Systems Engineering and Electronics ›› 2018, Vol. 40 ›› Issue (4): 891-897.doi: 10.3969/j.issn.1001-506X.2018.04.25
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XUE Rui, WANG Tong, HU Deting
Online:
Published:
Abstract:
Adaptive coded modulation (ACM) is an effective method to improve the throughput performance of the unmanned aerial vehicle (UAV) data link. The accuracy of channel estimation is one of the key factors to determine the performance of the ACM system, which directly affects the throughput performance of the UAV data link. The Nakagami fading channel is analyzed and modeled, and the representation of the signal through fading channels is derived. Secondly, the signaltonoise ratio (SNR) estimation algorithm based on multiple phase shift keying (MPSK) modulation for the Nakagami fading channel is deduced and analyzed. Simulation results show that the thirdorder moments (M3) estimation algorithm has a better performance compared with the traditional second and fourth moments (M2M4) SNR estimation algorithm. Finally, because the estimation performance of the nonconstant envelope modulation signal is poor for the existing estimation algorithms in Nakagami fading channels, a weighted SNR estimation algorithm for 16APSK high order modulated signals for nonconstant envelopes for channel estimation of UAV communication systems in Nakagami fading channels is proposed. The algorithm uses the prior information of the received signal and the order moment relation of the signal to estimate the SNR, which has the advantages of low complexity and high estimation accuracy. Simulation results show that the improved algorithm can estimate SNR of the 16APSK modulation signal, and has good SNR estimation performance. Compared with the M2M4 algorithm, the weighted estimation of the SNR estimation algorithm has higher estimation precision by using M3 information.
XUE Rui, WANG Tong, HU Deting. Weighted SNR estimation algorithm based on 16APSK in Nakagami channel[J]. Systems Engineering and Electronics, 2018, 40(4): 891-897.
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URL: https://www.sys-ele.com/EN/10.3969/j.issn.1001-506X.2018.04.25
https://www.sys-ele.com/EN/Y2018/V40/I4/891