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

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.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

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

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

Intelligent Processing in Wireless Communications Using Particle Swarm Based Methods

There are a lot of optimization needs in the research and design of wireless communica- tion systems. Many of these optimization problems are Nondeterministic Polynomial (NP) hard problems and could not be solved well. Many of other non-NP-hard optimization problems are combinatorial and do not have satisfying solutions either. This dissertation presents a series of Particle Swarm Optimization (PSO) based search and optimization algorithms that solve open research and design problems in wireless communications. These problems are either avoided or solved approximately before. PSO is a bottom-up approach for optimization problems. It imposes no conditions on the underlying problem. Its simple formulation makes it easy to implement, apply, extend and hybridize. The algorithm uses simple operators like adders, and multipliers to travel through the search space and the process requires just five simple steps. PSO is also easy to control because it has limited number of parameters and is less sensitive to parameters than other swarm intelligence algorithms. It is not dependent on initial points and converges very fast. Four types of PSO based approaches are proposed targeting four different kinds of problems in wireless communications. First, we use binary PSO and continuous PSO together to find optimal compositions of Gaussian derivative pulses to form several UWB pulses that not only comply with the FCC spectrum mask, but also best exploit the avail- able spectrum and power. Second, three different PSO based algorithms are developed to solve the NLOS/LOS channel differentiation, NLOS range error mitigation and multilateration problems respectively. Third, a PSO based search method is proposed to find optimal orthogonal code sets to reduce the inter carrier interference effects in an frequency redundant OFDM system. Fourth, a PSO based phase optimization technique is proposed in reducing the PAPR of an frequency redundant OFDM system. The PSO based approaches are compared with other canonical solutions for these communication problems and showed superior performance in many aspects. which are confirmed by analysis and simulation results provided respectively. Open questions and future Open questions and future works for the dissertation are proposed to serve as a guide for the future research efforts

Técnicas de igualização adaptativas com estimativas imperfeitas do canal para os futuros sistemas 5G

Wireless communication networks have been continuously experiencing an exponential growth since their inception. The overwhelming demand for high data rates, support of a large number of users while mitigating disruptive interference are the constant research focus and it has led to the creation of new technologies and efficient techniques. Orthogonal frequency division multiplexing (OFDM) is the most common example of a technology that has come to the fore in this past decade as it provided a simple and generally ideal platform for wireless data transmission. It’s drawback of a rather high peak-to-average power ratio (PAPR) and sensitivity to phase noise, which in turn led to the adoption of alternative techniques, such as the single carrier systems with frequency domain equalization (SC-FDE) or the multi carrier systems with code division multiple access (MC-CDMA), but the nonlinear Frequency Domain Equalizers (FDE) have been of special note due to their improved performance. From these, the Iterative Block Decision Feedback Equalizer (IB-DFE) has proven itself especially promising due to its compatibility with space diversity, MIMO systems and CDMA schemes. However, the IB-DFE requires the system to have constant knowledge of the communication channel properties, that is, to have constantly perfect Channel State Information (CSI), which is both unrealistic and impractical to implement. In this dissertation we shall design an altered IB-DFE receiver that is able to properly detect signals from SC-FDMA based transmitters, even with constantly erroneous channel states. The results shall demonstrate that the proposed equalization scheme is robust to imperfect CSI (I-CSI) situations, since its performance is constantly close to the perfect CSI case, within just a few iterations.Redes sem fios têm crescido de maneira contínua e exponencial desde a sua incepção. A tremenda exigência para altas taxas de dados e o suporte para um elevado número de utilizadores sem aumentar a interferência disruptiva originada por estes são alguns dos focos que levaram ao desenvolvimento de técnicas de compensação e novas tecnologias. “Orthogonal frequency division multiplexing” (OFDM) é um dos exemplos de tecnologias que se destacaram nesta última década, visto ter fornecido uma plataforma para transmissão de dados sem-fio eficaz e simples. O seu maior problema é a alta “peak-to-average power ratio” (PAPR) e a sua sensibilidade a ruído de fase que deram motivo à adoção de técnicas alternativas, tais como os sistemas “single carrier” com “frequency domain equalization” (SC-FDE) ou os sistemas “multi-carrier” com “code division multiple access” (MC-CDMA), mas equalizadores não lineares no domínio de frequência têm sido alvo de especial atenção devido ao seu melhor desempenho. Destes, o “iterative block decision feedback equalizer” (IB-DFE) tem-se provado especialmente promissor devido à sua compatibilidade com técnicas de diversidade no espaço, sistemas MIMO e esquemas CDMA. No entanto, IB-DFE requer que o sistema tenha constante conhecimento das propriedades dos canais usados, ou seja, necessita de ter perfeito “channel state information” (CSI) constantemente, o que é tanto irrealista como impossível de implementar. Nesta dissertação iremos projetar um recetor IB-DFE alterado de forma a conseguir detetar sinais dum transmissor baseado em tecnologia SC-FDMA, mesmo com a informação de estado de canal errada. Os resultados irão então demonstrar que o novo esquema de equalização proposto é robusto para situações de CSI imperfeito (I-CSI), visto que o seu desempenho se mantém próximo dos valores esperados para CSI perfeito, em apenas algumas iterações.Mestrado em Engenharia Eletrónica e Telecomunicaçõe