To Develop and Implement Low Power, High Speed VLSI for Processing Signals using Multirate Techniques

Multirate technique is necessary for systems with different input and output sampling rates. Recent advances in mobile computing and communication applications demand low power and high speed VLSI DSP systems [4]. This Paper presents Multirate modules used for filtering to provide signal processing in wireless communication system. Many architecture developed for the design of low complexity, bit parallel Multiple Constant Multiplications operation which dominates the complexity of DSP systems. However, major drawbacks of present approaches are either too costly or not efficient enough. On the other hand, MCM and digit-serial adder offer alternative low complexity designs, since digit-serial architecture occupy less area and are independent of the data word length [1][10]. Multiple Constant Multiplications is efficient way to reduce the number of addition and subtraction in polyphase filter implementation. This Multirate design methodology is systematic and applicable to many problems. In this paper, attention has given to the MCM & digit serial architecture with shifting and adding techniques that offers alternative low complexity in operations. This paper also focused on Multirate Signal Processing Modules using Voltage and Technology scaling. Reduction of power consumption is important for VLSI system and also it becomes one of the most critical design parameter. Transistorized Multirate module which has full custom design with different circuit topology and optimization level simulated on cadence platform. Multirate modules are used AMI 0.6 um, TSMC 0.35 um, and TSMC 0.25 um technologies for different voltage scaling. The presented methodology provides a systematic way to derive circuit technique for high speed operation at a low supply voltage. Multirate polyphase interpolator and decimator are also designed and optimized at architectural level in order to analyze the terms power consumption, area and speed. DOI: 10.17762/ijritcc2321-8169.150314

Statistically optimum pre- and postfiltering in quantization

We consider the optimization of pre- and postfilters surrounding a quantization system. The goal is to optimize the filters such that the mean square error is minimized under the key constraint that the quantization noise variance is directly proportional to the variance of the quantization system input. Unlike some previous work, the postfilter is not restricted to be the inverse of the prefilter. With no order constraint on the filters, we present closed-form solutions for the optimum pre- and postfilters when the quantization system is a uniform quantizer. Using these optimum solutions, we obtain a coding gain expression for the system under study. The coding gain expression clearly indicates that, at high bit rates, there is no loss in generality in restricting the postfilter to be the inverse of the prefilter. We then repeat the same analysis with first-order pre- and postfilters in the form 1+αz-1 and 1/(1+γz^-1 ). In specific, we study two cases: 1) FIR prefilter, IIR postfilter and 2) IIR prefilter, FIR postfilter. For each case, we obtain a mean square error expression, optimize the coefficients α and γ and provide some examples where we compare the coding gain performance with the case of α=γ. In the last section, we assume that the quantization system is an orthonormal perfect reconstruction filter bank. To apply the optimum preand postfilters derived earlier, the output of the filter bank must be wide-sense stationary WSS which, in general, is not true. We provide two theorems, each under a different set of assumptions, that guarantee the wide sense stationarity of the filter bank output. We then propose a suboptimum procedure to increase the coding gain of the orthonormal filter bank

Networked Control System Design and Parameter Estimation

Networked control systems (NCSs) are a kind of distributed control systems in which the data between control components are exchanged via communication networks. Because of the attractive advantages of NCSs such as reduced system wiring, low weight, and ease of system diagnosis and maintenance, the research on NCSs has received much attention in recent years. The first part (Chapter 2 - Chapter 4) of the thesis is devoted to designing new controllers for NCSs by incorporating the network-induced delays. The thesis also conducts research on filtering of multirate systems and identification of Hammerstein systems in the second part (Chapter 5 - Chapter 6). Network-induced delays exist in both sensor-to-controller (S-C) and controller-to-actuator (C-A) links. A novel two-mode-dependent control scheme is proposed, in which the to-be-designed controller depends on both S-C and C-A delays. The resulting closed-loop system is a special jump linear system. Then, the conditions for stochastic stability are obtained in terms of a set of linear matrix inequalities (LMIs) with nonconvex constraints, which can be efficiently solved by a sequential LMI optimization algorithm. Further, the control synthesis problem for the NCSs is considered. The definitions of H₂ and H∞ norms for the special system are first proposed. Also, the plant uncertainties are considered in the design. Finally, the robust mixed H₂/H∞ control problem is solved under the framework of LMIs. To compensate for both S-C and C-A delays modeled by Markov chains, the generalized predictive control method is modified to choose certain predicted future control signal as the current control effort on the actuator node, whenever the control signal is delayed. Further, stability criteria in terms of LMIs are provided to check the system stability. The proposed method is also tested on an experimental hydraulic position control system. Multirate systems exist in many practical applications where different sampling rates co-exist in the same system. The l₂-l∞ filtering problem for multirate systems is considered in the thesis. By using the lifting technique, the system is first transformed to a linear time-invariant one, and then the filter design is formulated as an optimization problem which can be solved by using LMI techniques. Hammerstein model consists of a static nonlinear block followed in series by a linear dynamic system, which can find many applications in different areas. New switching sequences to handle the two-segment nonlinearities are proposed in this thesis. This leads to less parameters to be estimated and thus reduces the computational cost. Further, a stochastic gradient algorithm based on the idea of replacing the unmeasurable terms with their estimates is developed to identify the Hammerstein model with two-segment nonlinearities. Finally, several open problems are listed as the future research directions

