Fading Channels Research Articles

A high-data-rate hybrid index communication system based on quadrature chaos shift keying

To address the rapidly increasing challenges posed by the demands for large-scale data transmission and processing, this paper proposes a high-data-rate hybrid index modulation communication system based on quadrature chaos shift keying (HR-HIM-QCSK). The system employs a hybrid modulation involving carrier index and slot index. In this approach, three mutually orthogonal reference signals are constructed using Walsh codes. These reference signals are then utilized to create three distinct QCSK signals, distinguishing between the activation modes of carriers and time slots. This design allows all slots to carry QCSK signals, significantly enhancing the data rate of the HR-HIM-QCSK system. Theoretical analysis and simulations conducted under additive white Gaussian noise and multipath Rayleigh fading channels demonstrate that the HR-HIM-QCSK system outperforms other competing systems in terms of bit error rate (BER) performance. Further analysis covers aspects such as data rate, spectral efficiency, complexity and covertness, highlighting the superior performance of the HR-HIM-QCSK system in high-data-rate communication. This study provides valuable insights for the design of efficient chaotic communication systems.

Protocol-based state estimation of two-time-scale complex networks with nonhomogeneous sojourn probabilities

This paper is dedicated to researching the problem of the state estimation for two-time-scale complex networks (TTSCNs) subject to sojourn probabilities (SPs) under channel fadings and false data injection attacks (FDIAs). The network’s switching topology is governed by a novel switching law that incorporates time-varying SPs, with the variation of SPs being regulated through a persistent dwell-time (PDT) switching signal. Meanwhile, for the sake of achieving energy savings and mitigating data congestion, the dynamic probabilistic event-triggered weighted try-once-discard (DPEWTOD) policy is innovatively developed by integrating with the major merits of the dynamic probabilistic event-triggered mechanism (DPETM) and WTOD protocol (WTODP) based on hybrid compensation. Different from the traditional communication rules, this DPEWTOD concept not only captures stochastic behavior of the dynamic triggering threshold (DTT), but also enables a compensatory measurement that closely approximates the actual value. Subsequently, we construct time delay-, DTT-, and PDT-dependent Lyapunov functionals to analyze the stability of error dynamic systems in the presence of fading and malicious FDIAs. By employing a separation technique, our proposed solving algorithm transforms non-convex analysis conditions into tractable ones. Eventually, the rationality and effectiveness of the proposed method are demonstrated by an resistance–capacitance (RC) circuit example.

Enhancing uplink NOMA cooperative networks with RIS-UAV assistance in Nakagami-[formula omitted] fading channels

Reconfigurable intelligent surfaces (RIS) emerges as a novel communication technology for the 6G networks, boasting advantages such as low cost, high energy efficiency, and wide coverage. To enhance spectrum utilization and ensure signal transmission stability in complex communication scenarios, this paper presents an uplink cooperative non-orthogonal multiple access (NOMA) transmission network assisted by unmanned aerial vehicles (UAV) equipped with RIS. Firstly, a direct link is established between near users and the base station, while a decode-and-forward (DF) relay R and RIS-UAV are deployed between far users and the base station to achieve reliable transmission in a dynamic environment through joint NOMA. Furthermore, an incremental cooperative NOMA scheme is proposed for the uplink transmission, where the relay R remains silent if the RIS-UAV successfully transmits the signal of distant users; if the RIS-UAV fails to transmit the signal to the base station, the relay R is activated to complete the communication between distant users and the base station. Then, the base station employs a selection combining (SC) scheme to process the received signals. Finally, exact expressions of the outage probability under various power allocation strategies are derived. The research results indicate that the outage performance improves with an increase in the number of RIS reflection elements. Moreover, the presence of RIS-UAV can reduce the impact of power allocation strategies on the performance of the uplink NOMA network compared to networks without RIS-UAV.

Performance Analysis of Downlink Cooperative User Relaying FD/HD NOMA Over Nakagami-$m$ Fading Channels

Performance Analysis of Downlink Cooperative User Relaying FD/HD NOMA Over Nakagami-$m$ Fading Channels

RIS Empowered Index Modulation-Based Receive Diversity Wireless System With Nakagami-$m$ Fading Channels

RIS Empowered Index Modulation-Based Receive Diversity Wireless System With Nakagami-$m$ Fading Channels

Scoring Aided Federated Learning on Long-Tailed Data for Wireless IoMT Based Healthcare System.

