Teaching MODEM Concepts and Design Procedure with MATLAB Simulations
MATLAB simulation is used as the primary tool to illustrate concepts, to validate MODEM designs, and to vent' operation of the subsystems employed in DSP based transmitters and receivers presented in a pair of classes on MODEM Design and Digital Receiver Design. The whole gamut of subsystems found in conventional and experimental modem designs are simulated and assembled to form a full end-to-end simulation of an operating MODEM. This paper describes the philosophy used to guide class involvement and assess the experience and the learning value to student participants.
Cascaded Integrator-Comb (CIC) Filter Introduction
In the classic paper, "An Economical Class of Digital Filters for Decimation and Interpolation", Hogenauer introduced an important class of digital filters called "Cascaded Integrator-Comb", or "CIC" for short (also sometimes called "Hogenauer filters"). Here, Matthew Donadio provides a more gentle introduction to the subject of CIC filters, geared specifically to the needs of practicing DSP designers.
Real-Time DSP Implementation of an Acoustic-Echo-Canceller with a Delay-Sum Beamformer
Traditional telephony uses only a single receiver for speech acquisition. If the speaker is standing away from the telephone, the signal will be weak and there will be interference sources from room reverberation. In addition, there is acoustic echo coming from the loudspeaker, which further interferes with the signal of interest. This research investigated the combination of common solutions to these problems. Electronic beamforming steered an array of microphones within software to enhance the signal power. Echo cancellation removed the echo coming from the loudspeaker. In combination these processing techniques can greatly enhance user experience.
LOW-RESOURCE DELAYLESS SUBBAND ADAPTIVE FILTER USING WEIGHTED OVERLAP-ADD
A delayless structure targeted for low-resource implementation is proposed to eliminate filterbank processing delays in subband adaptive filters (SAFs). Rather than using direct IFFT or polyphase filterbanks to transform the SAFs back into the time-domain, the proposed method utilizes a weighted overlap-add (WOLA) synthesis. Low-resource real-time implementations are targeted and as such do not involve long (as long as the echo plant) FFT or IFFT operations. Also, the proposed approach facilitates time distribution of the adaptive filter reconstruction calculations crucial for efficient real-time and hardware implementation. The method is implemented on an oversampled WOLA filterbank employed as part of an echo cancellation application. Evaluation results demonstrate that the proposed implementation outperforms conventional SAF systems since the signals used in actual adaptive filtering are not distorted by filterbank aliasing. The method is a good match for partial update adaptive algorithms since segments of the time-domain adaptive filter are sequentially reconstructed and updated.
FUZZY LOGIC BASED CONVOLUTIONAL DECODER FOR USE IN MOBILE TELEPHONE SYSTEMS
Efficient convolutional coding and decoding algorithms are most crucial to successful operation of wireless communication systems in order to achieve high quality of service by reducing the overall bit error rate performance. A widely applied and well evaluated scheme for error correction purposes is well known as Viterbi algorithm [7]. Although the Viterbi algorithm has very good error correcting characteristics, computational effort required remains high. In this paper a novel approach is discussed introducing a convolutional decoder design based on fuzzy logic. A simplified version of this fuzzy based decoder is examined with respect to bit error rate (BER) performance. It can be shown that the fuzzy based convolutional decoder here proposed considerably reduces computational effort with only minor BER performance degradation when compared to the classical Viterbi approach.
Ignal Enhancement Using Time-Frequency Based Denoising
This thesis investigates and compares time and wavelet-domain denoising techniques where received signals contain broadband noise. We consider how time and wavelet-domain denoising schemes and their combinations compare in the mean squared error sense. This work applies Wiener prediction and Median filtering as they do not require any prior signal knowledge. In the wavelet-domain we use soft or hard thresholding on the detail coefficients. In addition, we explore the effect of these wavelet-domain thresholding techniques on the coefficients associated with cycle-spinning and the newly proposed recursive cycle-spinning scheme. Finally, we note that thresholding does not make an attempt to de-noise coefficients that remain after thresholding; therefore we apply time domain techniques to the remaining detail coefficients from the first level of decomposition in an attempt to de-noise them further prior to reconstruction. This thesis applies and compares these techniques using a mean squared error criterion to identify the best performing in a robust test signal environment. We find that soft thresholding with Stein’s Unbiased Risk Estimate (SURE) thresholding produces the best mean squared error results in each test case and that the addition of Wiener prediction to the first level of decomposition coefficients leads to a slightly enhanced performance. Finally, we illustrate the effects of denoising algorithms on longer data segments.
A Multimedia DSP processor design
This Master Thesis presents the design of the core of a fixed point general purpose multimedia DSP processor (MDSP) and its instruction set. This processor employs parallel processing techniques and specialized addressing models to speed up the processing of multimedia applications. The MDSP has a dual MAC structure with one enhanced MAC that provides a SIMD, Single Instruction Multiple Data, unit consisting of four parallel data paths that are optimized for accelerating multimedia applications. The SIMD unit performs four multimedia-oriented 16-bit operations every clock cycle. This accelerates computationally intensive procedures such as video and audio decoding. The MDSP uses a memory bank of four memories to provide multiple accesses of source data each clock cycle.
