Performance Of Wireless Communication Research Articles

Bit Error Performance of APD and SPAD Receivers in Optical Wireless Communication

This review concentrates on the state-of-the-art hardware-oriented receiver aspects for optical wireless communication (OWC), and points to the importance of BER performance analysis and modeling in presence of non-perpendicular light incidence. Receivers in OWC networks for 6G applications have to work for strongly different light incidence angles, to allow the formation of connections to locally separated transceivers without the need for rotation units and accurate adjustment. In turn, and in combination with fully integrated optical receivers, reduction of cost and increased comfort can be achieved. Fully integrated [bipolar] complementary metal-oxide-semiconductor ([Bi]CMOS) receivers with on-chip avalanche photodiodes (APDs) and single-photon avalanche diodes (SPADs) are presented and their performance in optical wireless communication is summarized. Impressive data rates up to 2 Gbit/s and free-space transmission distances up to 27 m at bit error ratios (BER) below 10−9 are reached with linear-mode APD receivers. The importance of optical interference in the isolation and passivation stack on top of the integrated photodiodes is illuminated. To be able to predict the dependence of the BER of single-photon avalanche diode (SPAD) receivers on the light incidence angle, a model, which includes a model for the photon detection probability and a standing-wave model for the isolation and passivation stack, is extended. The dependence of the BER on the light incidence angle onto the photodiodes is investigated by electromagnetic simulation for optical transmission of the layers on top of the photodiode, device simulation for the avalanche triggering probability and BER modeling with MATLAB. It is found that incidence angles up to 30° have moderate influence on the BER and that the BER degrades significantly for incidence angles larger than 50°.

Dual-UAV Enabled Secure Data Collection With Propulsion Limitation

Unmanned aerial vehicles (UAVs) have been widely utilized to improve the end-to-end performance of wireless communications. However, its line-of-sight makes UAV communication vulnerable to malicious eavesdroppers. In this paper, we propose two cooperative dual-UAV enabled secure data collection schemes to ensure security, with the practical propulsion energy consumption considered. We first maximize the worst-case average secrecy rate with the average propulsion power limitation, where the scheduling, the transmit power, the trajectory and the velocity of the two UAVs are jointly optimized. To solve the non-convex multivariable problem, we propose an iterative algorithm based on block coordinate descent and successive convex approximation. To further save the on-board energy and prolong the flight time, we then maximize the secrecy energy efficiency of UAV data collection, which is a fractional and mixed integer nonlinear programming problem. Based on the Dinkelbach method, we transform the objective function into an integral expression and propose an iterative algorithm to obtain a suboptimal solution to secrecy energy efficiency maximization. Numerical results show that the average secrecy rate is maximized in the first scheme with propulsion limitation, while in the second scheme, the secrecy energy efficiency is maximized with the optimal velocity to save propulsion power and improve secrecy rate simultaneously.

Effects of adaptive optics on bit error rate of M-ary PPM oceanic optical wireless communication systems with aperture averaging in strong turbulence

Scintillation is the result of oceanic turbulence reducing the bit error rate (BER) performance of oceanic optical wireless communication (OWC) systems. The scintillation, also known as intensity fluctuations, occurs due to the turbulence-induced wavefront deformations. The correction of deformations by adaptive optics (AO) reduces the scintillation effect of turbulence and results in improved BER performance. In this paper, an oceanic OWC (OOWC) system that has a Gaussian laser beam at the transmitter, finite-sized circular aperture at the receiver, employing M-ary pulse position modulation (PPM) and operating in strong oceanic turbulence, is considered. Improvement in the BER performance of the OOWC system is examined with the implementation of AO correction. Comparison of BER performances between the AO and non-adaptive optics OOWC systems is shown by calculating the metric defined. BER of M-ary PPM OOWC links is evaluated over gamma–gamma fading channels. The modified Rytov theory together with the Zernike filter functions is used to find the AO corrected aperture averaged scintillation index where extended Huygens–Fresnel technique is used to obtain the average received signal power.