In this article, we propose a novel federated learning (FL) framework for wireless Internet of Medical Things (IoMT) based healthcare systems, where multiple mobile clients and one edge server (ES) collaboratively train a shared model on long-tail data through wireless channels. However, the presence of long-tailed data in this system may introduce a biased global model which fails to handle the tail classes. Additionally, the occurrence of severe fading in wireless channels may prevent mobile clients from successfully uploading local models to the ES, thereby excluding them from participating in the model aggregation. These situations adversely affect the performance of FL. To overcome these challenges, we propose a novel scoring aided FL framework that uses a scoring-based sampling strategy to select mobile clients with more tailed data and better transmission conditions to upload their local models. Specifically, we leverage the logits to explore the data distribution among local clients and propose a logits based scoring client selection method to alleviate the impact of long-tailed data. Moreover, we address the impact of severe fading by incorporating the channel state information (CSI) and data rate of clients into the logits based scoring and proposing a novel logits and model upload rate based client selection method. Experimental results demonstrate the effectiveness of our proposed framework. In particular, compared to the conventional FedAvg, the proposed framework can achieve accuracy gains ranging from 4.44% to 28.36% on the CIFAR-10-LT dataset with an imbalance factor (IF) of 50.

Impact of Modulation Constellation Type on the Finite Signal-to-Noise Ratio Diversity Gain in the Presence of a Multipath Fading Channel

Impact of Modulation Constellation Type on the Finite Signal-to-Noise Ratio Diversity Gain in the Presence of a Multipath Fading Channel

Cascaded ELM-based joint frame synchronization and channel estimation over Rician fading channel with hardware imperfections

Cascaded ELM-based joint frame synchronization and channel estimation over Rician fading channel with hardware imperfections

Secrecy Outage Probability and Secrecy Diversity Order of Alamouti STBC with Decision Feedback Detection over Time-Selective Fading Channels

Secrecy Outage Probability and Secrecy Diversity Order of Alamouti STBC with Decision Feedback Detection over Time-Selective Fading Channels

Pipelined Neural Network Assisted Mobility Speed Estimation Over Doubly-Selective Fading Channels

The speed estimation has been widely used for tracking mobile device locations, providing essential information in location/mobility-aware communications, enhancing received signal quality/robustness, and reducing energy consumption and latency. Deep learning can be used to improve the performance constrained by signal/system model. This work focuses on the issues on machine learning (ML) based speed estimation using primary synchronous signal (PSS), which is embedded in the 5G standards, over general time-variant multipath channels. Aiming to reduce the complexity involved in the ML algorithms for the speed estimation in mobile networks, we propose a pipelined ML algorithm to decompose the original ML model into several smaller ones. The advantages of the proposed convolutional neural network (CNN) based approach have been verified by simulations.

Performance Analysis of SWIPT Relay Networks Over Arbitrary Dependent Fading Channels

Performance Analysis of SWIPT Relay Networks Over Arbitrary Dependent Fading Channels

Performance analysis of hybrid combining schemes under Middleton class‐A and SαS${\rm S}\alpha{\rm S}$ impulsive noise model

AbstractImpulsive noise poses a significant challenge to single input multiple output wireless communication systems. This paper assesses the effectiveness of hybrid combining techniques, namely selection combining‐equal gain combining and selection combining‐maximal ratio combining, in mitigating impulsive noise impact caused by both man‐made and natural phenomena. The evaluation considers three different noise models: Additive white Gaussian noise, Middleton class‐A impulsive noise, and symmetric alpha stable impulsive noise, across Rayleigh and Rician fading channels. Bit error rate is employed to gauge channel performance. Our research contribution lies in the comprehensive assessment of hybrid combining techniques under diverse noise models, addressing a critical research gap in wireless communication. Findings indicate that impulsive noise has a more pronounced impact on channel performance than additive white Gaussian noise, and hybrid combining techniques prove more effective in mitigating these effects. The results hold significant implications for single input multiple output wireless communication systems, guiding the development of more robust and reliable communication systems in impulsive noise scenarios.