Computational Complexity of Signal Processing Functions in Software Radio

The increased usage of mobile communication devices has imposed a challenge of achieving efficient communication with minimum power consumption. Moreover, with the advent of software defined radios (SDR), it is highly possible that signal processing functions would be implemented in software in future mobile devices. Hence, the power consumption of these future devices will be directly related to the power consumed by the processor that executes SDR software. This thesis aims at analyzing the computational complexity of different modulation schemes and signal processing communication functions of IEEE WiFi standard. This analysis provides good insight on how the computational load varies at different data rates for different modulation schemes. For this purpose, we have analyzed computational complexity of various modulation schemes and other communication functions using widely known software radio platform i.e. USRP hardware and GNU Radio open source software platform, Matlab and OProfile (open source Linux profiling tool). After performing an extensive analysis, we are able to determine how different modulation schemes and communication functions perform computationally on a given platform. This analysis would help to achieve effective communication along with the efficient use of power in SDR based system

Optimum receiver design for broadband Doppler compensation in multipath/Doppler channels with rational orthogonal wavelet signaling

Copyright © 2007 IEEEIn this paper, we address the issue of signal transmission and Doppler compensation in multipath/Doppler channels. Based on a wavelet-based broadband Doppler compensation structure, this paper presents the design and performance characterization of optimum receivers for this class of communication systems. The wavelet-based Doppler compensation structure takes account of the coexistence of multiple Doppler scales in a multipath/Doppler channel and captures the information carried by multiple scaled replicas of the transmitted signal rather than an estimation of an average Doppler as in conventional Doppler compensation schemes. The transmitted signal is recovered by the perfect reconstruction (PR) wavelet analysis filter bank (FB). We demonstrate that with rational orthogonal wavelet signaling, the proposed communication structure corresponds to a Lth-order diversity system, where L is the number of dominant transmission paths. Two receiver designs for pulse amplitude modulation (PAM) signal transmission are presented. Both receiver designs are optimal under the maximum-likelihood (ML) criterion for diversity combination and symbol detection. Good performance is achieved for both receivers in combating the Doppler effect and intersymbol interference (ISI) caused by multipath while mitigating the channel noise. In particular, the second receiver design overcomes symbol timing sensitivities present in the first design at reasonable cost to performance.Limin Yu and Langford B. Whit

Computational Complexity of Signal Processing Functions in Software Radio

The increased usage of mobile communication devices has imposed a challenge of achieving efficient communication with minimum power consumption. Moreover, with the advent of software defined radios (SDR), it is highly possible that signal processing functions would be implemented in software in future mobile devices. Hence, the power consumption of these future devices will be directly related to the power consumed by the processor that executes SDR software. This thesis aims at analyzing the computational complexity of different modulation schemes and signal processing communication functions of IEEE WiFi standard. This analysis provides good insight on how the computational load varies at different data rates for different modulation schemes. For this purpose, we have analyzed computational complexity of various modulation schemes and other communication functions using widely known software radio platform i.e. USRP hardware and GNU Radio open source software platform, Matlab and OProfile (open source Linux profiling tool). After performing an extensive analysis, we are able to determine how different modulation schemes and communication functions perform computationally on a given platform. This analysis would help to achieve effective communication along with the efficient use of power in SDR based system

Computational Complexity of Signal Processing Functions in Software Radio

The increased usage of mobile communication devices has imposed a challenge of achieving efficient communication with minimum power consumption. Moreover, with the advent of software defined radios (SDR), it is highly possible that signal processing functions would be implemented in software in future mobile devices. Hence, the power consumption of these future devices will be directly related to the power consumed by the processor that executes SDR software. This thesis aims at analyzing the computational complexity of different modulation schemes and signal processing communication functions of IEEE WiFi standard. This analysis provides good insight on how the computational load varies at different data rates for different modulation schemes. For this purpose, we have analyzed computational complexity of various modulation schemes and other communication functions using widely known software radio platform i.e. USRP hardware and GNU Radio open source software platform, Matlab and OProfile (open source Linux profiling tool). After performing an extensive analysis, we are able to determine how different modulation schemes and communication functions perform computationally on a given platform. This analysis would help to achieve effective communication along with the efficient use of power in SDR based system