3811

3603

كارشناسي ارشد

مخابرات

اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر

1386

نه، 93،[II] ص: مصور، جدول، نمودار

ص.ع. به: فارسي و انگليسي

محمد جواد اميدي

علي محمد دوست حسيني

26/10/86

محمد دخيل عليان، محمد علي خسروي فرد

مهندسي برق و كامپيوتر

ID3603

به فارسي و انگليسي: قابل رويت در نسخه ديجيتال

AbstractNowadays Orthogonal Frequency Division Multiplexing OFDM is used as a popularmethod for high data rate transmission in wireless systems Dividing the wideband fadingchannel to several flat narrowband sub channels OFDM systems have a robustperformance against destructive fading phenomenon of the channel One of the topics discussed in this thesis is wireless channel estimation using Kalmanfiltering Kalman filter can be used to estimate processes from a state space model Channel estimation besides frequency and time synchronization are the two important andeffective issues regarding OFDM systems performance Not only the quality of the channelestimation algorithm affects the communication system s overall performance but also itscomputational complexity is of importance In this thesis the transition matrix of the statespace model is diagonalized by choosing a new basis for the model Then by furthersimplifications we present a method named diagonalized Kalman filter based on theoriginal Kalman filtering method The method presented has lower computationalcomplexity compared to the original method The OFDM signal suffers from large peak variation which is usually represented by thePeak to Average Power Ratio PAPR parameter Signals with large PAPR force the highpower amplifiers to operate with low power efficiency in order to avoid signal clipping Inthis thesis current PAPR reduction methods are introduced These methods are divided intotwo groups of distortion and distortion less techniques A new PAPR reduction method isalso presented in this paper by modifying FFT and IFFT matrices

محمد جواد اميدي

علي محمد دوست حسيني

محمد دخيل عليان، محمد علي خسروي فرد