Ricean K-Factor and SNR Estimation for M-PSK Modulated Signals Using the Fourth-Order Cross-Moments Matrix

Bousnina, Ines; Salah, M. Bassem Ben; Samet, Abdelaziz; Dayoub, Iyad

doi:10.1109/lcomm.2012.061912.120708

Cited by 11 publications

(14 citation statements)

References 11 publications

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“…The existing Rician channel models in the literature (see [7], [18], [20] and the references therein) assume: the LoS fading component, h LoS (t) = exp(j2π f d tcosθ 0 + jφ 0 ), where f d , θ 0 , and φ 0 are the maximum Doppler shift, angle of arrival, and initial phase, respectively; the NLoS fading component, h NLoS,• (t), is non-frequency selectivity with Rayleigh distribution and unit power, whose mean and autocorrelation function are zero and zero-order Bessel function, respectively, and whose real and imaginary parts are independent Gaussian random variables that can be modeled by various schemes addressed in [28].…”

Section: Preliminary and Formulationmentioning

confidence: 99%

“…Among the above mentioned Rice factor and RFR estimators except for [7], [9] and [10], they only considered the channel coefficients, and therefore 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.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, the NDA estimator cannot be applied to M-ary phase shift keying (MPSK) modulated signals [7]. The fourth-order cross-moments based Rice factor estimator was investigated in [7] for the MPSK modulated signals. The suggested approaches in [9] and [10] presented the estimation of the RFR for the purpose of frequency estimation.…”

Section: Introductionmentioning

confidence: 99%

“…The suggested approaches in [9] and [10] presented the estimation of the RFR for the purpose of frequency estimation. Moreover, these estimators presented in [7], [9], [10] and [25] only consider the frequency flat fading channels. Except for previous estimators published in the literature, to the best of the authors' knowledge, the estimation of the RFR has not been investigated for Rician doubly selective fading channels which are always encountered in wireless communication systems, especially for high rate wireless communications.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Rice Factor Ratio for Doubly Selective Fading Channels

et al. 2020

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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. INDEX TERMS Rice factor ratio, Rician doubly selective fading channels, second-order and fourth-order statistics.

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Section: Preliminary and Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Rice Factor Ratio for Doubly Selective Fading Channels

et al. 2020

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Research on the memory order of the power‐line communication channel

Zhai

2014

Int J Communication

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As a memory channel, power-line communication (PLC) channel can be modeled by the finite states Morkov model. The memory order in an finite states Morkov model is a key parameter, which is not solved in PLC systems yet. In the paper, the mutual information is used as a measure of the dependence between the different symbols, treated as the received scalar network analyzer, or amplitude of the current channel symbol or that of previous symbols. The joint distribution probabilities of the envelopes in PLC systems are computed based on the multi-path channel model, which is commonly used in PLC. With the first-order Markovian assumption, we confirm that given the information of the symbol immediately preceding the current one, any other previous symbol is independent of the current one in PLC systems. The field test is also performed to model the received OFDM signals with the help of autoregressive model. The results show that the firstorder autoregressive model is enough to model the fading channel in PLC systems, which means the amount of uncertainty remaining in the current symbol should be negligible, given the information corresponding to the immediately preceding one. POWERLINCE COMMUNICATIONS FIRST-ORDER MARKOV CHANNELS 1069 noisy communications channel, which isn't favorable for the high-frequency communications signal transmission with frequency ranging 0 -30 MHz [7].Because of its ubiquity of already existing electrical power delivery networks, PLC is susceptible to numerous appliances and power networks [8]. Several studies have shown that the PLC channel is impaired by different types of noise, which are mostly produced by the electrical appliances in the networks [9]. The isolator switching or breaker in the grids can cause impulse noise [10]: The broadcast transmitters operating at frequencies higher than a few hundred kilohertz, can ingress the narrow band noise, mostly amplitude modulated sinusoidal signals [11,12]; The switching actions of silicon-controlled rectifier diodes found in many electrical appliances, brush motors, dimmer switches, and industrial sources directly connected to the supply network can cause periodic impulsive noise synchronous to the mains frequency [13]; The switched-mode power supplies can result periodic impulsive noise asynchronous to the mains frequency, with a short duration, random occurrence, and a high-power spectral density [14]; Switching transients in the power network can cause asynchronous impulsive noise.Because the impulsive noise is actually produced by appliances in the power network, the powerline noise can also be regarded as a combined sum of the background noise and the impulsive noises from all nearby appliances [15]. In addition to the behaviors of appliances, channel characteristics between the noise sources and a receiver may vary synchronously to the mains voltage [16]. This channel fluctuation also causes the periodic features of the noise [17]. As a result, PLC channels can be seen as typical noisy channels.Like other noisy channels, the PLC chan...

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Modulation Identification Using Moment Features for Communications via Ricean Fading SIMO Channels

Salah

Samet²

2015

Wireless Pers Commun

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Ricean K-Factor and SNR Estimation for M-PSK Modulated Signals Using the Fourth-Order Cross-Moments Matrix

Cited by 11 publications

References 11 publications

Estimation of Rice Factor Ratio for Doubly Selective Fading Channels

Estimation of Rice Factor Ratio for Doubly Selective Fading Channels

Research on the memory order of the power‐line communication channel

Modulation Identification Using Moment Features for Communications via Ricean Fading SIMO Channels

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