33 research outputs found

    Artificial neural networks for location estimation and co-cannel interference suppression in cellular networks

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    This thesis reports on the application of artificial neural networks to two important problems encountered in cellular communications, namely, location estimation and co-channel interference suppression. The prediction of a mobile location using propagation path loss (signal strength) is a very difficult and complex task. Several techniques have been proposed recently mostly based on linearized, geometrical and maximum likelihood methods. An alternative approach based on artificial neural networks is proposed in this thesis which offers the advantages of increased flexibility to adapt to different environments and high speed parallel processing. Location estimation provides users of cellular telephones with information about their location. Some of the existing location estimation techniques such as those used in GPS satellite navigation systems require non-standard features, either from the cellular phone or the cellular network. However, it is possible to use the existing GSM technology for location estimation by taking advantage of the signals transmitted between the phone and the network. This thesis proposes the application of neural networks to predict the location coordinates from signal strength data. New multi-layered perceptron and radial basis function based neural networks are employed for the prediction of mobile locations using signal strength measurements in a simulated COST-231 metropolitan environment. In addition, initial preliminary results using limited available real signal-strength measurements in a metropolitan environment are also reported comparing the performance of the neural predictors with a conventional linear technique. The results indicate that the neural predictors can be trained to provide a near perfect mapping using signal strength measurements from two or more base stations. The second application of neural networks addressed in this thesis, is concerned with adaptive equalization, which is known to be an important technique for combating distortion and Inter-Symbol Interference (ISI) in digital communication channels. However, many communication systems are also impaired by what is known as co-channel interference (CCI). Many digital communications systems such as digital cellular radio (DCR) and dual polarized micro-wave radio, for example, employ frequency re-usage and often exhibit performance limitation due to co-channel interference. The degradation in performance due to CCI is more severe than due to ISI. Therefore, simple and effective interference suppression techniques are required to mitigate the interference for a high-quality signal reception. The current work briefly reviews the application of neural network based non-linear adaptive equalizers to the problem of combating co-channel interference, without a priori knowledge of the channel or co-channel orders. A realistic co-channel system is used as a case study to demonstrate the superior equalization capability of the functional-link neural network based Decision Feedback Equalizer (DFE) compared to other conventional linear and neural network based non-linear adaptive equalizers.This project was funded by Solectron (Scotland) Ltd

    Turbo- and BCH-coded wide-band burst-by-burst adaptive H.263-assisted wireless video telephony

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    Mobile and Wireless Communications

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    Mobile and Wireless Communications have been one of the major revolutions of the late twentieth century. We are witnessing a very fast growth in these technologies where mobile and wireless communications have become so ubiquitous in our society and indispensable for our daily lives. The relentless demand for higher data rates with better quality of services to comply with state-of-the art applications has revolutionized the wireless communication field and led to the emergence of new technologies such as Bluetooth, WiFi, Wimax, Ultra wideband, OFDMA. Moreover, the market tendency confirms that this revolution is not ready to stop in the foreseen future. Mobile and wireless communications applications cover diverse areas including entertainment, industrialist, biomedical, medicine, safety and security, and others, which definitely are improving our daily life. Wireless communication network is a multidisciplinary field addressing different aspects raging from theoretical analysis, system architecture design, and hardware and software implementations. While different new applications are requiring higher data rates and better quality of service and prolonging the mobile battery life, new development and advanced research studies and systems and circuits designs are necessary to keep pace with the market requirements. This book covers the most advanced research and development topics in mobile and wireless communication networks. It is divided into two parts with a total of thirty-four stand-alone chapters covering various areas of wireless communications of special topics including: physical layer and network layer, access methods and scheduling, techniques and technologies, antenna and amplifier design, integrated circuit design, applications and systems. These chapters present advanced novel and cutting-edge results and development related to wireless communication offering the readers the opportunity to enrich their knowledge in specific topics as well as to explore the whole field of rapidly emerging mobile and wireless networks. We hope that this book will be useful for students, researchers and practitioners in their research studies

    Wavelet-Coding for Radio over Fibre

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    Interference Mitigation in Wireless Communications

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    The primary objective of this thesis is to design advanced interference resilient schemes for asynchronous slow frequency hopping wireless personal area networks (FH-WPAN) and time division multiple access (TDMA) cellular systems in interference dominant environments. We also propose an interference-resilient power allocation method for multiple-input-multiple-output (MIMO) systems. For asynchronous FH-WPANs in the presence of frequent packet collisions, we propose a single antenna interference canceling dual decision feedback (IC-DDF) receiver based on joint maximum likelihood (ML) detection and recursive least squares (RLS) channel estimation. For the system level performance evaluation, we propose a novel geometric method that combines bit error rate (BER) and the spatial distribution of the traffic load of CCI for the computation of packet error rate (PER). We also derived the probabilities of packet collision in multiple asynchronous FH-WPANs with uniform and nonuniform traffic patterns. For the design of TDMA receivers resilient to CCI in frequency selective channels, we propose a soft output joint detection interference rejection combining delayed decision feedback sequence estimation (JD IRC-DDFSE) scheme. In the proposed scheme, IRC suppresses the CCI, while DDFSE equalizes ISI with reduced complexity. Also, the soft outputs are generated from IRC-DDFSE decision metric to improve the performance of iterative or non-iterative type soft-input outer code decoders. For the design of interference resilient power allocation scheme in MIMO systems, we investigate an adaptive power allocation method using subset antenna transmission (SAT) techniques. Motivated by the observation of capacity imbalance among the multiple parallel sub-channels, the SAT method achieves high spectral efficiency by allocating power on a selected transmit antenna subset. For 4 x 4 V-BLAST MIMO systems, the proposed scheme with SAT showed analogous results. Adaptive modulation schemes combined with the proposed method increase the capacity gains. From a feasibility viewpoint, the proposed method is a practical solution to CCI-limited MIMO systems since it does not require the channel state information (CSI) of CCI.Ph.D.Committee Chair: Professor Gordon L. StBe
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