Fading Channel Model Research Articles

Closed-Form Performance Analysis of the Inverse Power Lomax Fading Channel Model

Closed-Form Performance Analysis of the Inverse Power Lomax Fading Channel Model

Performance modeling of composite fading channels: an application to wearable wireless communication systems

In pragmatic wireless propagation scenarios, communication between wearable devices may be significantly impacted by fading, particularly when wireless communication is crucial for mission control, situational awareness, and team coordination in defense operations. There may be times when communication links are temporarily unavailable in places due to contemporaneous effect of slow fading and fast fading, including cities or regions with tough terrain. This phenomena results in composite fading environments. Moreover, the data transfer speeds may drop as a result of fading, making it a challenging task to rapidly transmit crucial real time data. In addition, the precision of GPS and positioning systems, that are essential for operations viz., target tracking, navigation and rescue can be impacted by fading. In this setting, the work portrays modeling the fading channels over the Weibull distribution by exploiting Tsallis’ q-statistical framework. From the analytical observations, it was evident that in contrast to the well-known composite models, the q-Weibull model provides a better characterization of the generated fading signals. Furthermore, the closed form solution to the different performance metrics that are crucial in characterizing the fading environments are provided.

Distributed Dynamic Event-Triggered Leader-Following Consensus for Nonlinear Multiagent Systems Over Fading Channel.

This article investigates the leader-following consensus problem of discrete-time nonlinear multiagent systems (MASs) over fading channels. With the consideration of the transmission among followers maybe affected by the fading networks, the nonidentical fading channels model is constructed. To reduce the transmission network burden, the dynamical event-triggered mechanism (DETM) is developed. Different from most of existing event-triggered strategies, the threshold parameter in the developed dynamical event-triggering condition is dynamically adjusted according to a dynamic rule. Based on the DETM, a distributed consensus control protocol is designed under fading channels. Then, sufficient criteria are provided to ensure that MASs can achieve the leaser-following consensus, and satisfy the H∞ performance index in the presence of fading channels. The desired controller parameters can be derived in terms of solutions of matrix inequalities that are lightly solvable. In the end, simulation results show that the designed dynamical event transmission policy is capable of diminishing communication burden more promptly and effectively than some existing ones.

A Multipath Approach to Self-Interference Cancellation in MIMO Rayleigh Fading Channels

An optically enabled multipath self-interference (MSI) cancellation technique for in-band full duplex (IBFD) multiple input multiple output (MIMO) Radio over Fiber RoF systems under Rayleigh fading channels is proposed. A digitally assisted Rayleigh fading channel model generates the MSI signal. An optically tunable multipath delay lines (OTMDL) module is designed using optical delay lines and an optical attenuator for coarse and fine-tuning of time delays and amplitude matching between the locally generated reference (LR) signal and the MSI signal. The OTMDL module adjusts the LR signal to cancel the effect of MSI on the signal received through the fading channel. The concept is validated using a remote sensor node of a 3 × 3 IBFD MIMO RoF system with a Rayleigh fading channel. The system's performance is evaluated by determining the MSI cancellation depths using the OTMDL section for various cancellation channels and by computing the MSI cancellation for both single band and wideband signals across different cancellation channels. An average value of MSI cancellation depth of 20.38 dB is obtained for a single-tone radio frequency signal in the range 15–25 GHz. Thus, the proposed system for MSI cancellation can be utilized in wireless communication systems in multiple ways.

An Analytical Reliability Performance Assessment of Cell-Free Massive MIMO Systems for 5G and Beyond Cellular Networks

