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On Channel Estimation of OFDM-BPSK and -QPSK over Generalized Alpha-Mu Fading Distribution

On Channel Estimation of OFDM-BPSK and -QPSK over Generalized Alpha-Mu Fading Distribution
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摘要 This paper evaluates the performance of OFDM-BPSK and -QPSK system in α-μ distribution. A fading model which is based on the non-linearity present in the propagation medium is utilized here for generation of α-μ variants. Different combinations of α and μ provides various fading distributions, one of which is Weibull fading. Investigations of channel estimation schemes gave an idea of further reducing the BER as to improve the performance of OFDM based systems. In flat fading environment, channel estimation is done using phase estimation of the transmitted signal with the help of trained symbols. Final results show the improvement in BER. However, the amount of results improved depends upon the amount of trained symbols. The more trained symbols will result into more improved BER. This paper evaluates the performance of OFDM-BPSK and -QPSK system in α-μ distribution. A fading model which is based on the non-linearity present in the propagation medium is utilized here for generation of α-μ variants. Different combinations of α and μ provides various fading distributions, one of which is Weibull fading. Investigations of channel estimation schemes gave an idea of further reducing the BER as to improve the performance of OFDM based systems. In flat fading environment, channel estimation is done using phase estimation of the transmitted signal with the help of trained symbols. Final results show the improvement in BER. However, the amount of results improved depends upon the amount of trained symbols. The more trained symbols will result into more improved BER.
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出处 《International Journal of Communications, Network and System Sciences》 2010年第4期380-384,共5页 通讯、网络与系统学国际期刊(英文)
关键词 OFDM FADING DISTRIBUTION Weibull FADING NAKAGAMI FADING Channel Estimation Training Symbols OFDM Fading Distribution Weibull Fading Nakagami Fading Channel Estimation Training Symbols
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