Performance of 16QAM over Rayleigh fading channel in the presence of non-Gaussian noise

Thinh, Vo Van; Tue, Huynh Huu

doi:10.1109/atc.2013.6698149

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…The performance of 16‐QAM scheme with the channel subject to Rayleigh fading and non‐Gaussian noise, modeled as a combination of a white Gaussian process and a shot noise process, is presented by Thinh and Tue . A simple approach to estimate the amplitude of fading channel is also presented by the authors.…”

Section: Related Workmentioning

confidence: 99%

Bit error probability of the M‐QAM scheme subject to multilevel double gated additive white Gaussian noise and η‐μ, κ‐μ, or α‐μ fading

Silva

Queiroz

Almeida

et al. 2019

Trans Emerging Tel Tech

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This paper presents new and exact expressions for the bit error probability (BEP) of the square M-ary quadrature amplitude modulation scheme subject to -, -or -fading and multilevel double gated additive white Gaussian noise, which is composed by the sum of a white Gaussian component of variance 2 g and a white Gaussian noise component of variance 2 i gated by a discrete random process defined in continuous time, which takes values into a finite discrete set. BEP curves, with and without imperfect channel estimation, corroborated by simulations using the Monte Carlo method, are presented for different values of parameters that characterize mathematically the channel.Trans Emerging Tel Tech. 2019;30:e3682.wileyonlinelibrary.com/journal/ett

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Section: Related Workmentioning

confidence: 99%

Bit error probability of the M‐QAM scheme subject to multilevel double gated additive white Gaussian noise and η‐μ, κ‐μ, or α‐μ fading

Silva

Queiroz

Almeida

et al. 2019

Trans Emerging Tel Tech

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“…Phase noise, narrowband noise, and impulse noise are also non-Gaussian random processes. Methods of signal processing in the presence of non-Gaussian noise were studied in [17][18][19][20][21][22][23]. Also, for non-Gaussian noise with a known correlation function, a Wiener filter can be used.…”

Section: Introductionmentioning

confidence: 99%

Application of Approximation Constructions with a Small Number of Parameters for the Estimation of a Rayleigh Fading Multipath Channel with Doppler Spectrum Spreading

Poborchaya

Pestryakov

Lobova

2022

Sensors

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In this article, an algorithm for joint estimation of communication channel gains and signal distortions in a direct conversion receiver is proposed. The received signal model uses approximations with a small number of parameters to reduce the computational complexity of the resulting algorithm. The estimation algorithm is obtained under the assumption of a priori uncertainty about the characteristics of the communication channel and noise distribution using the linear least squares method. Estimation is performed first by the test sequence, then by the information symbols obtained after detection. In addition, an analysis of the noise immunity of quadrature amplitude modulation (QAM) signal reception is carried out using different approximating structures in the estimation algorithm for systems with a single transmitting and receiving antenna (SISO) and for systems with multiple transmitting and receiving antennas (MIMO). Furthermore, this article examines the influence of the duration of the test signal, the number of sessions of its transmission, and the channel extrapolation interval on the quality of signal reception.

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Bit error probability of M-QAM under η-μ or κ-μ fading and impulsive noise gated by a signal characterized by a Markov process or Poisson process

Silva

Alencar

Queiroz

et al. 2020

Digital Signal Processing

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Performance of 16QAM over Rayleigh fading channel in the presence of non-Gaussian noise

Cited by 5 publications

References 8 publications

Bit error probability of the M‐QAM scheme subject to multilevel double gated additive white Gaussian noise and η‐μ, κ‐μ, or α‐μ fading

Bit error probability of the M‐QAM scheme subject to multilevel double gated additive white Gaussian noise and η‐μ, κ‐μ, or α‐μ fading

Application of Approximation Constructions with a Small Number of Parameters for the Estimation of a Rayleigh Fading Multipath Channel with Doppler Spectrum Spreading

Bit error probability of M-QAM under η-μ or κ-μ fading and impulsive noise gated by a signal characterized by a Markov process or Poisson process

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