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Channel-state-assisted convolutional decoding for single-input single-output IEEE 802.11n systems

Sourla Martha-Vasiliki

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Summary

This thesis is on the implementation and simulation of single-inputsingle-output IEEE 802.11n links and the examination ofchannel-state-assisted convolutional decoding to improve systemperformance. We present the full chain of transformations of the signalat the transmitter, according to the IEEE 802.11n standard, and explainthe role of each module. We also explain the corresponding receivermodules. At each step, we present the parameters of the code that isused to implement each module and describe their use. Then, we focus onsingle-input single-output systems that employ convolutional coding. Wederive closed-form approximations for the log-likelihood ratio (LLR) ofthe coded bits at the receiver end and, taking into account the specificsignal constellation determined by the IEEE 802.11n standard, we showthat, for any modulation and coding rate of the standard, the sequenceof LLRs that is given as input to the channel decoder can be viewed as asequence of received samples of binary phase-shift keying symbols inadditive-white-Gaussian-noise with varying, but known, bit amplitude.The amplitude variation is due to the different channel state overdifferent subcarriers. Then, we implement a channel decoding algorithmthat is tailored to the derived LLR expressions, simulate the systemperformance over IEEE TGn Model-B channels, and compare with plainLLR-based decoding that does not incorporate the varying channel state.

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