Fuzzy Logic Control for Multiresolutive Adaptive PN Acquisition Scheme in Time-Varying Multipath Ionospheric Channel

Communication with remote places is a challenge often solved using satellites. However, when trying to reach Antarctic stations, this solution suffers from poor visibility range and high operational costs. In such scenarios, skywave ionospheric communication systems represent a good alternative to satellite communications. The Research Group in Electromagnetism and Communications (GRECO) is designing an HF system for long haul digital communication between the Antarctic Spanish Base in Livingston Island (62.6S, 60.4W) and Observatori de l’Ebre in Spain (40.8N,0.5E) (Vilella et al., 2008). The main interest of Observatori de l’Ebre is the transmission of the data collected from the sensors located at the base, including a geomagnetic sensor, a vertical incidence ionosonde, an oblique incidence ionosonde and a GNSS receiver. The geomagnetic sensor, the vertical incidence ionosonde and the GNSS receiver are commercial solutions from third parties. The oblique incidence ionosonde, used to sound the ionospheric channel between Antarctica and Spain, was developed by the GRECO in the framework of this project. During the last Antarctic campaign, exhaustive measurements of the HF channel characteristics were performed, which allowed us to determine parameters such as availability, SNR, delay and Doppler spread, etc. In addition to the scientific interest of this sounding, a further objective of the project is the establishment of a backup link for data transmission from the remote sensors in the Antarctica. In this scenario, ionospheric communications appear to be an interesting complementary alternative to geostationary satellite communications since the latter are expensive and not always available from high-latitudes. Research work in the field of fuzzy logics applied to the estimation of the above mentioned channel was first applied in (Alsina et al., 2005a) for serial search acquisition systems in AWGN channels, afterwards applied to the same channel but in the multiresolutive structure (Alsina et al., 2009a; Morán et al., 2001) in papers (Alsina et al., 2007b; 2009b) achieving good results. In this chapter the application of fuzzy logic control trained for Rayleigh fading channels (Proakis, 1995) with Direct-Sequence Spread-Spectrum (DS-SS) is presented, specifically suited for the ionospheric channel Antarctica-Spain. Stability and reliability of the reception, which are currently being designed, are key factors for the reception. It is important to note that the fuzzy control design presented in this chapter not only resolves the issue of improving the multiresolutive structure performance presented by (Morán et al., 2001), but also introduces a new option for the control design of many LMS adaptive structures used for PN code acquisition found in the literature. (El-Tarhuni & Sheikh, 1996) presented an LMS-based system to acquire a DS-SS system in Rayleigh channels; years after, (Han et al., 2006) improved the performance of the acquisition system designed by (El-Tarhuni & Sheikh, 1996). And also in other type of channels, LMS filters are used as an acquisition system, even in oceanic transmissions (Stojanovic & Freitag, 2003). Although the fuzzy control system presented in this chapter is compared to the stability control used in (Morán et al., 2001) it also can be used to improve all previous designs performance in terms of stability and robustness. Despite this generalization, the design of every control system should be done according to the requirements of the acquisition system and the specific channel characteristics

A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions

Commercial speech recognizers have made possible many speech control applications such as wheelchair, tone-phone, multifunctional robotic arms and remote controls, for the disabled and paraplegic. However, they have a limitation in common in that recognition errors are likely to be produced when background noise surrounds the spoken command, thereby creating potential dangers for the disabled if recognition errors exist in the control systems. In this paper, a hybrid noise suppression filter is proposed to inter-face with the commercial speech recognizers in order to enhance the recognition accuracy under variant noisy conditions. It intends to decrease the recognition errors when the commercial speech recognizers are working under a noisy environment. It is based on a sigmoid function which can effectively enhance noisy speech using simple computational operations, while a robust estimator based on an adaptive-network-based fuzzy inference system is used to determine the appropriate operational parameters for the sigmoid function in order to produce effective speech enhancement under variant noisy conditions.The proposed hybrid noise suppression filter has the following advantages for commercial speech recognizers: (i) it is not possible to tune the inbuilt parameters on the commercial speech recognizers in order to obtain better accuracy; (ii) existing noise suppression filters are too complicated to be implemented for real-time speech recognition; and (iii) existing sigmoid function based filters can operate only in a single-noisy condition, but not under varying noisy conditions. The performance of the hybrid noise suppression filter was evaluated by interfacing it with a commercial speech recognizer, commonly used in electronic products. Experimental results show that improvement in terms of recognition accuracy and computational time can be achieved by the hybrid noise suppression filter when the commercial recognizer is working under various noisy environments in factories

Blind restoration of images with penalty-based decision making : a consensus approach

In this thesis we show a relationship between fuzzy decision making and image processing . Various applications for image noise reduction with consensus methodology are introduced. A new approach is introduced to deal with non-stationary Gaussian noise and spatial non-stationary noise in MRI

