Spelling suggestions: "subject:"additive gaussian noise"" "subject:"additive gaussian boise""
1 |
A virtual RSNS direction finding antenna systemChen, Jui-Chun 12 1900 (has links)
Approved for public release; distribution in unlimited. / In this thesis, a performance analysis and improvement of a phase sampling interferometer antenna system based on the Robust Symmetrical Number System (RSNS) in the presence of noise is investigated. Previous works have shown that the RSNS-based DF technique can provide high bearing resolution with a minimum number of antenna elements. However, the previous experimental data showed significant deviation from the theoretical results expected due to imperfections, errors, and noise. Therefore, an additive Gaussian noise model of RSNS-based DF was established and simulated. Simulation results show that the presence of noise distorts the signal amplitudes used in the RSNS processor and causes degradation of the angle-ofarrival estimates. A performance analysis was undertaken by first introducing the quadrature modulation configuration into RSNS-based DF system, which provided a digital antenna approach for more flexibility in the signal processing. With a digital approach, variable resolution signal preprocessing can be employed, using a virtual channel concept. The virtual channel concept changes moduli values without changing the actual physical antenna element spacing. This attractive property allows the RSNS algorithm to be implemented into existing antenna arrays and only requires modifying the antenna signal processor. Computer simulation results showed that the proposed method can successfully improve the system performance and also mitigate the effects of noise. / Captain, Taiwan Army
|
2 |
Modelling of Mobile Fading Channels with Fading Mitigation Techniques.Shang, Lei, lei.shang@ieee.org January 2006 (has links)
This thesis aims to contribute to the developments of wireless communication systems. The work generally consists of three parts: the first part is a discussion on general digital communication systems, the second part focuses on wireless channel modelling and fading mitigation techniques, and in the third part we discuss the possible application of advanced digital signal processing, especially time-frequency representation and blind source separation, to wireless communication systems. The first part considers general digital communication systems which will be incorporated in later parts. Today's wireless communication system is a subbranch of a general digital communication system that employs various techniques of A/D (Analog to Digital) conversion, source coding, error correction, coding, modulation, and synchronization, signal detection in noise, channel estimation, and equalization. We study and develop the digital communication algorithms to enhance the performance of wireless communication systems. In the Second Part we focus on wireless channel modelling and fading mitigation techniques. A modified Jakes' method is developed for Rayleigh fading channels. We investigate the level-crossing rate (LCR), the average duration of fades (ADF), the probability density function (PDF), the cumulative distribution function (CDF) and the autocorrelation functions (ACF) of this model. The simulated results are verified against the analytical Clarke's channel model. We also construct frequency-selective geometrical-based hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment with the proper statistical characteristics. The modified Clarke's model and the GBHDS model may be readily expanded to a MIMO channel model thus we study the MIMO fading channel, specifically we model the MIMO channel in the angular domain. A detailed analysis of Gauss-Markov approximation of the fading channel is also given. Two fading mitigation techniques are investigated: Orthogonal Frequency Division Multiplexing (OFDM) and spatial diversity. In the Third Part, we devote ourselves to the exciting fields of Time-Frequency Analysis and Blind Source Separation and investigate the application of these powerful Digital Signal Processing (DSP) tools to improve the performance of wireless communication systems.
|
Page generated in 0.0657 seconds