Accurate estimation of Doppler shift in mobile communications with high vehicle speed

Abstract

SUMMARYRepresenting the channel varying rate and the mobile speed of a mobile terminal directly, Doppler shift is an important parameter in vehicular mobile communications and therefore is widely used in mobile target detection and adaptive applications. Hence, this paper puts forward an accurate Doppler shift estimator in mobile communications with high vehicle speeds, which can also be treated as a vehicular speed estimator due to the well-known relation between the Doppler shift and the mobile speed. Specifically, the proposed estimator is based on the channel level crossing rate, and an iterative process is presented to achieve signalto-noise ratio (SNR) insensitive estimates in accordance with the level crossing rate estimation error analysis. Moreover, we prove the convergency of the iterative Doppler shift estimator in theory. Computer simulations conducted under a wide range of noise corruption clearly show that the proposed estimator substantially outperforms several existing estimators in terms of accuracy and achieves a good SNR-insensitive performance in a wide range of velocities and SNRs.

Doppler Shift Compensation Schemes in VANETs

“…In terms of BER performance at 30 dB SNR the 5th iteration achieves BER of 5 × 10 −3 , way above the 10 −3 threshold for errorfree threshold, therefore providing robust Doppler shift compensation performance under a wide range of fading conditions similar to the approach implemented by Qian et al [25] and Ma et al [26]. Hua et al [27] achieved the result using the level crossing rate estimation error analysis.…”

Doppler Shift Estimation and Compensation in High Speed MIMO-OFDM VANETs

“…In [4], a DFS estimator based on level-crossing rate (LCR) is proposed, while the DFS es-timator based on an autocorrelation function (ACF) is proposed in [5], [6], [7]. An extension to multiple input multiple output (MIMO) systems was investigated in [8], [25] and a frequency-domain DFS estimation method based on polynomial approximation to the zero order Bessel function of the first kind was proposed in [9]. In [10], the DFS in underwater acoustic (UWA) channel is extracted by time expansion and compression.…”

“…Hua et al [4], proposed an estimation of DFS using an adaptive level-crossing rate (LCR) method. Hua et al [4] exploited the proportionality relation between the LCR of the received signal envelope and the DFS to estimate the DFS.…”

“…Hua et al [4], proposed an estimation of DFS using an adaptive level-crossing rate (LCR) method. Hua et al [4] exploited the proportionality relation between the LCR of the received signal envelope and the DFS to estimate the DFS. However, the authors did not take into consideration effects of the multi-path delay spread on DFS estimates from the envelope of the received signal fading rate.…”

“…However, the authors did not take into consideration effects of the multi-path delay spread on DFS estimates from the envelope of the received signal fading rate. Moreover, a computationally complex iterative LCR approach was proposed without considering the high capacity MIMO channels [4]. The three issues such as multi-path delay spread, high computational system complexity and low capacity in the SISO channel render the algorithms in [4] unattractive in full scale deployment of VANETs in relatively high speed MI-MO-OFDM systems [24].…”