CAREER: A Unifying Signal Processing Framework for Estimating Statistical Channel Quality Measures In Wireless Communications

Arizona State University, Scottsdale AZ

Investigators

Abstract

0133841 Tepedelenlioglu, Cihan Arizona State University In wireless broadband communications, the distortion that the communication medium (`the channel') causes on the transmitted signal, warrants accurate channel models in order to characterize and mitigate the distortion. These models need to take into account the mobility of the transmitter and receiver, the possible presence of a line-of-sight between the communicators, and the presence of noise and interference, all of which are parameters that quantify the channel quality, and affect the performance of the communication system. It is, therefore, of interest to construct such models, and use these models to estimate these statistical channel quality measures. It is the goal of this research to construct and utilize a signal processing framework to estimate these channel quality measures, which is expected to aid in the design of broadband systems with improved performance. More specifically, in the course of this research, the PI will construct optimal (maximum likelihood and minimum variance) as well as moment-based estimators for channel quality indicators such as the maximum Doppler spread, signal to interference plus noise ratio, and the Ricean factor for broadband systems such as OFDM. After characterizing the deleterious effects of the time-selective and frequency-selective channel on general block transmission systems, for which OFDM is a special case, the PI will devise generalized OFDM transceivers that reduce the adverse effects of the inter-carrier interference. Hence, the research will focus on the adverse effects of the randomly time-varying channel on broadband systems and propose novel, low-complexity remedies.