Fading Channels Research Articles

Optimizing energy harvesting with diversity in cooperative simultaneous wireless information and power transfer systems

SummaryRadio frequency (RF) energy harvesting (EH) for wireless networks provides a green and sustainable solution and offers an energy‐efficient system. It is most crucial for fulfilling the power requirement of the rising number of low‐powered wireless devices and achieving sustainable development goals (SDG). It ensures the longevity of devices in the network even at inaccessible remote locations. Such RF‐EH‐based mechanisms are utilized in simultaneous wireless information and power transfer (SWIPT) systems. Most of the prevailing studies have analyzed the SWIPT system over conventional fading channels. However, due to the higher rate requirements, the current paradigm shift in frequency usage shifts towards the GHz band, which also offers better EH efficiency. Hence, SWIPT system analysis over the channel that is suitable for mm‐wave signal propagation is dealt with in this study. This study evaluates SWIPT performance over fluctuating two‐ray (FTR) fading channel that is crucial since it provides the best fit for characterizing GHz signal and also provides a generalized framework for most of the conventional fading channels. This study presents new analytical results assuming time switch relaying (TSR) protocol with (i) amplify and forward (AF) and (ii) decode and forward (DF) relaying. The results are also analyzed for H branches maximal ratio combining (MRC) diversity technique and evaluated the diversity gain for both AF and DF relays. The effectiveness of the system is measured in terms of system outage probability (SOP) to envisage the reliability of SWIPT based system. This work presents the simulation and modeling of such system and its obtained results are validated by Monte Carlo simulations for their accuracy.

Information Theory and Coding Techniques for 5G Wireless Communication Systems: Towards Efficient Spectrum Utilization

The introduction of 5G wireless communication networks has initiated a new period of connectivity, offering extremely high data rates, minimal delay, and extensive device compatibility. However, in order to fully use the capabilities of 5G, it is crucial to prioritize the effective exploitation of spectrum. Efficiency in data transmission is achieved by the optimization of data transmission, error minimization, and maximization of throughput, which are facilitated by information theory and coding techniques. This work examines the convergence of information theory and coding methods in the context of 5G wireless communication systems, with an emphasis on improving the efficiency of spectrum usage. The core of information theory is centered around the notion of entropy, which measures the level of uncertainty linked to a random variable. Information theory offers valuable insights into the underlying constraints of communication networks by utilizing concepts like channel capacity and error-correcting codes. When it comes to 5G, it is crucial to comprehend these limitations in order to develop transmission strategies that effectively utilize the spectrum resources at hand. Coding techniques, such as forward error correction (FEC) and channel coding, are essential for reducing the impact of noise, interference, and fading in wireless channels. Forward Error Correction (FEC) is a technique that enhances the reliability of transmitted data by introducing redundancy. This allows receivers to repair errors without requiring retransmissions, thus increasing the efficiency of the available spectrum. Advanced coding techniques such as low-density parity-check (LDPC) codes and polar codes are crucial for delivering high data transfer rates and reliability in 5G networks. By combining various access strategies, such as orthogonal frequency-division multiple access (OFDMA) and non-orthogonal multiple access (NOMA), along with advanced coding schemes, we can achieve higher spectral efficiency and increase the capacity for users. These strategies facilitate the optimal distribution of resources, enabling multiple users to efficiently share the same spectrum while satisfying their quality-of-service demands. Information theory and coding.

Information-Theoretic Security in Wireless Sensor Networks: Mathematical Models for Secure and Energy-Efficient Communication

Wireless Sensor Networks (WSNs) are used for a wide range of things these days, from watching the environment to improving healthcare systems. But because these networks are used everywhere, they are also open to security risks like spying, data corruption, and node capture. It is very important to address these issues in order to protect the accuracy, privacy, and access of data being sent. Information-theoretic security looks like a good way to deal with these problems because it uses mathematical models to make sure that transmission in WSNs is safe and uses little energy. This essay goes into detail about information-theoretic security in WSNs. It gives a full rundown of the mathematical basics and real-world implications for getting strong security in places with limited resources. The idea of "secrecy capacity" is at the heart of this method. It measures the highest rate at which authorized nodes can communicate privately while preventing spying foes. Utilizing the chance that exists in wireless channels, encrypted keys can be generated without using shared secrets, making them resistant to attempts that try to steal them. Because sensor nodes only have a short power life, energy economy is very important in WSNs. Information-theoretic security methods, like physical layer security and joint communication, are designed to use as little energy as possible while still providing strong security. Nodes can work together to improve signal strength and fight channel fading using cooperative methods. This makes the network last longer without compromising security. This article also talks about the trade-offs between security, energy savings, and communication performance in WSNs. This helps us figure out how to make the best transfer schemes.