In today‟s realm, the 5G cellular networks offer a new era of fully digital environment by connecting people anywhere anytime. This era requires inspiring demands to the networks in terms of spectral and energy efficiencies, low-latency and ultra-reliable communications. A major development to deal with these unparalleled demands is the introduction of Cell- Free Massive MIMO (CF mMIMO) systems to the cellular network. In recent years, mathematical foundations have been laid for a CF mMIMO communication system to evaluate the spectral and energy efficiencies given the number of access points. Various existing literatures have adopted mathematical models to formulate closed-form expressions for these efficiencies using uncorrelated Rayleigh fading for simple linear processing detectors. In this paper, we try to address a compelling and interesting question which has not received much attention lately. The question is how to evaluate the reliability of a connected user terminal in both a CF mMIMO and conventional mMIMO system? We answer this question by first analyzing the signal models for both systems assuming exact channel estimates and consider an uncorrelated Rayleigh fading channel model. The exact Bit Error Rate, as a reliability assessment, in closed-form are then derived based on strong mathematical foundations, which are simple to numerically evaluate in Matlab R2022, for MPSK and MQAM modulation schemes. The mathematical models presented in this work can be used in 5G and Beyond 5G networks to evaluate the distributions of error rates for a user given the number of Access points or Base Station antennas and modulation scheme. Machine Learning algorithms can be applied to the analytical expressions with a view to predict the error performance of a user terminal given the fading characteristic of the propagation environmen

A Spatially Non-Stationary Fading Channel Model for Simulation and (Semi-) Analytical Study of ELAA-MIMO

A Spatially Non-Stationary Fading Channel Model for Simulation and (Semi-) Analytical Study of ELAA-MIMO

Performance Evaluation of 5G New Radio Polar Code over Different Multipath Fading Channel Models

Performance Evaluation of 5G New Radio Polar Code over Different Multipath Fading Channel Models

Secrecy Performance of a Non-Orthogonal Multiple Access-Based Space–Air–Ground Integrated Network System with Stochastic Geometry Distribution of Terrestrial Terminals and Fog Absorption in Optical Link

Recently, non-orthogonal multiple access (NOMA)-based space–air–ground integrated networks (SAGINs) have gained increasing attention due to their robust communication, broader coverage, and resource-saving advantages. However, it is imperative to consider physical layer security as a crucial performance metric in NOMA-based SAGINs. This study addresses this concern by constructing a NOMA-based free space optical (FSO)/radio frequency (RF) dual-hop SAGIN system with eavesdroppers on both links. The two new fading channel models were proposed, considering the FSO link’s fog absorption and the RF link’s stochastic distribution based on Málaga and shadowed Rician distributions. The closed-form expressions for the secrecy outage probability are derived for the SAGIN system. Monte Carlo simulations were conducted to validate the theoretical findings. The results revealed the influence of fog absorption and the stochastic geometry distribution on the SAGIN system.

On the Performance of MMSE Channel Estimation in Massive MIMO Systems over Spatially Correlated Rician Fading Channels

Massive multiple-input-multiple-output (M-MIMO) offers remarkable advantages in terms of spectral, energy, and hardware efficiency for future wireless systems. However, its performance relies on the accuracy of channel state information (CSI) available at the transceivers. This makes channel estimation pivotal in the context of M-MIMO systems. Prior research has focused on evaluating channel estimation methods under the assumption of spatially uncorrelated fading channel models. In this study, we evaluate the performance of the minimum-mean-square-error (MMSE) estimator in terms of the normalized mean square error (NMSE) in the uplink of M-MIMO systems over spatially correlated Rician fading. The NMSE allows for easy comparison of different M-MIMO configurations, serving as a relative performance indicator. Besides, it is an advantageous metric due to its normalization, scale invariance, and consistent performance indication across diverse scenarios. In the system model, we assume imperfections in channel estimation and that the random angles in the correlation model follow a Gaussian distribution. For this scenario, we derive an accurate closed-form expression for calculating the NMSE, which is validated via Monte-Carlo simulations. Our numerical results reveal that as the Rician K-factor decreases, approaching Rayleigh fading conditions, the NMSE improves. Additionally, spatial correlation and a reduction in the antenna array interelement spacing lead to a reduction in NMSE, further enhancing the overall system performance.