Joint Communication, Sensing, and Computation Enabled 6G Intelligent Machine System

With the rapid development of the smart city, high-level autonomous driving, intelligent manufacturing, and so on, the stringent industrial-level requirements of extremely low latency and high reliability for communication and new trends in sub-centimeter sensing have transcended the abilities of 5G and call for the development of 6G. Based on analyzing the function design of the communication, sensing, and emerging intelligent computation systems, we propose the joint communication, sensing, and computation (JCSC) framework for the 6G intelligent machine-type communication (IMTC) network to realize low latency and high reliability of communication, highly accurate sensing, and fast environment adaption. In the proposed JCSC framework, the communication, sensing, and computation abilities cooperate to benefit each other by utilizing the unified hardware, resource, and protocol design. Sensing information is exploited as a priori information to enhance the reliability and latency performance of wireless communication and to optimize the resource utilization of the communication network, which further improves the distributed computation and cooperative sensing ability. We propose promising enabling technologies such as joint communication and sensing (JCS), JCSC wireless networking techniques, and intelligent computation techniques. We also summarize the challenges to achieve the JCSC framework. Then we introduce intelligent flexible manufacturing as a typical use case of the IMTC with JCSC framework, where the enabling technologies are deployed. Finally, we present the simulation results to prove the feasibility of the JCSC framework by evaluating the JCSC waveform, and the JCSC-enabled neighbor discovery and medium access control.

Dispersion From Diffuse Reflectors and Its Effect on Terahertz Wireless Communication Performance

This article investigates the temporal dispersion of a wireless terahertz communication signal caused by reflection from a rough (diffuse) surface, and its subsequent impact on symbol error rate versus data rate. Broadband measurements of diffuse reflectors using terahertz time-domain spectroscopy were used to establish and validate a scattering model that uses stochastic methods to describe the effects of surface roughness on the phase and amplitude of a reflected terahertz signal, expressed as a communication channel transfer function. The modeled channel was used to simulate a quadrature phase shift keying (QPSK) modulated wireless communication link to determine the relationships between symbol error rate and data rate as a function of surface roughness. The simulations reveal that surface roughness from wall texturing results in group delay dispersion that limits achievable data rate with low errors. A distinct dispersion limit in surface roughness is discovered beyond which unacceptable numbers of symbol errors begin to accrue for a given data rate.

Joint Power Allocation and Passive Beamforming Design for IRS-Assisted Physical-Layer Service Integration

Intelligent reflecting surface (IRS) has emerged as an appealing solution to enhance wireless communication performance by reconfiguring the wireless propagation environment. In this paper, we propose to apply IRS to the physical-layer service integration (PHY-SI) system, where a single-antenna access point (AP) integrates two sorts of service messages, i.e., multicast message and confidential message, via superposition coding to serve multiple single-antenna users. Our goal is to optimize the power allocation (for transmitting different messages) at the AP and the passive beamforming at the IRS to maximize the achievable secrecy rate region. To this end, we formulate this problem as a bi-objective optimization problem, which is shown equivalent to a secrecy rate maximization problem subject to the constraints on the quality of multicast service. Due to the non-convexity of this problem, we propose two customized algorithms to obtain its high-quality suboptimal solutions, thereby approximately characterizing the secrecy rate region. The resulting performance gap with the globally optimal solution is analyzed. Furthermore, we provide theoretical analysis to unveil the impact of IRS beamforming on the performance of PHY-SI. Numerical results demonstrate the advantages of leveraging IRS in improving the performance of PHY-SI and also validate our theoretical analysis.

Research and Design of Distributed Fire Alarm System of Indoor Internet of Things Based on LoRa

