uncorrelated but nonuniform noise fields, that is, the noise signals at the different microphones are uncorrelated, but the noise power spectral densities can vary. However, no assumptions on the array geometry are made. The proposed method will be compared to the speech distortion-weighted multichannel Wiener filter (SDW-MWF). Similar to the SDW-MWF, the new algorithm requires only estimates of the input signal to noise ratios and the input cross-correlations. Hence, no explicit channel knowledge is necessary. A new version of the SDW-MWF for spatially uncorrelated noise is developed which has a reduced computational complexity, because matrix inversions can be omitted. The presented blind-matched filtering approach is similar to this SDW-MWF for spatially uncorrelated noise but additionally achieves some improvements in the speech quality due to a partial equalization of the acoustic system.

Time-frequency dependent voice activity detection based on a simple threshold test

This paper proposes an efficient method to determine for each time-frequency point whether speech is present or absent in a noisy microphone signal. Based on a likelihood ratio test for the conditional speech presence probability a simple threshold test is derived. This test compares the current input power for each time-frequency point with an estimate of the noise power spectral density. The theoretical results as well as the simulation results indicate that voice activity is well approximated.

A multichannel Wiener filter with partial equalization for distributed microphones

In speech enhancement applications, the multichannel Wiener filter (MWF) is widely used to reduce noise and thus improve signal quality. The MWF performs noise reduction by estimating the desired signal component in one of the microphones, referred to as the reference microphone. However, for distributed microphones, the selection of the reference microphone has a significant impact on the broadband output SNR of the MWF, largely depending on the acoustical transfer function (ATF) between the desired source and the reference microphone. In this paper, a multichannel Wiener filtering approach using a soft combined reference is presented. Simulation results show that the proposed scheme leads to a higher broadband output SNR compared to an arbitrarily selected reference microphone, moreover achieving a partial equalization of the overall acoustic system.