Uplink-downlink resource optimization for provisioning 5G application considering SUI fading channel models

Recently, superposition coding (SC), Stanford University Interim (SUI) fading channel, user clustering, successive interference cancellation (SIC) mechanism has been incorporated into the power allocation design for attaining good performance. Nonetheless, the existing model works with cluster size up to 4 user per cluster and induce higher control channel overhead. In addressing this paper introduce an effective resource allocation (ERA) design for power domain non-orthogonal multiple access (PD-NOMA) system. The ERA, first employ Zadoff Chu (ZC) coding, then power is allocated according to the distance considering 5 user per cluster. Finally, multi-level SIC is done at the receiver end. The ERA performance is studied by varying signal-to-noise ratio (SNR) in terms of bit error rate (BER) considering a maximum of five users per cluster. Further, the ERA performance in terms of BER is tested under different scenario defined in SUI propagation scenario such as higher pathloss, moderate path loss, and low path loss. The throughput performance under varied density and speed is also studied; the ERA achieves much better performance in terms of ERA, SNR and throughput than standard multi-user downlink resource allocation (MUDRA) model.

Downlink Learning-aided Precoding for Cell-Free networks Specially D esigned for beyond 5G Communication System

Objectives: With increase in number of access points in Cell-Free Massive Multiple Input Multiple Output (CFMM) system, spatial complexity of calculating precoding vector increases with traditional precoding schemes. So, to reduce computational complexity, network cost, and run time, a new deep learning -aided precoder is specially designed for CFMM system. The performance of downlink (DL) Cell-Free Massive Multiple Input Multiple Output (CFMM) system operating under Rayleigh fading channel model is analyze using new deep learning-based precoding scheme. Methods: We introduce new deep learning-aided precoder and an improved version of basic scalable pilot assignment algorithm which enhances system performance. We derive closed- form expression for average DL spectral efficiency (SE) for the proposed scheme, which is then compared with Minimum Mean Square Error Successive Interference Cancellation (MMSESIC), Regularized Zero Forcing (RZF), Least Square (LS) and Maximum Ratio (MR) combining techniques. We analyze the proposed scheme with perfect channel state information (CSI), instantaneous CSI, coherent transmission, non-coherent transmission, different pilot configuration. Findings: The spectral efficiency obtained with CFMM-MMSESIC and the proposed scheme is 3 bits/s/Hz, and 2.5bits/s/Hz respectively, which clearly indicates the difference of 20 % only. So, the proposed scheme gives near optimal results, and we can use simple linear combining techniques instead of complex non-linear combining techniques. Also, the proposed scheme with coherent data transmission gives performance curve, which is very close to MMSESIC scheme as desired. The performance of the proposed system is improved by reducing run time and computational complexity as compared to conventional linear precoding schemes. Novelty: The proposed precoder improves performance by reducing run time and computational complexity. Advanced pilot assignment algorithm enhances performance by reducing pilot contamination. Keywords: Cell-Free Massive Multiple Input Multiple Output, Pilot Contamination, Precoding, Minimum Mean Square Error Successive Interference Cancellation, Maximum Ratio, Regularized Zero Forcing (RZF), Least Square (LS)

Set‐membership state estimation for delayed switched systems with fading measurement and interval uncertainty

AbstractConsidering the influence of interval uncertainty, a set‐membership state estimation algorithm based on zonotope is proposed for discrete‐time delayed switched systems subject to unknown but bounded noises. To economize on communication resources, an event‐triggered mechanism is introduced to ensure the efficient transmission of the required observation information. For the channel fading phenomenon during data transmission, an interval channel fading model applicable to the zonotope set‐emmbership state estimation is proposed. The asynchronous state observer is constructed by considering the inconsistency between event‐triggered instant and subsystem switched instant. The sufficient conditions for the existence of the state observer are given using the average dwell time method. The optimal observer gain matrix is derived by solving convex optimization. On this basis, the zonotope and the state estimation interval containing states are given by the zonotopic method. Finally, the validity and feasibility of the proposed algorithm are demonstrated by a numerical example with the comparison result.