RIS-Assisted D2D Communication over Nakagami-m Fading with RSMA.

In this study, we investigated reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) communication systems over Nakagami-m fading channels. To enhance the reliability of RIS-assisted D2D communications, we utilized the rate-splitting multiple access (RSMA) technique to maximize the achievable ergodic rate for our considered systems. Specifically, both devices decoded the common symbol by treating private symbols as interference, and then each private symbol was decoded by treating the other as interference. In order to maximize the achievable ergodic rate at the destination, we analyzed the achievable ergodic rate of the RIS link and the D2D link, and the destination jointly decoded both symbols transmitted from the source and device by involving the maximum ratio combination (MRC). We obtained a closed-form expression for the achievable ergodic rate of the proposed RIS-assisted D2D communication system. Finally, we investigated the influence of power allocation factors and the number of reflective elements on the achievable ergodic rate. As seen by the numerical results, there was a good match between the analysis and simulation results, as well as significant superiority compared with existing works.

Performance Analysis of BER and SNR Performance in High-QAM Modulations Using Advancements in MIMO Systems

Wireless communications is one of the most active areas of technology development of our time. This development is being driven primarily by the transformation of what has been largely a medium for supporting voice telephony into a medium for supporting other services, such as the transmission of video, images, text, and data. Today, the widely deployed network type is based on a centralized approach that requires a network point of access, commonly called the Access Point (AP), to serves as a gateway between the mobile device and the Internet. The obtained results demonstrate that spatial diversity along with the power of STBC significantly improves the error performance in frequency selective wireless fading channels. The BER level is depend on the modulation type, SNR value and channel behavior. Modulation schemes that we have used in this paper are 4-QAM, 8-QAM, 16-QAM and 64-QAM which further improved using forward error correction codes (FEC). A comparison is made between the diversity gains of MIMO systems in terms of BER for high QAM modulation scheme. This work presents, a simulation toll MATLAB R2023a used for model implemented using Nakagami channel to study the performance analysis of Bit Error rate (BER) V/S Signal to Noise ratio (SNR). Keywords: AWGN, BER, Fading Channel, MIMO System, Nakagami, OFDM, QAM Modulation, SNR, STBC etc.

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.

RSMA-aided V2X communications: A multi-layer perspective

Rate-splitting multiple access (RSMA), a novel technology in next-generation mobile communications, has garnered increasing attention for its powerful and flexible interference management when compared to traditional multiple access methods. However, considering classical vehicle-to-everything (V2X) communication networks with multiple cells, the flexibility of decoding increases with an increasing number of users having different requests, which results in higher outage performance and additional energy consumption. In order to address these problems, this paper proposes a novel multi-layer (ML) RSMA scheme, aiming to enhance the system performance and decrease the decoding flexibility simultaneously. For the first layer, users enjoying optimal quality of service (QoS) are selected to aid the other cluster members. For the second layer, the cluster members are grouped following the QoS and request similarity. In addition, with respect to our proposed ML-V2X RSMA system, this paper investigates the performance over Rayleigh fading channels, where we derive closed-form expressions of achievable sum rate and outage probability, respectively. Numerical results reveal that: (1) For low SNR scenarios, the ML-V2X RSMA system achieves higher achievable sum rates than classical NOMA-aided V2X systems. (2) The outage probability of ML-V2X RSMA system is superior to that of NOMA-aided V2X systems and traditional cooperative communication systems.

Deep learning-based receiver design for generalized frequency division multiplexing (GFDM)

Generalized frequency division multiplexing (GFDM) is a new efficient multi-carrier system in highly dispersive channels. In a conventional GFDM receiver, if the length of a GFDM block is the power of two (an even number), the equalizer can be implemented with low complexity using the fast Fourier transform (FFT). On the downside, if the block length is even, the GFDM matrix will be singular, leading to severe performance loss. Thus, in the conventional GFDM system, high performance and low complexity cannot be achieved jointly. This paper proposes a new GFDM receiver based on deep learning (DL) methods that can achieve high performance regardless of the GFDM block length. In the proposed GFDM receiver, a deep neural network (DNN) is used to demodulate GFDM symbols. A particular case of a convolutional neural network (CNN) and a fully connected layer are employed in the DNN block. We simulate the proposed DL-based GFDM system in additive white Gaussian noise (AWGN) and multipath channels. Simulation results show that the proposed receiver achieves a significantly higher bit error rate (BER) performance than the conventional GFDM receiver when the length of the GFDM block is even in both AWGN and fading channels. Therefore, the proposed DL-based GFDM receiver can achieve low complexity and high performance simultaneously.