In order to comprehensively improve the sensitivity of fire warning and effectively shorten the warning time, this paper proposes and implements an indoor distributed fire alarm system based on low power wide area network. The system is mainly composed of three parts: a multisensor acquisition node based on LoRa technology, a distributed edge gateway, and a remote user monitoring system. The multisensor collection node obtains environmental parameters such as indoor temperature, smoke concentration, and air quality and then transmits the sensing data to edge gateway by LoRa after preprocessing. The edge gateway is based on an embedded Linux platform and is deployed in distributed state to collect and store data from multiple collection nodes. Besides, edge gateway forwards valid data to the remote user monitoring system by standard MQTT protocol. The user monitoring system displays current deployment area parameters to users in real time and provides early warning prompts based on relevant preset indicators to help the administrator make more accurate decisions on corresponding measures. The system has been deployed and tested in Nanjing Institute of Technology. By sensor calibration experiments, LoRa communication experiments, and system tests in different environments, the experimental results show that the average received signal strength in a small interference space is -104.12 dBm, and the average received signal strength in a noisy signal environment is -57.5 dBm. By setting the optimal transmitting power for each distance, the packet receiving rate can reach more than 95%, and the alarm accuracy can reach 100% under premise of ensuring the lowest power consumption. Finally, this paper conducts a comprehensive performance analysis on the wireless communication performance of environmental collection nodes, multisensor data fusion algorithm, distributed LoRa edge gateway deployment performance, and remote system early warning accuracy.

Theoretical study on the effectiveness of optical filters to suppress orientation-based solar light noise.

It is well established in the literature that the performance of an underwater optical wireless communication (UOWC) system degrades due to various channel-based and environmental attributes. So far, consistent performance by a UOWC system has not been discussed when the system receiver (Rx) is positioned at a certain depth and takes on different orientations, i.e., vertically upward or downward, and horizontally left or right. This paper discusses the UOWC system performance when the Rx points in three different orientations and captures the modulated light signal and different intensities of solar light. We carry out a detailed comparative performance analysis of the UOWC Rx system considering various optical components, such as a colored glass optical bandpass filter, optical thin-film interference filter, and optical wide-field birefringent filter (OWFBF), which are mounted in front of the UOWC Rx to suppress solar light noise interference for different orientations. We observe that the same UOWC Rx behaves differently in all three orientations and the OWFBF outperforms.

Influence of Autoencoder-Based Data Augmentation on Deep Learning-Based Wireless Communication

Deep learning (DL) has been gradually applied to wireless communication and has achieved remarkable results. However, training a DL model requires numerous data, and an insufficient training dataset will cause serious overfitting problem and reduce model accuracy. Data augmentation (DA) is one of the commonly used techniques to solve the above problem. It is widely used to improve the performance of image and text classification tasks, but its impact on DL-based wireless communication has not been fully explored. Inspired by the emerging deep autoencoder (AE) generative model, we propose an AE-based DA method to improve the generalization performance of the DL-based wireless communication. We perform experimental verification on the two tasks of channel estimation model of wireless communication physical layer and massive multiple-input multiple-output (MIMO) power allocation optimization model. Experimental results show that the AE-based DA method can improve the generalization performance of the wireless communication, but this improvement is related to the training dataset size. When the training dataset size is smaller than a threshold, AE can improve model performance by increasing the relevant training data, but when it is larger than this threshold, it reduces model performance. We also propose that the straight line intersection method can be used directly to roughly determine this threshold. Furthermore, we propose a mixup-based method to solve the problem that the AE cannot improve model performance when the training dataset size is larger than the threshold.

IRS Meets Relaying: Joint Resource Allocation and Passive Beamforming Optimization

Intelligent reflecting surface (IRS) has recently emerged as a new solution to enhance wireless communication performance via passive signal reflection. In this letter, we unlock the potential of IRS controller in relaying information and propose a novel IRS-assisted communication system with both IRS passive reflection and active relaying. Specifically, we jointly optimize the time allocations for decode-and-forward (DF) relaying by the IRS controller and the IRS passive beamforming to maximize the achievable rate of the proposed system. We also compare the rate performance of the proposed system with the conventional IRS without relaying, and reveal the conditions for one to outperform the other. Simulation results demonstrate that the proposed new design can significantly improve the coverage/rate performance of IRS-assisted systems.

Automated Driving with Cooperative Perception Based on CVFH and Millimeter-Wave V2I Communications for Safe and Efficient Passing through Intersections.

