Mansour A. Aldajani 2001

Abstract of PhD Dissertation
Electrical Engineering Department, UCLA, September 2001
Advisor: Prof. Ali H. Sayed

Adaptive Techniques for Data Conversion and Coding with Application to Power Control in CDMA Wireless Systems

Mansour A. Aldajani, UCLA

Digital communication systems transmit information in digital form. In TV and radio broadcasting, for example, the source of information is analog. Therefore, the information would need to be transformed into digital form in order to be suitable for transmission or storage. This process is performed by analog source encoding. Such source encoders achieve high transmission efficiency by decreasing the bit rate needed to represent the information while maintaining acceptable accuracy and robustness against channel distortions.

Existing source encoders can suffer from limited SNR and dynamic range performance. This dissertation develops a variety of structures for adaptive delta and sigma delta modulators that address these difficulties. This is achieved by introducing a new scheme for adapting the step size of the one-bit quantizer in the modulation loop. In order to get further performance improvement, these systems are extended to the multi-bit case, where multi-bit quantizers are employed. It is shown that the resulting systems maintain the same attractive properties as the single-bit case, namely, improved SNR and superior dynamic range. All systems are analyzed both analytically and by simulations.

The ideas developed for delta and sigma delta modulation turn out to be relevant for power control schemes in wireless communications. As is well-known, the requirement of power control in the uplink channel of a DS-CDMA system is a critical limitation. Power control is needed because all users share the same bandwidth to transmit data and thus inter-users interference will occur. The delta modulation-like behavior of closed-loop power control, however, makes it suffer from slow tracking in the presence of fast and deep fading of the wireless channel condition. This dissertation analyzes the causes of such limited performance and develops several algorithms to compensate for these causes. The resulting schemes show improved power control performance.

Acknowledgment This work was supported in part by the National Science Foundation under grant CCR-0208573. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.