Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

Design of quadrature mirror filter banks with canonical signed digit coefficients using genetic algorithms.

This thesis is about the use of a genetic algorithm to design QMF bank with canonical signed digit coefficients. A filter bank has applications in areas like video and audio coding, data communication, etc. Filter bank design is a multiobjective optimization problem. The performance depends on the reconstruction error of the overall filter bank and the individual performance of the composing lowpass filter. In this thesis we have used reconstruction error of the overall filter bank as our main objective and passband error, stopband error, stopband and passband ripples and transition width of the individual lowpass filter as constraints. Therefore filter bank design can be formulated as single objective multiple constraint optimization problem. A unique genetic algorithm is developed to optimize filer bank coefficients such that the corresponding system\u27s response matches that of an ideal system with an additional constraint that all coefficients are in canonical signed digit (CSD) format. A special restoration technique is used to restore the CSD format of the coefficients after crossover and mutation operators in Genetic algorithm. The proposed restoration technique maintains the specified word length and the maximum number of nonzero digits in filter banks coefficients. Experimental results are presented at the end. It is demonstrated that the designed genetic algorithm is reliable, and efficient for designing QMF banks.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .U67. Source: Masters Abstracts International, Volume: 43-05, page: 1785. Thesis (M.A.Sc.)--University of Windsor (Canada), 2004

Optimisation of multiplier-less FIR filter design techniques

This thesis is concerned with the design of multiplier-less (ML) finite impulse response (FIR) digital filters. The use of multiplier-less digital filters results in simplified filtering structures, better throughput rates and higher speed. These characteristics are very desirable in many DSP systems. This thesis concentrates on the design of digital filters with power-of-two coefficients that result in simplified filtering structures. Two distinct classesof ML FIR filter design algorithms are developed and compared with traditional techniques. The first class is based on the sensitivity of filter coefficients to rounding to power-of-two. Novel elements include extending of the algorithm for multiple-bands filters and introducing mean square error as the sensitivity criterion. This improves the performance of the algorithm and reduces the complexity of resulting filtering structures. The second class of filter design algorithms is based on evolutionary techniques, primarily genetic algorithms. Three different algorithms based on genetic algorithm kernel are developed. They include simple genetic algorithm, knowledge-based genetic algorithm and hybrid of genetic algorithm and simulated annealing. Inclusion of the additional knowledge has been found very useful when re-designing filters or refining previous designs. Hybrid techniques are useful when exploring large, N-dimensional searching spaces. Here, the genetic algorithm is used to explore searching space rapidly, followed by fine search using simulated annealing. This approach has been found beneficial for design of high-order filters. Finally, a formula for estimation of the filter length from its specification and complementing both classes of design algorithms, has been evolved using techniques of symbolic regression and genetic programming. Although the evolved formula is very complex and not easily understandable, statistical analysis has shown that it produces more accurate results than traditional Kaiser's formula. In summary, several novel algorithms for the design of multiplier-less digital filters have been developed. They outperform traditional techniques that are used for the design of ML FIR filters and hence contributed to the knowledge in the field of ML FIR filter design

Direct digital synthesizers : theory, design and applications

Traditional designs of high bandwidth frequency synthesizers employ the use of a phase-locked-loop (PLL). A direct digital synthesizer (DDS) provides many significant advantages over the PLL approaches. Fast settling time, sub-Hertz frequency resolution, continuous-phase switching response and low phase noise are features easily obtainable in the DDS systems. Although the principle of the DDS has been known for many years, the DDS did not play a dominant role in wideband frequency generation until recent years. Earlier DDSs were limited to produce narrow bands of closely spaced frequencies, due to limitations of digital logic and D/A-converter technologies. Recent advantages in integrated circuit (IC) technologies have brought about remarkable progress in this area. By programming the DDS, adaptive channel bandwidths, modulation formats, frequency hopping and data rates are easily achieved. This is an important step towards a "software-radio" which can be used in various systems. The DDS could be applied in the modulator or demodulator in the communication systems. The applications of DDS are restricted to the modulator in the base station. The aim of this research was to find an optimal front-end for a transmitter by focusing on the circuit implementations of the DDS, but the research also includes the interface to baseband circuitry and system level design aspects of digital communication systems. The theoretical analysis gives an overview of the functioning of DDS, especially with respect to noise and spurs. Different spur reduction techniques are studied in detail. Four ICs, which were the circuit implementations of the DDS, were designed. One programmable logic device implementation of the CORDIC based quadrature amplitude modulation (QAM) modulator was designed with a separate D/A converter IC. For the realization of these designs some new building blocks, e.g. a new tunable error feedback structure and a novel and more cost-effective digital power ramp generator, were developed.reviewe

Adaptive relay techniques for OFDM-based cooperative communication systems

Cooperative communication has been considered as a cost-effective manner to exploit the spatial diversity, improve the quality-of-service and extend transmission coverage. However, there are many challenges faced by cooperative systems which use relays to forward signals to the destination, such as the accumulation of multipath channels, complex resource allocation with the bidirectional asymmetric traffic and reduction of transmission efficiency caused by additional relay overhead. In this thesis, we aim to address the above challenges of cooperative communications, and design the efficient relay systems. Starting with the channel accumulation problem in the amplify-and-forward relay system, we proposed two adaptive schemes for single/multiple-relay networks respectively. These schemes exploit an adaptive guard interval (GI) technique to cover the accumulated delay spread and enhance the transmission efficiency by limiting the overhead. The proposed GI scheme can be implemented without any extra control signal. Extending the adaptive GI scheme to multiple-relay systems, we propose a relay selection strategy which achieves the trade-off between the transmission reliability and overhead by considering both the channel gain and the accumulated delay spread. We then consider resource allocation problem in the two-way decode-and-forward relay system with asymmetric traffic loads. Two allocation algorithms are respectively investigated for time-division and frequency-division relay systems to maximize the end-to-end capacity of the two-way system under a capacity ratio constraint. For the frequency-division systems, a balanced end-to-end capacity is defined as the objective function which combines the requirements of maximizing the end-to-end capacity and achieving the capacity ratio. A suboptimal algorithm is proposed for the frequency-division systems which separates subcarrier allocation and time/power allocation. It can achieve the similar performance with the optimal one with reduced complexity. In order to further enhance the transmission reliability and maintaining low processing delay, we propose an equalize-and-forward (EF) relay scheme. The EF relay equalizes the channel between source and relay to eliminate the channel accumulation without signal regeneration. To reduce the processing time, an efficient parallel structure is applied in the EF relay. Numerical results show that the EF relay exhibits low outage probability at the same data rate as compared to AF and DF schemes

Color television study Final report, Nov. 1965 - Mar. 1966

Color television camera for transmission from lunar and earth orbits and lunar surfac

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada