Type of Document Master's Thesis Author Agashe, Parag URN etd-11182008-063200 Title Selective cancellation of interference for CDMA Degree Master of Science Department Electrical Engineering Advisory Committee
Advisor Name Title Jacobs, Ira Committee Chair Woerner, Brian D. Committee Chair Rappaport, Theodore S. Committee Member Keywords
- Multiple Access Interference
Date of Defense 1996-01-11 Availability restricted Abstract
Recently, it has been shown that Multiple Access Interference (MAl) cancellation is a promising technique for improving the performance and capacity of the reverse link in a Code Division Multiple Access (CDMA) cellular system. However, it has beep observed that indiscriminate cancellation of all received signals can degrade performance. This thesis explores the use of selective cancellation to improve the performance of practical CDMA systems. First, this thesis considers the performance of adaptive interference cancellation applied to a CDMA micro cellular environment. This thesis employs a circular geometry and a closed form expression for the Bit Error Rate of a CDMA system with interference cancellation to analyze the effect of out-of-cell interference. Results are presented which indicate that out-of-cell interference will severely limit the benefits of interference cancellation in a multicellular system. Attempts to cancel all out-of-cell interference will further degrade performance. However, the use of selective interference cancellation in which only the strongest out-of-cell interferers are cancelled may result in significant performance enhancement. These results are shown to agree closely with those obtained using a hexagonal geometry. The MAl is modeled using both the simple and an improved Gaussian approximation.
This thesis also investigates the use of selective cancellation with bit averaging. Amplitude estimates over several consecutive symbols can be averaged to improve the accuracy of the estimate. An expression for the BER of the interference cancellation receiver with hard decisions is developed. Results show that averaging power estimates leads to considerable improvement in capacity. Results are also presented for the case of perfect power estimates.
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