Securing cooperative vehicular networks amid obstructing vehicles and mixed fading channels

Smart cities (SCs) were founded on the basis of the Internet of Vehicles paradigm, aiming to enhance the quality of life. Despite not having a unique composition, the intelligent transportation services (ITS) is a key component in most of the SCs. The ITS integrates the new communication systems along with the traditional transportation systems, forming a universal network of static and vehicular entities communicating over wireless broadcast channels. In addition to its vulnerability to co-channel interference (CCI), eavesdropping, and fading, the vehicle-to-vehicle communication channels could be subjected to shadowed fading. That is due to the probabilistic obstruction by big vehicles. Hence, degrading the signal-to-noise ratio at the receiving vehicle severely. This work evaluates the secrecy performance of a practical cooperative vehicular relaying network in terms of its secrecy outage probability (SOP). Due to the probabilistic existence of a vehicular obstacle, three different communication scenarios are considered and a novel closed-form analytical expression for the SOP is obtained over mixed Nakagami-m fading and Nakagami-N-Gamma shadowed fading channels. The system comprises legitimate source and destination operating in full-duplex mode, thus imposing CCI on both the relay and the passive eavesdropper. The result demonstrate the impacts of the secrecy data rate threshold, the strength of shadowing, the density of the obstructing vehicles, and several parameters on the SOP. High levels of shadowing strength and density of obstructing vehicles significantly degrades the secrecy performance by increasing the SOP. Accordingly, adopting the mixed fading channel model is of great importance for practical network modeling.

Estimation of Uplink Channels for Multiple Users Using Tensor Modeling in RIS-Aided MISO Communication

In this paper estimation of uplink channels using tensor modeling is addressed for multiple users in a reconfigurable intelligent surface (RIS)-aided multiple-input single-output (MISO) communication. The coherence interval is divided into structured frames of pilot symbols transmitted by the users and pattern of phase shifts applied by the RIS in order to estimate the base station (BS)-RIS channels and the RIS-user’s channels. Estimation methods that use tensor modeling including Khatri-Rao Factorization (KRF) and bilinear alternating least squares (BALS) are applied to the signal model. Numerical results show that both KRF and BALS are superior to the LS estimator by 10 dB SNR for the correlated Rayleigh fading channel model.

Channel Estimation in MIMO OFDM Systems with Tapped Delay Line Model

The continuous increase in the user demands fornew-generation communication systems, is making the wireless channel more complex and challenging for estimation, developing a simulation model for the channel,and evaluating the performance of different MIMO systems. In this work, a simulation model for multipath fading channels in wireless communication is performed. The model includes a selection of typical Tapped-Delay-Line channel models that can be implemented to reproduce the effects of representative channel distortion and interference. Based on the simulation results, the proposed method exhibits accurate channel estimation performance for frequency-selective fading channels. The proposed work employed LS, MMSE, and ML methods for channel estimation, using 16 and 32 pilots and fixed pilot locations in each frame. Results are obtained for 4x4, 8x8, 16x16, 16x8, and 16x4 MIMO systems and tapped delay line systems.

Neural network channel estimator for time‐variant frequency‐selective fading channels

AbstractThe next generations of wireless communications systems are pushing the limits of the channel estimation methods utilized in the orthogonal frequency division multiplexing receptors. This letter proposes a novel channel estimation method using a densely connected neural network considering the time‐variant frequency‐selective fading channel model. A fully connected deep neural network for the AWGN channel case is also proposed. The comparative complexity of the estimation for different channel models is also discussed. The simulation results demonstrate that the densely connected neural network method surpasses the minimum mean‐square error method performance for a signal‐to‐noise ratio ranging from 0 to 25 dB in the frequency‐selective channel.

Generalized MGF-based secrecy outage performance analysis over fading channels using mixture gamma distribution

This paper proposes a novel method to provide secrecy outage performance in various fading environments using a mixture gamma (MG) distribution, which is well known to approximate numerous fading channel models. First, we derive the generalized moment generating function (G-MGF) and incomplete G-MGF (IG-MGF) of the MG distribution. Then, by applying those formulas, we obtain the exact and asymptotic expressions of the secrecy outage probability along with the corresponding lower bound and probability of the strictly positive secrecy capacity for various fading scenarios. Finally, the accuracy and effectiveness of all derived formulas are verified through extensive numerical experiments.

