1,088 research outputs found

    Communication Subsystems for Emerging Wireless Technologies

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    The paper describes a multi-disciplinary design of modern communication systems. The design starts with the analysis of a system in order to define requirements on its individual components. The design exploits proper models of communication channels to adapt the systems to expected transmission conditions. Input filtering of signals both in the frequency domain and in the spatial domain is ensured by a properly designed antenna. Further signal processing (amplification and further filtering) is done by electronics circuits. Finally, signal processing techniques are applied to yield information about current properties of frequency spectrum and to distribute the transmission over free subcarrier channels

    Multiple-antenna-aided OFDM employing genetic-algorithm-assisted minimum bit error rate multiuser detection

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    The family of minimum bit error rate (MBER) multiuser detectors (MUD) is capable of outperforming the classic minimum mean-squared error (MMSE) MUD in terms of the achievable bit-error rate (BER) owing to directly minimizing the BER cost function. In this paper,wewill invoke genetic algorithms (GAs) for finding the optimum weight vectors of the MBER MUD in the context of multiple-antenna-aided multiuser orthogonal frequency division multiplexing (OFDM) .We will also show that the MBER MUD is capable of supporting more users than the number of receiver antennas available, while outperforming the MMSE MUD

    Recent Trends in Communication Networks

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    In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

    Intelligent genetic algorithms for next-generation broadband multi-carrier CDMA wireless networks

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    This dissertation proposes a novel intelligent system architecture for next-generation broadband multi-carrier CDMA wireless networks. In our system, two novel and similar intelligent genetic algorithms, namely Minimum Distance guided GAs (MDGAs) are invented for both peak-to-average power ratio (PAPR) reduction at the transmitter side and multi-user detection (MUD) at the receiver side. Meanwhile, we derive a theoretical BER performance analysis for the proposed MC-CDMA system in A WGN channel. Our analytical results show that the theoretical BER performance of synchronized MC-CDMA system is the same as that of the synchronized DS-CDMA system which is also used as a theoretical guidance of our novel MUD receiver design. In contrast to traditional GAs, our MDGAs start with a balanced ratio of exploration and exploitation which is maintained throughout the process. In our algorithms, a new replacement strategy is designed which increases significantly the convergence rate and reduces dramatically computational complexity as compared to the conventional GAs. The simulation results demonstrate that, if compared to those schemes using exhaustive search and traditional GAs, (1) our MDGA-based P APR reduction scheme achieves 99.52% and 50+% reductions in computational complexity, respectively; (2) our MDGA-based MUD scheme achieves 99.54% and 50+% reductions in computational complexity, respectively. The use of one core MDGA solution for both issues can ease the hardware design and dramatically reduce the implementation cost in practice.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    A Tutorial on Clique Problems in Communications and Signal Processing

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    Since its first use by Euler on the problem of the seven bridges of K\"onigsberg, graph theory has shown excellent abilities in solving and unveiling the properties of multiple discrete optimization problems. The study of the structure of some integer programs reveals equivalence with graph theory problems making a large body of the literature readily available for solving and characterizing the complexity of these problems. This tutorial presents a framework for utilizing a particular graph theory problem, known as the clique problem, for solving communications and signal processing problems. In particular, the paper aims to illustrate the structural properties of integer programs that can be formulated as clique problems through multiple examples in communications and signal processing. To that end, the first part of the tutorial provides various optimal and heuristic solutions for the maximum clique, maximum weight clique, and kk-clique problems. The tutorial, further, illustrates the use of the clique formulation through numerous contemporary examples in communications and signal processing, mainly in maximum access for non-orthogonal multiple access networks, throughput maximization using index and instantly decodable network coding, collision-free radio frequency identification networks, and resource allocation in cloud-radio access networks. Finally, the tutorial sheds light on the recent advances of such applications, and provides technical insights on ways of dealing with mixed discrete-continuous optimization problems
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