Fading Channels Research Articles

Random Access in Fast Fading Channels: Signature Code Design and Active User Identification

Random Access in Fast Fading Channels: Signature Code Design and Active User Identification

Cooperative spectrum sensing based on locally linear embedding and Adaboost in dynamic fading channel

Cooperative spectrum sensing based on locally linear embedding and Adaboost in dynamic fading channel

Joint SNR and Rician K-Factor Estimation Using Multimodal Network Over Mobile Fading Channels

Joint SNR and Rician K-Factor Estimation Using Multimodal Network Over Mobile Fading Channels

Accurate Expression of the Effective Capacity for Various MIMO Receivers Over Weibull Fading Channels

Accurate Expression of the Effective Capacity for Various MIMO Receivers Over Weibull Fading Channels

Hybrid transmission scheme using FBMC and OFDM under multipath fading channels

Hybrid transmission scheme using FBMC and OFDM under multipath fading channels

SER Analysis of GFDM System οver 𝜶 – 𝝁 Fading Channel for 5G Wireless Applications

SER Analysis of GFDM System οver 𝜶 – 𝝁 Fading Channel for 5G Wireless Applications

BER performance analysis of polar-coded FBMC/OQAM in the presence of AWGN and Nakagami-m fading channel

<abstract> <p>Offset quadrature amplitude modulation–based filter bank multicarrier (FBMC-OQAM) method is a promising technology for future wireless communication systems. It offers several advantages over traditional orthogonal frequency-division multiplexing (OFDM) modulation, including higher spectral efficiency, lower out-of-band emission, and improved robustness to time-frequency selective channels. Polar codes, a new class of error-correcting codes, have received much attention recently due to their ability to achieve the Shannon limit with practical decoding complexity. This paper analyzed and investigated the error rate performance of polar-coded FBMC-OQAM systems. Our results show that applying polar codes to FBMC-OQAM systems significantly improves the error rate. In addition, we found that employing random code interleavers can yield additional coding gains of up to 0.75 dB in additive white Gaussian noise (AWGN) and 2 dB in Nakagami-m fading channels. Our findings suggest that polar-coded FBMC-OQAM is a promising combination for future wireless communication systems. We also compared turbo-coded FBMC-OQAM for short code lengths, and our simulations showed that polar codes exhibit comparable error-correcting capabilities. These results will be of interest to researchers and engineers working on the advancement of future wireless communication systems.</p> </abstract>

Energy Harvesting based Performance analysis in Nakagami-m fading channels

Energy Harvesting based Performance analysis in Nakagami-m fading channels

On Pre-Processing of Generalized Gamma Fading Channel Samples for Secret Key Generation

On Pre-Processing of Generalized Gamma Fading Channel Samples for Secret Key Generation

Performance Analysis of Equal-Gain Combining Receivers Over Composite Multipath/ Shadowing Fading Channels

Performance Analysis of Equal-Gain Combining Receivers Over Composite Multipath/ Shadowing Fading Channels

Polarimetric Modeling of Mobile Fading Channels

Polarimetric Modeling of Mobile Fading Channels

Multi-sensor Power Allocation for Remote Estimation Over Semi-Markov Fading Channels

Multi-sensor Power Allocation for Remote Estimation Over Semi-Markov Fading Channels

Statistical CSI Aided MIMO-NOMA Transmission in Correlated Rician Fading Channels

Statistical CSI Aided MIMO-NOMA Transmission in Correlated Rician Fading Channels

ANALYSIS OF THE USER PAIRING NOMA SYSTEM OVER THE NAKAGAMI-M FADING CHANNEL CONDITIONS

The potential of non-orthogonal multiple access (NOMA) as a multiple access strategy for 5G and LTE upgrades has attracted much attention. In this study, we examine user pairing in NOMA strategy for multiple-input multiple-output (MIMO) users. The simulation results for near-near (N-N) and near-far (N-F) user pairing shames have been provided. The channel becomes time-selective after considering the node mobility situation. Furthermore, simulation curves demonstrate that adopting the user pairing approach reduces computing cost. The network's sum rate performance was further tested utilizing selection combining (SC) NOMA and time division for multiple access (TDMA). It is shown that when a user nearest to the base station is linked with the farthest user from the base station, the total sum rate dramatically increases. When the channel conditions between the two users are varied, the NOMA performs significantly better. The NOMA still surpasses TDMA in terms of sum rate when N-N and far-far (F-F) pairings are used, but the difference isn't significant. The SC-NOMA has a low performance when compared to TDMA. It was discovered that when the shape parameter is adjusted to two, the outage probability (OP) performance of three NOMA mobile users and a standard orthogonal multiple access (OMA) mobile user improved (multipath propagation scenario).

