Abstract
This paper presents a new time of arrival (TOA) estimation technique using an improved energy detection (ED) receiver based on the empirical mode decomposition (EMD) in an impulse radio (IR) 60 GHz millimeter wave (MMW) system. A threshold is employed via analyzing the characteristics of the received energy values with an extreme learning machine (ELM). The effect of the channel and integration period on the TOA estimation is evaluated. Several well-known ED-based TOA algorithms are used to compare with the proposed technique. It is shown that this ELM-based technique has lower TOA estimation error compared to other approaches and provides robust performance with the IEEE 802.15.3c channel models.
Highlights
Accurate estimation of the time of arrival (TOA) in wireless systems is a challenging problem due to inter-symbol interference and multipath fading
6 Results and discussion the mean absolute error (MAE) of several well-known TC methods were examined for signal-to-noise ratio (SNR) in the range 4 to 30 dB with the IEEE 802.15.3c channel models
(2)The obtained MAEs of the improved energy detector (ED) received indicate that the ability to achieve TOA estimations in Line of Sight (LOS) models is better than that in Non-line of Sight (NLOS) models with regard to each given SNR within 4–30 dB
Summary
Accurate estimation of the time of arrival (TOA) in wireless systems is a challenging problem due to inter-symbol interference and multipath fading. Guvenc first proposed a TOA estimation method via analyzing the kurtosis characteristics of the energy of the received pulses [6].
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