Estimation of Rice Factor Ratio for Doubly Selective Fading Channels

Junfeng Wang,Hao Jiang,Jianghui Li,Haixin Sun,Hamada Esmaiel,Gaofeng Pan,Yue Cui

doi:10.1109/access.2020.2973180

Abstract

In wireless communication systems, Rice factor ratio (RFR) defined as K/(1 + K) is a key parameter not only to evaluate the quality of communication channel since it can reveal the severity of the small-scale fading, but also to be employed as a priori information for estimation of other parameters such as frequency. Consequently, its estimation is important for a variety of wireless application scenarios. In this paper, we propose an estimation algorithm on the RFR for the received signals that are disturbed by the Rician doubly selective fading channels and additive noise. During the estimation periods, we initially utilize the known signals to multiply the received signals. Second-order and fourth-order statistics are then employed to further deal with the processed signals mentioned above, which disposes of influence of some unnecessary parameters, e.g., indistinguishable multipaths, maximum Doppler shift, Doppler shift, and noise variance. Finally, a useful expression on the RFR estimation is derived for the Rician frequency selective fast fading channels by flexibly mathematical calculation. Furthermore, the presented method only uses the maximum estimation values of the second-order and fourth-order statistics defined in this paper, which can reduce the computational complexity. Importantly, the investigated scheme is robust to the signal-to-noise ratio over 0 dB and frequency offset (maximum Doppler shift and Doppler shift), and shows a slight improvement on the estimation performance with an increase of the aided data length. The performance and benefits of the proposed approach are verified and evaluated through computer simulations.

Highlights

In the past several years, to satisfy the essential requirements of the traffic growth, the latency reduction and the energy efficiency in the wireless communications, a variety of advanced technologies have been introduced in the existing literature [1]–[5]
We provide two propositions to describe the second-order and fourth-order statistics of r, which will be used to derive the Rice factor ratio (RFR) via some mathematical operations
The above merits, it can be noticed from the equation of the estimation on the RFR that only maximum estimation values of the second-order and fourth-order statistics defined in this paper are utilized, which further reduces the computational complexity so that the addressed scheme is more suitable for such application scenarios requiring low computational loads

Summary

INTRODUCTION

In the past several years, to satisfy the essential requirements of the traffic growth, the latency reduction and the energy efficiency in the wireless communications, a variety of advanced technologies have been introduced in the existing literature [1]–[5]. The estimator for the Rice factor was addressed in [19], which was based on the statistics of the channel phase derivative, i.e., the first moment and zero-crossing rate of the received signal instantaneous frequency. Among the above mentioned Rice factor and RFR estimators except for [7], [9] and [10], they only considered the channel coefficients, and are unable to apply for modulated signals with additive noise [7] To deal with this problem, Chen and Beaulieu [25] considered data-aided and non-data-aided (NDA) methods and utilized autocorrelation of the received signal (namely, the second-order fading statistics) to estimate the Rice factor when a priori knowledge of the normalized maximum Doppler shift was assumed.

PRELIMINARY AND FORMULATION

DERIVED EXPRESSION ON THE ESTIMATION OF THE RICE FACTOR RATIO

CONCLUDED ALGORITHM ON THE ESTIMATION OF THE RICE FACTOR RATIO

PERFORMANCE EVALUATION

STD OF THE ESTIMATED RICE FACTOR RATIO VERSUS N

CONCLUSION