International Journal of Scientific and Research Publications, Volume 5, Issue 7, July 2015 1 ISSN 2250-3153 www.ijsrp.org Performance Improvement of Intelligent Weather System for Satellite Networks Amruta Chavan 1 , R.D.Patane 2 1 STUDENT, M.E (ELECTRONICS AND TELECOMMUNICATION) 2 PROFESSOR, TERNA ENGINEERING COLLEGE, NERUL, NAVI MUMBAI Email: - 1 amrutac79@gmail.com, 2 rrpatane@yahoo.co.in Abstract- In high frequency satellite systems prediction of channel characteristics can be of immense value in improving the quality of signals. Signal attenuation impacts QoS in wireless and satellite networks. An intelligent decision support system is therefore necessary for service providers by accurately calculating cloud, fog, rain, gaseous, and scintillation attenuations using predicted signal-weather correlated database in collaboration with ITU-R propagation models combined with gateway, and ground terminal characteristics. The effect becomes a key feature in adjusting and improving satellite signal power, modulation and coding schemes, monitored and controlled altogether by a powerful and efficient intelligent-based attenuation countermeasure system. Weather attenuations can have a distorting effect on signal fidelity at higher frequencies that lead to excessive digital transmission error. This loss of signal is commonly referred to as signal attenuation. Signal attenuation impacts QoS (Quality Of service) in wireless and satellite networks. An intelligent decision support system is therefore necessary for service providers by accurately calculating the attenuations [1]-[5]. In this project we are calculating rain attenuation. The fuzzy logic is added into the system. The fuzzy system will determine the ambiguous signal during the attenuation performed. Index Terms - Intelligent system, Rain attenuation, fuzzy logic, Ku-Band satellite. 1. INTRODUCTION Rain attenuation (RA) is major source of impairment to signal propagation at microwave and millimeter wavebands. These impairments become particularly severe at high frequencies, especially above Ku band. As such, it is extremely hard to optimally manage satellite dependent network resources that are impacted by weather attenuations. Thus, the need arises to properly predict significant attenuation factors that affect quality of service (QoS) [1]. To improve receive signal over satellite communications in DVB-S, We propose the fuzzy logic to deploy over the system. Rain attenuation is a dominant source of attenuation over Ku- band satellite communication. Because of the frequency of Ku- band was affected in rhythm of rain attenuation. In case of both of them are synchronized, the signal will loss or attenuated. This is vital problem to occur in Ku-band where high frequency is deployed [3]. We use ITU-R model to accurately compute rain attenuations as a function of both propagation angle and rainfall rate. This data controlled by the intelligent system via a Fuzzy Logic decision mechanism, provide a better estimate satellite networking parameters such as link and queuing characteristics. The derived parameters would enable the IS(intelligent systems) to maintain QoS and SLAs(service level agreements). In view of these analytical approaches, dealing with weather-impacted QoS and reliable satellite communications are currently non-existent. Other thrusts in satellite service providers are shifting their resolution towards intelligent- based prediction methods. These types of methods accurately predict relevant atmospheric metrics by adaptively applying the prediction methods to regulate transmit power, transmission rate, modulation schemes and channel coding[4]. Consequently, these methods will promptly adjust to new signal changes through the inter-connected network entities, before attenuation problems actually manifest themselves, to maintain end-to-end QoS requirements. The remaining section of the paper are as follows: In section 2 we describe fuzzy logic based unit followed by fuzzy variables, membership function and defuzzification process. In section 3 signal to noise ratio modification is presented. Finally, conclusion is outlined in section 4. 1.2. Problem Defination Rain is a dominant source of attenuation for Satellite networks over higher frequency bands. The signals should be properly received and transmitted with attenuation or not. If SNR is better , we will assume the quality of signal as better. In term of QoS, end user must get quality signal from transmission link weather rain attenuation or clear sky. Service must be strength and quality of signal must be maintained. In order to achieve this, we proposed a good process which can resolve the problem of rain attenuation by applying fuzzy logic inside the exiting Intelligent system. 2. FUZZY-LOGIC-BASED UNIT Fuzzy logic is a conceptualized as a generalization of classical logic and a mathematical theory, which encompasses the idea of vagueness when defining a meaning. For example, there is uncertainty are ‘fuzziness’ in expressions like ‘tall’ or ‘short’ , since these expressions are imprecise and relative. Variables considered thus are termed ‘fuzzy.’ Fuzziness is simple one means of describing uncertainty. The objective of every receive signal utility is to operate at correct receive bit signal from source. It use fuzzy logic to solve problem.