Mecanismos de rede para swarms de drones em ambientes de monitorização aquática

With the development of intelligent platforms for environment sensing, drones present themselves as a fundamental resource capable of responding to the widest range of applications. Monitoring aquatic sensing environments is one such application and the communication between them becomes a key aspect for both navigation and sensing tasks. Testing an aquatic environment with a high number of Unmanned Surface Vehicles (USVs) is very costly, requiring a lot of time and resources. Therefore, simulation platforms become elements of great importance . In this dissertation a simulator is developed containing a modular architecture, based on a delay tolerant network, being capable of simulating aquatic environments as similar as possible to real aquatic environments. In addition to the developed simulator, this dissertation presents methods and strategies of cluster formation, allowing the aquatic drones to select, in a distributed way, the gateways of each cluster that will be responsible for forwarding collected data towards the gateway on land. Two gateway selection methods were implemented, one focused on the energy of aquatic drones, and one considering different metrics such as link quality, centrality and energy. The proposed methods were evaluated across several cases and scenarios, with clusters built and changed in a dynamic way, and it was observed that the election of gateways with a method based on several metrics, together with appropriated control strategy, provides a better outcome of the network behaviour throughout the aquatic monitoring tasks.Com o desenvolvimento de plataformas inteligentes que permitem monitorizar vários ambientes, os drones apresentam-se como um recurso fundamental capaz de responder às mais vastas aplicações. A monitorização de meios aquáticos com recurso a drones é uma destas aplicações e a comunicação entre os mesmos torna-se um aspeto fundamental, tanto em tarefas de navegação como em tarefas de sensorização. Testar um ambiente aquático com um elevado número de drones aquáticos é muito caro, requer muito tempo e vários recursos, por isso, plataformas de simulação tornam-se elementos de grande importância. Nesta dissertação é desenvolvido um simulador, com uma arquitetura modular, tendo por base uma rede tolerante a atrasos, sendo capaz de simular ambientes aquáticos o mais semelhante possível a ambientes aquáticos reais. Para além do simulador desenvolvido, esta dissertação propõe métodos e estratégias de formação de clusters de drones, permitindo que os drones aquáticos elejam, de uma forma distribuída, os gateways de cada cluster que serão responsáveis por encaminhar os dados recolhidos pelos drones em direção à estação em terra. Foram implementados dois métodos de eleição de gateway, um focado na energia dos drones aquáticos, e outro capaz de considerar diferentes métricas, tais como a qualidade de ligação, a centralidade e a energia. Os métodos propostos foram avaliados através de vários cenários em que os clusters são construídos e alterados de forma dinâmica, e foi observado que a escolha de gateways com um método baseado em várias métricas, e juntamente com uma estratégia de controlo apropriada, proporciona um melhor comportamento da rede ao longo das tarefas de monitorização aquática.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Emerging Communications for Wireless Sensor Networks

Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide

Resource Allocation for Coordinated Multipoint Joint Transmission System and Received Signal Strength Based Positioning in Long Term Evolution Network

The Long-Term Evolution Advanced (LTE-A) system are expected to provide high speed and high quality services, which are supported by emerging technologies such as Coordinated Multipoint (CoMP) transmission and reception. Dynamic resource allocation plays a vital role in LTE-A design and planning, which is investigated in this thesis. In addition, Received Signal Strength (RSS) based positioning is also investigated in orthogonal frequency division multiplexing (OFDM) based wireless networks, which is based on an industry project. In the first contribution, a physical resource blocks (PRB) allocation scheme with fuzzy logic based user selection is proposed. This work considers three parameters and exploit a fuzzy logic (FL) based criterion to categorize users. As a result, it enhances accuracy of user classification. This work improves system capacity by a ranking based PRBs allocation schemes. Simulation results show that proposed fuzzy logic based user selection scheme improves performance for CoMP users. Proposed ranking based greedy allocation algorithm cut complexity in half but maintain same performance. In the second contribution, a two-layer proportional-fair (PF) user scheduling scheme is proposed. This work focused on fairness between CoMP and Non-CoMP users instead of balancing fairness in each user categories. Proposed scheme jointly optimizes fairness and system capacity over both CoMP and Non-CoMP users. Simulation results show that proposed algorithm significantly improves fairness between CoMP and Non-CoMP users. In the last contribution, RSS measurement method in LTE system is analyzed and a realizable RSS measurement method is proposed to fight against multipath effect. Simulation results shows that proposed method significantly reduced measurement error caused by multipath. In RSS based positioning area, this is the first work that consider exploiting LTE’s own signal strength measurement mechanism to enhance accuracy of positioning. Furthermore, the proposed method can be deployed in modern LTE system with limited cost

Applications of fuzzy counterpropagation neural networks to non-linear function approximation and background noise elimination

An adaptive filter which can operate in an unknown environment by performing a learning mechanism that is suitable for the speech enhancement process. This research develops a novel ANN model which incorporates the fuzzy set approach and which can perform a non-linear function approximation. The model is used as the basic structure of an adaptive filter. The learning capability of ANN is expected to be able to reduce the development time and cost of the designing adaptive filters based on fuzzy set approach. A combination of both techniques may result in a learnable system that can tackle the vagueness problem of a changing environment where the adaptive filter operates. This proposed model is called Fuzzy Counterpropagation Network (Fuzzy CPN). It has fast learning capability and self-growing structure. This model is applied to non-linear function approximation, chaotic time series prediction and background noise elimination

Development of Fuzzy Receiver for GSM Application

A channel equalizer is one of the most important subsystems in any cellular communication receiver. It is also the subsystem that consumes maximum computation time in the receiver. Traditionally maximum-likelihood sequence estimation (MLSE) was the most popular form of equalizer. Owing to non-stationary characteristics of the communication channel MLSE receivers perform poorly. Under these circumstances maximum-aposteriori probability (MAP) receivers also called Bayesian receivers perform better. This thesis proposes a fuzzy receiver that implements MAP equalizer and provides a performance close to the optimal Bayesian receiver. Here Bit Error Rate (BER) has been used as the performance index. This thesis presents an investigation on design of fuzzy based receivers for GSM application. Extensive simulation studies which shows that the performance of the proposed receiver is close to optimal receiver for variety of channel conditions in different receiver speeds where channel suffers from Rayleigh fading. The proposed receiver also provides near optimal performance when channel suffers from nonlinearities