Development of a dc-ac power conditioner for wind generator by using neural network

This project present of development single phase DC-AC converter for wind generator application. The mathematical model of the wind generator and Artificial Neural Network control for DC-AC converter is derived. The controller is designed to stabilize the output voltage of DC-AC converter. To verify the effectiveness of the proposal controller, both simulation and experimental are developed. The simulation and experimental result show that the amplitude of output voltage of the DC-AC converter can be controlled

Efficient implementation of filter bank multicarrier systems using circular fast convolution

In this paper, filter bank-based multicarrier systems using a fast convolution approach are investigated. We show that exploiting offset quadrature amplitude modulation enables us to perform FFT/IFFT-based convolution without overlapped processing, and the circular distortion can be discarded as a part of orthogonal interference terms. This property has two advantages. First, it leads to spectral efficiency enhancement in the system by removing the prototype filter transients. Second, the complexity of the system is significantly reduced as the result of using efficient FFT algorithms for convolution. The new scheme is compared with the conventional waveforms in terms of out-of-band radiation, orthogonality, spectral efficiency, and complexity. The performance of the receiver and the equalization methods are investigated and compared with other waveforms through simulations. Moreover, based on the time variant nature of the filter response of the proposed scheme, a pilot-based channel estimation technique with controlled transmit power is developed and analyzed through lower-bound derivations. The proposed transceiver is shown to be a competitive solution for future wireless networks

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Smart antennas in software radio base stations

The application of adaptive antenna techniques to fixed-architecture base stations has been shown to offer wide-ranging benefits, including interference rejection capabilities or increased coverage and spectral efficiency. Unfortunately, the actual implementation of these techniques to mobile communication scenarios has traditionally been set back by two fundamental reasons. On one hand, the lack of flexibility of current transceiver architectures does not allow for the introduction of advanced add-on functionalities. On the other hand, the often oversimplified models for the spatiotemporal characteristics of the radio communications channel generally give rise to performance predictions that are, in practice, too optimistic. The advent of software radio architectures represents a big step toward the introduction of advanced receive/transmit capabilities. Thanks to their inherent flexibility and robustness, software radio architectures are the appropriate enabling technology for the implementation of array processing techniques. Moreover, given the exponential progression of communication standards in coexistence and their constant evolution, software reconfigurability will probably soon become the only costefficient alternative for the transceiver upgrade. This article analyzes the requirements for the introduction of software radio techniques and array processing architectures in multistandard scenarios. It basically summarizes the conclusions and results obtained within the ACTS project SUNBEAM,1 proposing algorithms and analyzing the feasibility of implementation of innovative and softwarereconfigurable array processing architectures in multistandard settings.Peer Reviewe