Adaptive bit allocation with reduced feedback for wireless multicarrier transceivers
Issue Date
2007-12-31Author
Tadikonda, Udaya Kiran
Publisher
University of Kansas
Type
Thesis
Degree Level
M.S.
Discipline
Electrical Engineering & Computer Science
Rights
This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
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Show full item recordAbstract
With the increasing demand in the wireless mobile applications came a growing need to transmit information quickly and accurately, while consuming more and more bandwidth. To address this need, communication engineers started employing multicarrier modulation in their designs, which is suitable for high data rate transmission. Multicarrier modulation reduces the system's susceptibility to the frequency-selective fading channel, by transforming it into a collection of approximately flat subchannels. As a result, this makes it easier to compensate for the distortion introduced by the channel. This thesis concentrates on techniques for saving bandwidth usage when employing adaptive multicarrier modulation, where subcarrier parameters (bit and energy allocations) are modulated based on the channel state information feedback obtained from previous burst.Although bit and energy allocations can substantially increase error robustness and throughput of the system, the feedback information required at both ends of the transceiver can be large. The objective of this work is to compare different feedback compression techniques that could reduce the amount of feedback information required to perform adaptive bit and energy allocation in multicarrier transceivers.This thesis employs an approach for reducing the number of feedback transmissions by exploiting the time-correlation properties of a wireless channel and placing a threshold check on bit error rate (BER) values. Using quantization and source coding techniques, such as Huffman coding, Run length encoding and LZW algorithms, the amount of feedback information has been compressed. These calculations have been done for different quantization levels to understand the relationship between quantization levels and system performance. These techniques have been applied to both OFDM and MIMO-OFDM systems.
Description
Thesis (M.S.)--University of Kansas, Electrical Engineering & Computer Science, 2007.
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- Theses [3768]
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