A deep learning based broadcast approach for image semantic communication over fading channels

A deep learning based broadcast approach for image semantic communication over fading channels

Effectiveness Evaluation of Coded FTN Signaling in the Presence of Nonlinear Distortion Under Multipath Fading Channels

Effectiveness Evaluation of Coded FTN Signaling in the Presence of Nonlinear Distortion Under Multipath Fading Channels

Comparative Performance of Point-to-Point Multiple Input Multiple Output System under Weibull and Rayleigh Fading Channels

Multiple-input multiple-output (MIMO) technologies use multiple antennas at the sender and the receiver to get the high data rate that the next-generation communication system needs. This paper compares MIMO systems using the Quadrature Phase Shift Keying (QPSK) modulation scheme for two-channel distributions of Rayleigh and Weibull types. The performance of the work is far with the Minimum Mean Square Equalizer (MMSE) in terms of Bit Error Rate (BER) for various antenna number situations on the transmitter and receiver sides. The MIMO module is carried out using MATLAB code. The channel noise will be a signal of random noise that is generated. To mitigate the impact of inter-channel interference, the MMSE approach employs inverse filtering at the receiver, and BER will be calculated. According to simulation results, the system's performance is primarily influenced by the number of antennas; it decreased as the number of antennas increased, and the BER of the Weibull channel decreased as the two-parameter value increased

Dither Signal Design for PAPR Reduction in OFDM-IM Over a Rayleigh Fading Channel

Dither Signal Design for PAPR Reduction in OFDM-IM Over a Rayleigh Fading Channel

Reduced-Complexity Intelligent Reflecting Surface Optimization for Single-Carrier Transmission in Frequency-Selective Fading Channel

Reduced-Complexity Intelligent Reflecting Surface Optimization for Single-Carrier Transmission in Frequency-Selective Fading Channel

Manifold Optimization-Based Data Detection Algorithm for Multiple-Input–Multiple-Output Orthogonal Frequency-Division Multiplexing Systems under Time-Varying Channels

Recently, multiple-input–multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems have gained significant attention in the field of wireless communications. The utilization of the Riemannian manifold has become prevalent in MIMO-OFDM systems. However, the existing data detection algorithms for MIMO-OFDM systems are mostly designed for block fading channels. Additionally, these algorithms often suffer from high computational complexity. In this paper, we propose a data detection algorithm on the basis of Riemannian manifold optimization for MIMO-OFDM systems under time-varying channels. The core concept of this algorithm is to optimize the transmitted signals by solving the manifold optimization problem in the case of time-varying channels. In order to reduce the computational complexity of the algorithm, we improve the proposed algorithm by dividing the transmitted signals into multiple subframes for solving the optimization problem separately and using the pilots to maintain the performance of the algorithm. In the simulation, the performance of multiple proposed algorithms and the forced-zero detection algorithm under different parameter settings are compared. The simulation results show that the proposed algorithm demonstrates good bit error rate and computational complexity performances.

Performance Evaluation of Fractal Wavelet Packet Transform on Wireless Communication Systems

The performance of the phase shift keying (PSK) modulation technique over additive white Gaussian noise (AWGN) and multipath propagation channels generally becomes worse for higher-order modes. Therefore, a new modulation technique should be provided in order to have a system that is capable of transmitting data with higher efficiency while maintaining better performance at the same time. This paper presents the development of a fractal wavelet packet transform incorporated within the M-ary PSK system, namely M-ary PSK orthogonal wavelet division multiplexing (OWDM), which is proposed to obtain high performance of modulation in terms of spectrum efficiency and bandwidth resources intended for wireless communication systems. To demonstrate performance improvement over a Rayleigh frequency selective fading channel and in the presence of AWGN noise, the proposed system was evaluated and compared to the basic modulation system and M-ary PSK employing orthogonal frequency division multiplexing (OFDM). The performance results show that M-ary PSK OWDM had better performance in comparison with M-ary PSK OFDM and the conventional system. By utilizing 16 subcarriers, QPSK OWDM achieved bit error rate performance improvement from 1.5 × 10-3 to 1 × 10-4 for Eb/N0 of 20 dB with efficient bandwidth.