LoWait: Learning Optimal Waiting Time Threshold to Minimize Age of Information Over Wireless Fading Channels

LoWait: Learning Optimal Waiting Time Threshold to Minimize Age of Information Over Wireless Fading Channels

An Efficient Symbol Timing Scheme for OFDM Systems Using Optimal Correlation-Based Circular-Shifted Preamble

We propose a coarse symbol timing scheme for wireless orthogonal frequency division multiplexing (OFDM) systems using an optimal correlation-based circular-shifted preamble (CSP). Our proposed scheme is implemented by off-line correlation-ranking and on-line processing. The on-line processing derives an optimal CSP for transmission according to the off-line correlation-ranking, and employs a delayed multiplication operation for symbol timing. The conducted simulation results show that our proposed scheme outperforms the other existing representative schemes over typical multi-path fading channels in terms of mean square error (MSE) while keeping the computational complexity low.

Optimization of Vehicular Edge Computing Under Time-Varying Fading Channels With Path Prediction

Optimization of Vehicular Edge Computing Under Time-Varying Fading Channels With Path Prediction

Secure Performance of RIS-NOMA System Under κ-μ Shadowed Fading Channel

Secure Performance of RIS-NOMA System Under κ-μ Shadowed Fading Channel

A Novel Machine Learning Approach for Blind Carrier Offset Estimation in OFDM Systems

As wireless networks continue to evolve with the emergence of sixth-generation networks and beyond, OFDM technology is expected to be an essential system component for providing reliable connectivity in an increasingly complex environment. Its high spectrum efficiency, efficiency against impulse noise, and resilience against frequency-selective multipath fading channels make it an invaluable component. Although OFDM technology has various capabilities and uses and is widely used, it has some issues and challenges, and one of these challenges is Carrier Frequency Offset (CFO). The CFO destroys orthogonality between subcarriers and causes subcarrier misalignment at the receiver, resulting in Inter- Carrier Interference (ICI) in OFDM systems. This interference impairs system performance by introducing errors and degrading signal-to-noise ratios (SNR). In this paper, a novel approach to estimate the CFO in OFDM systems via Feedforward Neural Network (FNN) has been proposed. The architecture is precisely designed for regression tasks, with a focus on accurately estimating the continuous parameter φ based on the input features. The multiple hidden layers facilitate the extraction of intricate patterns, while careful training options ensure efficient optimization and monitoring of the training process. The performance of the proposed FNN algorithm is assessed and compared with other subspace-based methods, ESPRIT, PM(MUSIC), and QR. Remarkably, the results demonstrate that the FNN algorithm consistently outperforms all subspace methods, especially in low SNR scenarios.

Attention Guided Multi-Task Network for Joint CFO and Channel Estimation in OFDM Systems

The existence of high carrier frequency offset (CFO) and fading channels degrades the performance of communication systems in high mobility environments significantly. To address these challenges, in this paper, we propose an attention guided multi-task network for joint CFO and channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Specifically, considering the correlation between CFO estimation and channel estimation, we construct a multi-task neural network framework which consists of a shared branch (SB), a CFO estimation branch (CFOEB) and a channel estimation branch (CEB). Among them, the SB extracts common features of two tasks, and the CFOEB and CEB make more detailed CFO and channel estimation, respectively. To further suppress the influence of CFO estimation error on channel estimation, we introduce an attention guided module (AGM) which completes the re-calibration of the channel dimension on the basis of different CFO characteristics. We train the whole network by an end-to-end paradigm and construct a suitable multi-task loss function to balance the losses between different tasks. Simulation results demonstrate that the proposed attention guided multi-task learning based joint CFO and channel estimation scheme outperforms the conventional methods and has greater robustness under various conditions.