Title:
Low-power discrete Fourier transform and soft-decision Viterbi decoder for OFDM receivers
Low-power discrete Fourier transform and soft-decision Viterbi decoder for OFDM receivers
Author(s)
Suh, Sangwook
Advisor(s)
Barry, John R.
Hasler, Jennifer
Hasler, Jennifer
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Abstract
The purpose of this research is to present a low-power wireless communication receiver with an enhanced performance by relieving the system complexity and performance degradation imposed by a quantization process. With an overwhelming demand for more reliable communication systems, the complexity required for modern communication systems has been increased accordingly. A byproduct of this increase in complexity is a commensurate increase in power consumption of the systems. Since the Shannon's era, the main stream of the methodologies for promising the high reliability of communication systems has been based on the principle that the information signals flowing through the system are represented in digits. Consequently, the system itself has been heavily driven to be implemented with digital circuits, which is generally beneficial over analog implementations when digitally stored information is locally accessible, such as in memory systems. However, in communication systems, a receiver does not have a direct access to the originally transmitted information. Since the received signals from a noisy channel are already continuous values with continuous probability distributions, we suggest a mixed-signal system in which the received continuous signals are directly fed into the analog demodulator and the subsequent soft-decision Viterbi decoder without any quantization involved. In this way, we claim that redundant system complexity caused by the quantization process is eliminated, thus gives better power efficiency in wireless communication systems, especially for battery-powered mobile devices. This is also beneficial from a performance perspective, as it takes full advantage of the soft information flowing through the system.
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Date Issued
2011-08-31
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Text
Resource Subtype
Dissertation