High-Capacity Multiple-Input Multiple-Output Communication for Internet-of-Things Applications Using 3D Steering Nolen Beamforming Array

In this paper, a novel 2D Nolen beamforming phased array with 3D scanning capability to achieve high channel capacity is presented for multiple-input multiple-output (MIMO) Internet-of-Things (IoT) applications. The proposed 2D beamforming phased array is designed by stacking a fundamental building block consisting of a 3 × 3 tunable Nolen matrix, which applies a small number of phase shifters with a small tunning range and reduces the complexity of the beam-steering control mechanism. Each 3 × 3 tunable Nolen matrix can achieve a full 360° range of progressive phase delay by exciting all three input ports, and nine individual radiation beams can be generated and continuously steered on azimuth and elevation planes by stacking up three tunable Nolen matrix in horizontal and three in vertical to maximize signal-to-noise ratio (SNR) in the corresponding spatial directions. To validate the proposed design, the simulations have been conducted on the circuit network and assessed in a fading channel environment. The simulation results agree well with the theoretical analysis, which demonstrates the capability of the proposed 2D Nolen beamforming phased array to realize high channel capacity in MIMO-enabled IoT communications.

Performance implications of channel aware cooperative probing-GBN ARQ in the context of wireless body area networks

The advent of Wireless Body Area Networks (WBAN) in patient care has revolutionized the healthcare sector as patients can now be monitored continuously in real-time and as well remotely. Despite its significant advantages, WBAN encounters a notable challenge in the fading aspect, which undermines its effectiveness. Improving WBAN efficiency involves tackling signal fading, which is crucial. Cooperative communication offers a promising solution by introducing spatial diversity to counteract fading effects. We propose a scheme that uses cooperative communication and the Probing-Go Back N Automatic Repeat Request (P-GBN ARQ) technique to reduce the fading effect. The proposed method uses feedback to predict the channel's current state, and the probing interval is determined by the received signal's Average Fading Duration (AFD). The proposed scheme's performance is also assessed extensively through simulations employing various metrics. The results demonstrate a considerable improvement in throughput performance with the inclusion of knowledge about channel fading. The Bit Error Rate (BER) execution is compared with Selection Combiner (SC) and conventional Maximal Ratio Combining (MRC). At 10−3, the cooperative method achieves it at 13 dB SNR, whereas the direct approach reaches it at 24 dB SNR, requiring an additional 11 dB. The proposed approach minimizes BER, enhancing throughput and reliability in WBAN.

Channel-Blind Joint Source-Channel Coding for Wireless Image Transmission.

Joint source-channel coding (JSCC) based on deep learning has shown significant advancements in image transmission tasks. However, previous channel-adaptive JSCC methods often rely on the signal-to-noise ratio (SNR) of the current channel for encoding, which overlooks the neural network's self-adaptive capability across varying SNRs. This paper investigates the self-adaptive capability of deep learning-based JSCC models to dynamically changing channels and introduces a novel method named Channel-Blind JSCC (CBJSCC). CBJSCC leverages the intrinsic learning capability of neural networks to self-adapt to dynamic channels and diverse SNRs without relying on external SNR information. This approach is advantageous, as it is not affected by channel estimation errors and can be applied to one-to-many wireless communication scenarios. To enhance the performance of JSCC tasks, the CBJSCC model employs a specially designed encoder-decoder. Experimental results show that CBJSCC outperforms existing channel-adaptive JSCC methods that depend on SNR estimation and feedback, both in additive white Gaussian noise environments and under slow Rayleigh fading channel conditions. Through a comprehensive analysis of the model's performance, we further validate the robustness and adaptability of this strategy across different application scenarios, with the experimental results providing strong evidence to support this claim.

