Complex Block Floating-Point Format with Box Encoding For Wordlength Reduction in Communication Systems

We propose a new complex block floating-point format to reduce implementation complexity. The new format achieves wordlength reduction by sharing an exponent across the block of samples, and uses box encoding for the shared exponent to reduce quantization error. Arithmetic operations are performed on blocks of samples at time, which can also reduce implementation complexity. For a case study of a baseband quadrature amplitude modulation (QAM) transmitter and receiver, we quantify the tradeoffs in signal quality vs. implementation complexity using the new approach to represent IQ samples. Signal quality is measured using error vector magnitude (EVM) in the receiver, and implementation complexity is measured in terms of arithmetic complexity as well as memory allocation and memory input/output rates. The primary contributions of this paper are (1) a complex block floating-point format with box encoding of the shared exponent to reduce quantization error, (2) arithmetic operations using the new complex block floating-point format, and (3) a QAM transceiver case study to quantify signal quality vs. implementation complexity tradeoffs using the new format and arithmetic operations.Comment: 6 pages, 9 figures, submitted to Asilomar Conference on Signals, Systems, and Computers 201

FPGA Implementation of the Front-End of a DOCSIS 3.0 Receiver

The introduction of cable television (CATV) in the 1940s and 1950s has significantly influenced communications technology. Originally supplying only one-way television programming, the CATV industry recognized the potential of two-way communications. Starting with the introduction of pay-per view services in the 1980s, two-way communications over CATV networks eventually expanded into supplying internet access services. The increased demand for CATV services, and thus the increased demand for CATV equipment, has led the CATV industry to develop interoperability standards. The primary standard now used by the CATV industry is the Data Over Cable Service Specification (DOCSIS). DOCSIS defines both the upstream (data towards the CATV provider) and downstream (data towards the CATV customer) transmission channels. This includes specifications for the modulators and demodulators used in these channels. The number of manufacturers of CATV modulators and demodulators has greatly increased over the last twenty years and continues to do so. As the number of competitive CATV equipment suppliers increases, these manufacturers must look to ways to remain competitive by reducing time-to-market and costs associated with equipment design, as well as allowing their designs to be flexible so that they may adapt to the improvements in DOCSIS. In the past, manufacturers have primarily used Application Specific Integrated Circuits (ASICs) to implement digital hardware designs for CATV equipment. ASICs have a very high initial setup cost and do not allow for system modifications without a complete redesign. Recently, Field Programmable Gate Array (FPGA) technology has been introduced that allows manufacturers to both modify their designed digital hardware structures without a complete physical hardware redesign, as well as providing a reduced initial setup cost. Although in the long term, ASICs provide a cheaper alternative to FPGAs when produced in quantity, FPGAs provide quicker time-to-market in new product development and allow changes to made after initial release. This ability to change designs after release and the quicker time-to-market has led manufacturers to adopt FPGAs in new products. A critical component in the upstream channel of a DOCSIS compliant system is the Quadrature Amplitude Modulated (QAM) receiver. The data received at the QAM receiver have undergone several impairments including additive noise, timing offset, and frequency and phase mismatches between the transmitted modulated signal and the signal received at the demodulator. It is the function of the front-end of the receiver to correct for these impairments. This thesis presents methods for, and an example of, the design and implementation of a DOCSIS compliant QAM receiver front-end that corrects for timing, phase and frequency impairments experienced in the upstream communication channel when additive noise is present. The circuits presented are designed and implemented to reduce hardware costs when using FPGA technology. In addition, the circuits designed do not use proprietary logic, which gives designers more flexibility when implementing their own demodulator front-end circuitry. The FPGA implementation presented in this thesis achieves an average MER of 54.3 dB in a no-noise channel and close to 31 dB MER in a 25 dBc AWGN channel. The overall design uses 65 dedicated 18-bit by 18-bit multipliers and 2,970 bytes of RAM to implement the digital front-end of the receiver

