Measurements, Models, Systems and Design

531 s.

Waveform Design for 5G and beyond Systems

5G traffic has very diverse requirements with respect to data rate, delay, and reliability. The concept of using multiple OFDM numerologies adopted in the 5G NR standard will likely meet these multiple requirements to some extent. However, the traffic is radically accruing different characteristics and requirements when compared with the initial stage of 5G, which focused mainly on high-speed multimedia data applications. For instance, applications such as vehicular communications and robotics control require a highly reliable and ultra-low delay. In addition, various emerging M2M applications have sparse traffic with a small amount of data to be delivered. The state-of-the-art OFDM technique has some limitations when addressing the aforementioned requirements at the same time. Meanwhile, numerous waveform alternatives, such as FBMC, GFDM, and UFMC, have been explored. They also have their own pros and cons due to their intrinsic waveform properties. Hence, it is the opportune moment to come up with modification/variations/combinations to the aforementioned techniques or a new waveform design for 5G systems and beyond. The aim of this Special Issue is to provide the latest research and advances in the field of waveform design for 5G systems and beyond

On the Efficient Broadcasting of Heterogeneous Services over Band-Limited Channels: Unequal Power Allocation for Wavelet Packet Division Multiplexing

Multiple transmission of heterogeneous services is a central aspect of broadcasting technology. Often, in this framework, the design of efficient communication systems is complicated by stringent bandwidth constraint. In wavelet packet division multiplexing (WPDM), the message signals are waveform coded onto wavelet packet basis functions. The overlapping nature of such waveforms in both time and frequency allows improving the performance over the commonly used FDM and TDM schemes, while their orthogonality properties permit to extract the message signals by a simple correlator receiver. Furthermore, the scalable structure of WPDM makes it suitable for broadcasting heterogeneous services. This work investigates unequal error protection (UEP) of data which exhibit different sensitivities to channel errors to improve the performance of WPDM for transmission over band-limited channels. To cope with bandwidth constraint, an appropriate distribution of power among waveforms is proposed which is driven by the channel error sensitivities of the carried message signals in case of Gaussian noise. We address this problem by means of the genetic algorithms (GAs), which allow flexible suboptimal solution with reduced complexity. The mean square error (MSE) between the original and the decoded message, which has a strong correlation with subjective perception, is used as an optimization criterion

Evolutionary Computing and Second generation Wavelet Transform optimization: Current State of the Art

The Evolutionary Computation techniques are exposed to number of domains to achieve optimization. One of those domains is second generation wavelet transformations for image compression. Various types of Lifting Schemes are being introduced in recent literature. Since the growth in Lifting Schemes is in an incremental way and new types of Lifting Schemes are appearing continually. In this context, developing flexible and adaptive optimization approaches is a severe challenge. Evolutionary Computing based lifting scheme optimization techniques are a valuable technology to achieve better results in image compression. However, despite the variety of such methods described in the literature in recent years, security tools incorporating anomaly detection functionalities are just starting to appear, and several important problems remain to be solved. In this paper, we present a review of the most well-known EC approaches for optimizing Secondary level Wavelet transformations

VLSI implementation of a massively parallel wavelet based zerotree coder for the intelligent pixel array

In the span of a few years, mobile multimedia communication has rapidly become a significant area of research and development constantly challenging boundaries on a variety of technologic fronts. Mobile video communications in particular encompasses a number of technical hurdles that generally steer technological advancements towards devices that are low in complexity, low in power usage yet perform the given task efficiently. Devices of this nature have been made available through the use of massively parallel processing arrays such as the Intelligent Pixel Processing Array. The Intelligent Pixel Processing array is a novel concept that integrates a parallel image capture mechanism, a parallel processing component and a parallel display component into a single chip solution geared toward mobile communications environments, be it a PDA based system or the video communicator wristwatch portrayed in Dick Tracy episodes. This thesis details work performed to provide an efficient, low power, low complexity solution surrounding the massively parallel implementation of a zerotree entropy codec for the Intelligent Pixel Array

Self-similarity and wavelet forms for the compression of still image and video data