Least Square Estimation-Based Different Fast Fading Channel Models in MIMO-OFDM Systems

In cellular wireless communication systems, channel estimation (CE) plays a pivotal role as a crucial technique applied in orthogonal frequency division multiplexing (OFDM) modulation. CE utilizes a variety of methods, including decision-directed channel estimation, pilot-assisted channel estimation (PACE), and blind channel estimation. Among these options, PACE is widely favored for its remarkable stability and consistent superior performance. The idea of massive multiple-input multiple-output (MIMO) shows tremendous potential for the future of wireless communications. However, existing massive MIMO systems face challenges with their high computational complexity and intricate spatial structures, preventing efficient utilization of channel and sparsity features in these multiantenna systems. In communication channels, the signal received is often influenced by the characteristics of the channel and noise present at the receiver. To address this issue, an efficient dataset is utilized, employing the least square (LS) algorithm for minimization. OFDM is a commonly and widely used modulation method in communication systems utilized to specifically combat resonance fading in wireless channels. In wireless communication systems employing OFDM-MIMO, frequency selectivity and time-varying attributes due to multipath channels cause Intercarrier Interference (ICI) among symbols. Channel estimation is a vital aspect for mitigating the effects of fading channels. This investigation focuses on the application of a method examined in the study, which involves a block-type pilot symbol-assisted estimation technique for Rayleigh and Rician fading channel models. The research assesses the performance of the least square (LS) channel estimators in fast-fading channel models while employing various symbol mapping techniques focusing on bit error rate, throughput, and mean square error. The results indicate that the LS estimator exhibits excellent performance in Rayleigh and AWGN channels within the pedestrian A (PedA) model for both uplink and downlink scenarios. It outperforms the PedA model without channel estimation.

Performance Analysis of 5G New Radio LDPC over Different Multipath Fading Channel Models

The creation and developing of a wireless network communication that is fast, secure, dependable, and cost-effective enough to suit the needs of the modern world is a difficult undertaking. Channel coding schemes must be chosen carefully to ensure timely and error-free data transfer in a noisy and fading channel. To ensure that the data received matches the data transmitted, channel coding is an essential part of the communication system's architecture. NR LDPC (New Radio Low Density Parity Check) code has been recommended for the fifth-generation (5G) to achieve the need for more internet traffic capacity in mobile communications and to provide both high coding gain and low energy consumption. This research presents NR-LDPC for data transmission over two different multipath fading channel models, such as Nakagami-m and Rayleigh in AWGN. The BER performance of the NR-LDPC code using two kinds of rate-compatible base graphs has been examined for the QAM-OFDM (Quadrature Amplitude Modulation-Orthogonal Frequency Division Multiplexing) system and compared to the uncoded QAM-OFDM system. The BER performance obtained via Monte Carlo simulation demonstrates that the LDPC works efficiently with two different kinds of channel models: those that do not fade and those that fade and achieves significant BER improvements with high coding gain. It makes sense to use LDPC codes in 5G because they are more efficient for long data transmissions, and the key to a good code is an effective decoding algorithm. The results demonstrated a coding gain improvement of up to 15 dB at 10-3 BER.

Performance Analysis of IRS-Assisted THz Communication Systems over α-μ Fading Channels with Pointing Errors.

In this paper, we analyze the performance of an intelligent reflecting surface (IRS)-aided terahertz (THz) wireless communication system with pointing errors. Specifically, we derive closed-form analytical expressions for the upper bounded ergodic capacity and approximate expression of the outage probability. We adopt an α-μ fading channel model for our analysis that is experimentally demonstrated to be a good fit for THz small-scale fading statistics, especially in indoor communication scenarios. In the proposed analysis, the statistical distribution of the α-μ fading channel is used to derive analytical expressions for the ergodic capacity and outage probability. Our proposed analysis considers not only the IRS reflected channels, but also the direct channel between the communication nodes. The results of the derived analytical expressions are validated through Monte Carlo simulations. Through simulations, it has been noticed that pointing errors degrade the performance of the IRS-assisted THz wireless communication system which can be compensated by deploying an IRS having a large number of reflecting elements.