Variation-aware high-level DSP circuit design optimisation framework for FPGAs

The constant technology shrinking and the increasing demand for systems that operate under different power profiles with the maximum performance, have motivated the work in this thesis. Modern design tools that target FPGA devices take a conservative approach in the estimation of the maximum performance that can be achieved by a design when it is placed on a device, accounting for any variability in the fabrication process of the device. The work presented here takes a new view on the performance improvement of DSP designs by pushing them into the error-prone regime, as defined by the synthesis tools, and by investigating methodologies that reduce the impact of timing errors at the output of the system. In this work two novel error reduction techniques are proposed to address this problem. One is based on reduced-precision redundancy and the other on an error optimisation framework that uses information from a prior characterisation of the device. The first one is a generic architecture that is appended to existing arithmetic operators. The second defines the high-level parameters of the algorithm without using extra resources. Both of these methods allow to achieve graceful degradation whilst variation increases. A comparison of the new methods is laid against the existing methodologies, and conclusions drawn on the tradeoffs between their cost, in terms of resources and errors, and their benefits in terms of throughput. In some cases it is possible to double the performance of the design while still producing valid results.Open Acces

Design of a reusable distributed arithmetic filter and its application to the affine projection algorithm

Digital signal processing (DSP) is widely used in many applications spanning the spectrum from audio processing to image and video processing to radar and sonar processing. At the core of digital signal processing applications is the digital filter which are implemented in two ways, using either finite impulse response (FIR) filters or infinite impulse response (IIR) filters. The primary difference between FIR and IIR is that for FIR filters, the output is dependent only on the inputs, while for IIR filters the output is dependent on the inputs and the previous outputs. FIR filters also do not sur from stability issues stemming from the feedback of the output to the input that aect IIR filters. In this thesis, an architecture for FIR filtering based on distributed arithmetic is presented. The proposed architecture has the ability to implement large FIR filters using minimal hardware and at the same time is able to complete the FIR filtering operation in minimal amount of time and delay when compared to typical FIR filter implementations. The proposed architecture is then used to implement the fast affine projection adaptive algorithm, an algorithm that is typically used with large filter sizes. The fast affine projection algorithm has a high computational burden that limits the throughput, which in turn restricts the number of applications. However, using the proposed FIR filtering architecture, the limitations on throughput are removed. The implementation of the fast affine projection adaptive algorithm using distributed arithmetic is unique to this thesis. The constructed adaptive filter shares all the benefits of the proposed FIR filter: low hardware requirements, high speed, and minimal delay.Ph.D.Committee Chair: Anderson, Dr. David V.; Committee Member: Hasler, Dr. Paul E.; Committee Member: Mooney, Dr. Vincent J.; Committee Member: Taylor, Dr. David G.; Committee Member: Vuduc, Dr. Richar

The effect of coefficient quantization optimization on filtering performance and gate count

Abstract. Digital filters are an essential component of Digital Signal Processing (DSP) applications and play a crucial role in removing unwanted signal components from a desired signal. However, digital filters are known to be resource-intensive and consume a large amount of power, making it important to optimize their design in order to minimize hardware requirements such as multipliers, adders, and registers. This trade-off between filter performance and hardware consumption can be influenced by the quantization of filter coefficients. Therefore, this thesis investigates the quantization of Finite Impulse Response (FIR) filter coefficients and analyzes its impact on filter performance and hardware resource consumption. A method called dynamic quantization is introduced and an algorithm for step-by-step dynamic quantization is provided to improve upon the results obtained with the classical fixed point quantization method. To demonstrate the effectiveness of this approach, the dynamic quantization of filter coefficients for a Low-pass Equiripple FIR filter is examined and a comparative study of the magnitude response and hardware consumption of the generated filter using both the classical and dynamic quantization methods is presented. By understanding the trade-offs and benefits of each quantization method, engineers can make informed decisions about the most appropriate approach for their specific application