This thesis is concerned with the methods used to reduce the data volume required to represent still images and video sequences. The number of disparate still image and video coding methods increases almost daily. Recently, two new strategies have emerged and have stimulated widespread research. These are the fractal method and the wavelet transform. In this thesis, it will be argued that the two methods share a common principle: that of self-similarity. The two will be related concretely via an image coding algorithm which combines the two, normally disparate, strategies. The wavelet transform is an orientation selective transform. It will be shown that the selectivity of the conventional transform is not sufficient to allow exploitation of self-similarity while keeping computational cost low. To address this, a new wavelet transform is presented which allows for greater orientation selectivity, while maintaining the orthogonality and data volume of the conventional wavelet transform. Many designs for vector quantizers have been published recently and another is added to the gamut by this work. The tree structured vector quantizer presented here is on-line and self structuring, requiring no distinct training phase. Combining these into a still image data compression system produces results which are among the best that have been published to date. An extension of the two dimensional wavelet transform to encompass the time dimension is straightforward and this work attempts to extrapolate some of its properties into three dimensions. The vector quantizer is then applied to three dimensional image data to produce a video coding system which, while not optimal, produces very encouraging results

A DWT based perceptual video coding framework: concepts, issues and techniques

The work in this thesis explore the DWT based video coding by the introduction of a novel DWT (Discrete Wavelet Transform) / MC (Motion Compensation) / DPCM (Differential Pulse Code Modulation) video coding framework, which adopts the EBCOT as the coding engine for both the intra- and the inter-frame coder. The adaptive switching mechanism between the frame/field coding modes is investigated for this coding framework. The Low-Band-Shift (LBS) is employed for the MC in the DWT domain. The LBS based MC is proven to provide consistent improvement on the Peak Signal-to-Noise Ratio (PSNR) of the coded video over the simple Wavelet Tree (WT) based MC. The Adaptive Arithmetic Coding (AAC) is adopted to code the motion information. The context set of the Adaptive Binary Arithmetic Coding (ABAC) for the inter-frame data is redesigned based on the statistical analysis. To further improve the perceived picture quality, a Perceptual Distortion Measure (PDM) based on human vision model is used for the EBCOT of the intra-frame coder. A visibility assessment of the quantization error of various subbands in the DWT domain is performed through subjective tests. In summary, all these findings have solved the issues originated from the proposed perceptual video coding framework. They include: a working DWT/MC/DPCM video coding framework with superior coding efficiency on sequences with translational or head-shoulder motion; an adaptive switching mechanism between frame and field coding mode; an effective LBS based MC scheme in the DWT domain; a methodology of the context design for entropy coding of the inter-frame data; a PDM which replaces the MSE inside the EBCOT coding engine for the intra-frame coder, which provides improvement on the perceived quality of intra-frames; a visibility assessment to the quantization errors in the DWT domain

Broadcast quality video over IP

We consider the problem of designing systems for the transmission of high-quality video signals over certain high-speed segments of the public IP network. Our most important contribution is the definition of a network/coder interface for IP networks which gathers channel state information, and then sets parameters of the video coder to maximize the quality of the signal delivered to the receiver, while remaining fair to other data or video connections. This interface plays a role analogous to that of a Leaky Bucket controller, in that it specifies traffic shaping parameters which result in simultaneous good Quality of Service (QoS) for the source and good network performance. Since the network is not assumed to provide any form of QoS guarantee, fundamental to our construction is a hidden Markov model for the channel, based on which the interface solves a problem of optimal stochastic control, to decide how to configure the encoder. Other contributions are (a) modifications to the standard Internet transport protocol, to make it suitable for the transport of delay-constrained traffic and to gather channel state information, and (b) the design of an error-resilient video coder. Experimental studies reveal that the proposed system is able to stream video signals of the quality of current TV-broadcasts, among hosts in wide-area networks connected to the experimental vBNS backbone

Development and applications of adaptive IIR and subband filters

Adaptive infinite impulse response (IIR) filter is a challenging research area. Identifiers and Equalizers are among the most essential digital signal processing devices for digital communication systems. In this study, we consider IIR channel both for system identification and channel equalization purposes. We focus on four different approaches: Least Mean Square (LMS), Recursive Least Square (RLS), Genetic Algorithm (GA) and Subband Adaptive Filter (SAF). ). The performance of conventional LMS and RLS based IIR system identification and channel equalization are found with the help of computer simulations. And also the convergence speed and the ability to locate the global optimum solution using a population based algorithm named Genetic Algorithm is given