Developing Laboratory Experiments to teach Undergraduate Engineering Students Multi-User Massive MIMO Technology for 5G Cellular Networks

An effective method of facilitating student learning in a laboratory environment is “practice by doing”. The study of modules related to signal-processing for digital communications requires deep mathematical and theoretical foundations but the practice goal is not really emphasized in the undergraduate curriculum at the University of Mauritius. This causes the students to lose interest in the corresponding modules resulting in high rate of failures. In this work, we propose to develop laboratory experiments with a view to bridge the gap between theoretical and practical aspects in the field of Massive Multiple-Input Multiple-Output (MIMO) systems for 5G cellular networks. Various laboratory scenarios are set up that consider a Maximum Ratio Combining (MRC) receiver in the uplink with an uncorrelated Rayleigh fading channel. Moreover, from a signal processing perspective to enhance the student’s understanding, we analyze the efficiency and error performance of Massive MIMO systems with MPSK and MQAM modulation schemes as well as perfect and imperfect channel estimates. The leading industry software package MATLAB R2022 is used to develop all laboratory experiments and the codes are elaborated in this analysis. Data collected from the experiments are used to generate spectral efficiency and error performance curves which can be used for future research. The findings underscore the significance of accounting for both scenarios and illuminate promising avenues for future research in the realm of massive MIMO education and learning. The assimilation of MATLAB® flowcharts for each MRC receiver, MPSK, and MQAM with perfect and imperfect Channel State Information (CSI) adds further depth to the study, ensuring a comprehensive understanding of the intricacies of massive MIMO systems. Ultimately, this contribution helps in the nurturing of expertise such that future generations of wireless communication pioneers can be inspired.

Performance analysis of the FSO communication system with random jamming over a composite Málaga turbulence fading channel

The performance analysis of a free space optical (FSO) communication system in the presence of random jamming is presented over a Málaga (M) distributed channel model with pointing errors and atmospheric attenuation. Firstly, the probability density function expressions of the transmission channel, signal-to-jamming ratio, and signal-to-noise ratio are derived. Then, considering the probability of the jammer and Gaussian white noise, the closed-form expressions for the ergodic channel capacity, outage probability, and average bit error rate are derived. Moreover, asymptotic expressions for the aforementioned performance metrics are also derived to ascertain the diversity gain of the system. Extensive Monte Carlo simulations are performed to demonstrate the credibility of this theoretical analysis. Results indicate that the adverse impact of random jamming is higher than that of Gaussian noise for the FSO communication system. Besides, this observation highlights the pulsating nature of the jamming effect, showcasing that within high signal-to-jamming ratio regions, a low probability jammer exerts the most significant impact on the FSO system.

Hybrid selection combining scheme for correlated cooperative communication over [formula omitted]-[formula omitted] fading channels

Due to poor (limited) scattering, a correlation among channels is inevitable, resulting in performance degradation of wireless communication systems. In this paper, we propose a hybrid selection combining (SC), also known as switched scaled – SC for correlated cooperative communication over κ-μ fading channel. By using paired error analysis, we derive the end-to-end symbol error probability of this system over bivariate κ-μ channel fading with M-ary phase shift keying (MPSK) modulation. In addition, we obtain significant parameters of hybrid SS-SC, such as the optimum scaling factor and optimum threshold by using the second derivative test. For every signal to noise ratio (SNR), we obtain different optimum thresholds and scaling factors. Our analytical results were found to overlap significantly with those of the simulation results. They were also compared with the variants of SC and switched diversity techniques. Our study demonstrates that the proposed hybrid technique performs better than the other SC and switched diversity schemes over correlated and uncorrelated fading channels. Furthermore, we derive an asymptotic symbol error probability for the proposed system, and the asymptotic results are in agreement with the analytical results at higher SNRs. Our study also shows that the diversity order of the system depends on the mutually exclusive events of the proposed technique.