Outage and average sum‐rate analysis of intelligent reflecting surface assisted nonorthogonal multiple access system over η−μ fading channel

SummaryIntelligent reflecting surface (IRS) is evolved as a one of key technology by enabling a reconfigurable, intelligent, and low power for the sixth‐generation (6G) wireless communication. In this research, an IRS‐assisted NOMA network is explored over fading channel, where IRS is placed on top of the base station (BS). IRS aids in fine‐tuning the phase of the incoming signal from BS in a meticulous way, which improves the performance of the system. The statistical channel modeling of downlink IRS‐NOMA system is proposed and validated with Monte Carlo (MC) simulation. Also, analytical expressions of OP and average sum‐rate are derived for user in IRS‐NOMA system over fading channel. Furthermore, the influence of performance factors such as number of reflecting elements (M), power allocation factor, and imperfect successive interference cancelation (I‐SIC) on OP are examined. Simulation results reveal that the IRS‐NOMA system experiences less outage compared to IRS‐OMA and conventional relaying techniques.

Performance Analysis of Distributed Reconfigurable-Intelligent-Surface-Assisted Air–Ground Fusion Networks with Non-Ideal Environments

This paper investigates the impact of non-ideal environmental factors, including hardware impairments, random user distributions, and imperfect channel conditions, on the performance of distributed reconfigurable intelligent surface (RIS)-assisted air–ground fusion networks. Using an unmanned aerial vehicle (UAV) as an aerial base station, performance metrics such as the outage probability, ergodic rate, and energy efficiency are analyzed with Nakagami-m fading channels. To highlight the superiority of RIS-assisted air–ground networks, comparisons are made with point-to-point links, amplify-and-forward (AF) relay scenarios, conventional centralized RIS deployment, and fusion networks without hardware impairments. Monte Carlo simulations are employed to validate theoretical analyses, demonstrating that in non-ideal environmental conditions, distributed RIS-assisted air–ground fusion networks outperform benchmark scenarios. This model offers some insights into the improvement of wireless communication networks in emerging smart cities.

Performance Evaluation of 5G New Radio Low Density Parity Check Codes over Different Scenarios of Lognormal Fading Channel

Performance Evaluation of 5G New Radio Low Density Parity Check Codes over Different Scenarios of Lognormal Fading Channel

Sampling for Remote Estimation of the Wiener Process over an Unreliable Channel

In this paper, we study a sampling problem where a source takes samples from a Wiener process and transmits them through a wireless channel to a remote estimator. Due to channel fading, interference, and potential collisions, the packet transmissions are unreliable and could take random time durations. Our objective is to devise an optimal causal sampling policy that minimizes the long-term average mean square estimation error. This optimal sampling problem is a recursive optimal stopping problem, which is generally quite difficult to solve. However, we prove that the optimal sampling strategy is, in fact, a simple threshold policy where a new sample is taken whenever the instantaneous estimation error exceeds a threshold. This threshold remains a constant value that does not vary over time. By exploring the structure properties of the recursive optimal stopping problem, a low-complexity iterative algorithm is developed to compute the optimal threshold. This work generalizes previous research by incorporating both transmission errors and random transmission times into remote estimation. Numerical simulations are provided to compare our optimal policy with the zero-wait and age-optimal policies.

Error analysis of OFDM‐IM systems for beyond 5G: The effect of IQI at transceiver

SummaryIt is well known that hardware impairments (HWIs) can worthy reduce the wireless system performance at high carrier frequencies by showing random effects. Most current researches for 5 GB systems assume that transmitters and receivers (transceivers) are perfectly equipped. But wireless transceivers ( ) are affected by HWIs in practice. Considering the previous studies in the literature, it is reported that HWIs have devastating effects on the performance of OFDM and OFDM‐index modulation (IM) systems with fading channels. In this paper, in‐phase and quadrature phase imbalance (IQI), which is the one of most HWIs between transmitter and receiver in wireless communication systems, is examined on OFDM‐IM system over Rayleigh and Nakagami‐ fading channels. Two well‐known detectors, the maximum likelihood (ML) detector and the log‐likelihood ratio (LLR) detector are used under the effect of the IQI at . Error performance analyzes over fading channels of the IQI effect on OFDM‐IM system are realized first theoretically and then by computer simulations. Results obtained for the presence of IQI at show that a performance evaluation based only on the presence of IQI in the receiver would be optimistic and misleading in terms of the performance of real‐life OFDM‐IM systems.

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.