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Kalman Filtering Approach to Optimize OFDM Data Rate

Description: This study is based on applying a non-linear mapping method, here the unscented Kalman filter; to estimate and optimize data rate resulting from the arrival rate having a Poisson distribution in an orthogonal frequency division multiplexing (OFDM) transmission system. OFDM is an emerging multi-carrier modulation scheme. With the growing need for quality of service in wireless communications, it is highly necessary to optimize resources in such a way that the overall performance of the system models should rise while keeping in mind the objective to achieve high data rate and efficient spectral methods in the near future. In this study, the results from the OFDM-TDMA transmission system have been used to apply cross-layer optimization between layers so as to treat different resources between layers simultaneously. The main controller manages the transmission of data between layers using the multicarrier modulation techniques. The unscented Kalman filter is used here to perform nonlinear mapping by estimating and optimizing the data rate, which result from the arrival rate having a Poisson distribution.
Date: August 2011
Creator: Wunnava, Sashi Prabha
Partner: UNT Libraries

Study of the effects of background and motion camera on the efficacy of Kalman and particle filter algorithms.

Description: This study compares independent use of two known algorithms (Kalmar filter with background subtraction and Particle Filter) that are commonly deployed in object tracking applications. Object tracking in general is very challenging; it presents numerous problems that need to be addressed by the application in order to facilitate its successful deployment. Such problems range from abrupt object motion, during tracking, to a change in appearance of the scene and the object, as well as object to scene occlusions, and camera motion among others. It is important to take into consideration some issues, such as, accounting for noise associated with the image in question, ability to predict to an acceptable statistical accuracy, the position of the object at a particular time given its current position. This study tackles some of the issues raised above prior to addressing how the use of either of the aforementioned algorithm, minimize or in some cases eliminate the negative effects
Date: August 2009
Creator: Morita, Yasuhiro
Partner: UNT Libraries

Baseband Noise Suppression in Ofdm Using Kalman Filter

Description: As the technology is advances the reduced size of hardware gives rise to an additive 1/f baseband noise. This additive 1/f noise is a system noise generated due to miniaturization of hardware and affects the lower frequencies. Though 1/f noise does not show much effect in wide band channels because of its nature to affect only certain frequencies, 1/f noise becomes a prominent in OFDM communication systems where narrow band channels are used. in this thesis, I study the effects of 1/f noise on the OFDM systems and implement algorithms for estimation and suppression of the noise using Kalman filter. Suppression of the noise is achieved by subtracting the estimated noise from the received noise. I show that the performance of the system is considerably improved by applying the 1/f noise suppression.
Date: May 2012
Creator: Rodda, Lasya
Partner: UNT Libraries