Digital implementation of an upstream DOCSIS QAM modulator and channel emulator

The concept of cable television, originally called community antenna television (CATV), began in the 1940's. The information and services provided by cable operators have changed drastically since the early days. Cable service providers are no longer simply providing their customers with broadcast television but are providing a multi-purpose, two-way link to the digital world. Custom programming, telephone service, radio, and high-speed internet access are just a few of the services offered by cable service providers in the 21st century. At the dawn of the internet the dominant mode of access was through telephone lines. Despite advances in dial-up modem technology, the telephone system was unable to keep pace with the demand for data throughput. In the late 1990's an industry consortium known as Cable Television Laboratories, Inc. developed a standard protocol for providing high-speed internet access through the existing CATV infrastructure. This protocol is known as Data Over Cable Service Interface Specification (DOCSIS) and it helped to usher in the era of the information superhighway. CATV systems use different parts of the radio frequency (RF) spectrum for communication to and from the user. The downstream portion (data destined for the user) consumes the bulk of the spectrum and is located at relatively high frequencies. The upstream portion (data destined to the network from the user) of the spectrum is smaller and located at the low end of the spectrum. This lower frequency region of the RF spectrum is particularly prone to impairments such as micro-reflections, which can be viewed as a type of multipath interference. Upstream data transfer in the presence of these impairments is therefore problematic and requires complex signal correction algorithms to be employed in the receiver. The quality of a receiver is largely determined by how well it mitigates the signal impairments introduced by the channel. For this reason, engineers developing a receiver require a piece of equipment that can emulate the channel impairments in any permutation in order to test their receiver. The conventional test methodology uses a hardware RF channel emulator connected between the transmitter and the receiver under test. This method not only requires an expensive RF channel emulator, but a functioning analog front-end as well. Of these two problems, the expense of the hardware emulator is likely less important than the delay in development caused by waiting for a functional analog front-end. Receiver design is an iterative, time consuming process that requires the receiver's digital signal processing (DSP) algorithms be tested as early as possible to reduce the time-to-market. This thesis presents a digital implementation of a DOCSIS-compliant channel emulator whereby cable micro-reflections and thermal noise at the analog front-end of the receiver are modelled digitally at baseband. The channel emulator and the modulator are integrated into a single hardware structure to produce a compact circuit that, during receiver testing, resides inside the same field programmable gate array (FPGA) as the receiver. This approach removes the dependence on the analog front-end allowing it to be developed concurrently with the receiver's DSP circuits, thus reducing the time-to-market. The approach taken in this thesis produces a fully programmable channel emulator that can be loaded onto FPGAs as needed by engineers working independently on different receiver designs. The channel emulator uses 3 independent data streams to produce a 3-channel signal, whereby a main channel with micro-reflections is flanked on either side by adjacent channels. Thermal noise normally generated by the receiver's analog front-end is emulated and injected into the signal. The resulting structure utilizes 43 dedicated multipliers and 401.125 KB of RAM, and achieves a modulation error ratio (MER) of 55.29 dB

An Introduction to Digital Signal Processing

An Introduction to Digital Signal Processing aims at undergraduate students who have basic knowledge in C programming, Circuit Theory, Systems and Simulations, and Spectral Analysis. The book is focused on basic concepts of digital signal processing, MATLAB simulation and implementation on selected DSP hardware in which the candidate is introduced to the basic concepts first before embarking to the practical part which comes in the later chapters. Initially Digital Signal Processing evolved as a postgraduate course which slowly filtered into the undergraduate curriculum as a simplified version of the latter. The goal was to study DSP concepts and to provide a foundation for further research where new and more efficient concepts and algorithms can be developed. Though this was very useful it did not arm the student with all the necessary tools that many industries using DSP technology would require to develop applications. This book is an attempt to bridge the gap. It is focused on basic concepts of digital signal processing, MATLAB simulation and implementation on selected DSP hardware. The objective is to win the student to use a variety of development tools to develop applications. Contents• Introduction to Digital Signal processing.• The transform domain analysis: the Discrete-Time Fourier Transform• The transform domain analysis: the Discrete Fourier Transform• The transform domain analysis: the z-transform• Review of Analogue Filter• Digital filter design.• Digital Signal Processing Implementation Issues• Digital Signal Processing Hardware and Software• Examples of DSK Filter Implementatio