Effect of Impulsive Noise on IRS-Aided Communication Systems

Ashraf, Umer; Begh, Gh. Rasool

doi:10.1109/tvt.2022.3203192

Cited by 6 publications

(3 citation statements)

References 26 publications

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“…One of the most common assumptions in the existing IRS literature is the Gaussian nature of noise. However, there are different communication setups where the effect of non‐Gaussian noise cannot be overlooked 23 . These include power line communication (PLC), 24 industrial wireless sensor network (IWSN), 25 co‐channel and adjacent channel interference in mobile cellular networks, 26,27 and underwater communication setups 28 .…”

Section: Introductionmentioning

confidence: 99%

“…However, there are different communication setups where the effect of non-Gaussian noise cannot be overlooked. 23 These include power line communication (PLC), 24 industrial wireless sensor network (IWSN), 25 co-channel and adjacent channel interference in mobile cellular networks, 26,27 and underwater communication setups. 28 Therefore, to characterize the non-Gaussian behavior of noise, an additive white generalized Gaussian noise (AWGGN) model has been considered in this work since it includes classical Gaussian noise and Laplacian noise as special cases.…”

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confidence: 99%

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Performance analysis of intelligent reflecting surface‐assisted mobile wireless networks subjected to generalized Gaussian noise

Ashraf,

Rasool Begh

2023

Int J Communication

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SummaryDifferent from the prior works, this paper presents the performance analysis of an intelligent reflecting surface (IRS)‐assisted communication link in a static and mobile scenario impaired by Rayleigh fading and additive white generalized Gaussian noise (AWGGN). Precisely, the IRS is configured as an intelligent access point, and the mobile behavior of the nodes is characterized by the random waypoint (RWP) model. To this end, closed‐form expressions of average bit error rate (BER), average channel capacity (ACC), and outage probability (OP) in both static and mobile scenarios are obtained. To gain further insight into the system performance at high signal‐to‐noise ratio (SNR), asymptotic expressions are obtained. Moreover, the effect of the number of reflective elements () and the shaping parameter () on the system performance is thoroughly studied. The results indicate that introduction of IRS leads to significant improvement in the overall system performance. The derived results are corroborated with Monte Carlo simulations.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Performance analysis of intelligent reflecting surface‐assisted mobile wireless networks subjected to generalized Gaussian noise

Ashraf,

Rasool Begh

2023

Int J Communication

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“…This enables the design of protocols that wirelessly communicate and thus prolong devices' life time and reduce the rate of their battery replacements turning them "greener [16]". 4. Renewable Energy Integration: The efficient utilization of renewable sources of energy for communication network development infers the system integrity and release from the crutches of the non-renewable energy sources [17].…”

Section: Introductionmentioning

confidence: 99%

Optimization of capacity in non-Gaussian noise models with and without fading channels for sustainable communication systems

Al-Rubaye,

ALRikabi,

Hazim

2023

Heritage and Sustainable Development

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The highest rate at which information may be reliably sent via a communication link is known as its capacity. In the case of non-Gaussian noise, the capacity of the channel depends on the specific characteristics of the noise, which can cause severe errors and reduce the reliability of communication systems over a fading channel. The Gaussian mixture impulsive noise model (GMINM), which is a more general and flexible non-Gaussian model for impulsive noise, has been compared in this paper with the Middleton Class-A impulsive noise model (MCAINM) in terms of derived channel capacity normalized by channel bandwidth (C/BW) with and without Rayleigh fading (Rf) channels. It also investigated the trade-off between complexity and accuracy in modeling the impulsive noise using two simplified Middleton Class-A impulsive noise models based on derived C/BW. The derived C/BW of these models under various conditions, such as different signal-to-noise ratios and impulsive noise parameters and models, have been performed and evaluated using two different scenarios: the exact method and the semi-analytical method. When the impulsive noise parameters and A are both near 0 in GMINM and MCAINM, respectively, the capacity of the impulsive noise channel is found to be equivalent to that of the Gaussian channel sustainable, as shown by the findings based on Monte-Carlo simulations. We have shown that when the impulsive noise decreases, the capacity increases in all models; however, the capacity of Gaussian noise is higher than the capacity of non-Gaussian noise, which in turn is higher than the capacity of non-Gaussian noise over the Rf channel overall values of SNR in dB. Moreover, multi-channel configuration introduces spatial diversity and multiplexing gains that have been proposed to sustainably optimize the ergodic capacity for the challenge case when the channel state information (CSI) is unknown at the transmitter in non-Gaussian noise over Rf channel. In today's rapidly evolving world, sustainable communication systems play a crucial role in ensuring efficient and responsible utilization of resources. As the demand for wireless communication continues to rise, it becomes imperative to optimize the capacity of communication channels, especially in scenarios involving non-Gaussian noise models and fading channels.

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Channel Estimator and Symbol Detector for OTFS Systems Impaired by Impulsive Noise

2023

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Effect of Impulsive Noise on IRS-Aided Communication Systems

Cited by 6 publications

References 26 publications

Performance analysis of intelligent reflecting surface‐assisted mobile wireless networks subjected to generalized Gaussian noise

Performance analysis of intelligent reflecting surface‐assisted mobile wireless networks subjected to generalized Gaussian noise

Optimization of capacity in non-Gaussian noise models with and without fading channels for sustainable communication systems

Channel Estimator and Symbol Detector for OTFS Systems Impaired by Impulsive Noise

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