Channel estimation in time domain using complementary sequence
Shufeng Li, Hongda Wu, Libiao Jin
Abstract
Shufeng Li, Hongda Wu, Libiao Jin
Abstract
It is indispensable to take a low complexity and high accuracy channel estimation algorithm into account under rapidly growth in wireless communication. In this paper, we propose an algorithm for channel estimation using complementary sequence (CS). By utilizing the fantastic autocorrelation property of CS, time domain channel estimation can be easily achieved. We analyzed the complementary sequence, m sequence and combinational Barker code (CB-c) including autocorrelation function (ACF) and expansion principle. Furthermore, the system model and the design of channel estimation sequence are described. The normalized mean square error (NMSE) performance shows that the CS is superior to the other two kinds of sequence. Meanwhile, the BER performance proved the feasibility of complementary sequences for time domain channel estimation.
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It is indispensable to take a low complexity and high accuracy channel estimation algorithm into account under rapidly growth in wireless communication. In this paper, we propose an algorithm for channel estimation using complementary sequence (CS). By utilizing the fantastic autocorrelation property of CS, time domain channel estimation can be easily achieved. We analyzed the complementary sequence, m sequence and combinational Barker code (CB-c) including autocorrelation function (ACF) and expansion principle. Furthermore, the system model and the design of channel estimation sequence are described. The normalized mean square error (NMSE) performance shows that the CS is superior to the other two kinds of sequence. Meanwhile, the BER performance proved the feasibility of complementary sequences for time domain channel estimation.
Key concepts: Autocorrelation, Channel (broadcasting), Sequence (biology), Algorithm, Computer science, Time domain, Frequency domain, Bit error rate