The development of automated driving is actively progressing, and connected cars are also under development. Connected cars are the technology of connecting vehicles to networks so that connected vehicles can enhance their services. Safety services are among the main services expected in connected car society. Cooperative perception belongs to safety services and improves safety by visualizing blind spots. This visualization is achieved by sharing sensor data via wireless communications. Therefore, the number of visualized blind spots highly depends upon the performance of wireless communications. In this paper, we analyzed the required sensor data rate to be shared for the cooperative perception in order to realize safe and reliable automated driving in an intersection scenario. The required sensor data rate was calculated by the combination of recognition and crossing decisions of an automated driving vehicle to adopt realistic assumptions. In this calculation, CVFH was used to derive tight requirements, and the minimum required braking aims to alleviate the traffic congestion around the intersection. At the end of the paper, we compare the required sensor data rate with the outage data rate realized by conventional and millimeter-wave communications, and show that millimeter-wave communications can support safe crossing at a realistic velocity.

Research progress of adaptive optics in wireless optical communication system for Xi’an University of Technology

In chronological order, this paper summarizes the research progress and technical classification of adaptive optics technology in the application of wireless optical communication system at home and abroad. Then it introduces the work of Xi’an University of Technology in this field, including adaptive optics system with wavefront measurement, adaptive optics system with wavefront-less measurement, wavefront correction of liquid crystal spatial light modulator, wavefront correction of the combination of tilt mirror and deformable mirror, spatial optical fiber coupling adaptive optical wavefront correction, etc. The adaptive optics technology can effectively correct the distorted wavefront caused by atmospheric turbulence and improve the coupling efficiency and communication performance in wireless optical communication. Although these methods are not perfect in theoretical analysis and engineering practice, they can be regarded as useful exploration in this field.

100 m full-duplex underwater wireless optical communication based on blue and green lasers and high sensitivity detectors

In this paper, in order to improve the practicability and performance of the underwater wireless optical communication (UWOC), we propose a full-duplex (FD) UWOC system based on blue–green wavelength division, which make full use of the low-loss transmission window of water. Narrowband optical filters corresponding to the blue and green wavelengths are employed to eliminate self-interference caused by the backscattering. Single-photon sensitivity photomultipliers (PMTs) are exploited to extend the communication range. The impairment introduced by limited bandwidth and nonlinearity of the devices is compensated by post equalizers. Finally, an FD UWOC system reaching a data rate up to 200-Mbps at a distance of 100 m is demonstrated in a standard swimming pool, which is competitive both in range and data rate among the reported explorations of FD UWOC system. By using a nonlinear equalizer based on the memory polynomial model, the data rates are enhanced by 60-Mbps and 140 Mbps for the blue and green links compared with hard decision, respectively. By measuring the minimum optical power at which the bit error ratio (BER) is lower than the forward error correction (FEC) threshold, and combining with the attenuation coefficient of water as well as the geometric loss caused by the beam divergence, we predict that the proposed FD UWOC system can achieve 200 Mbps over 120 m or 100 Mbps over 139 m underwater transmission. Finally, we analyze and estimate the performance of the FD UWOC system in practical seawater.

Game theoretical secure wireless communication for UAV-assisted vehicular Internet of Things

With the ever-expanding applications of vehicles and the development of wireless communication technology, the burgeoning unmanned aerial vehicle (UAV) assisted vehicular internet of things (UVIoTs) has emerged, where the ground vehicles can experience more efficient wireless services by employing UAVs as a temporary mobile base station. However, due to the diversity of UAVs, there exist UAVs such as jammers to degenerate the performance of wireless communication between the normal UAVs and vehicles. To solve above the problem, in this paper, we propose a game based secure data transmission scheme in UVIoTs. Specifically, we exploit the offensive and defensive game to model the interactions between the normal UAVs and jammers. Here, the strategy of the normal UAV is to determine whether to transmit data, while that of the jammer is whether to interfere. We then formulate two optimization problems, i.e., maximizing the both utilities of UAVs and jammers. Afterwards, we exploit the backward induction method to analyze the proposed countermeasures and finally solve the optimal solution. Lastly, the simulation results show that the proposed scheme can improve the wireless communication performance under the attacks of jammers compared with conventional schemes.

Intelligent Reflecting Surface Based Passive Information Transmission: A Symbol-Level Precoding Approach

Intelligent reflecting surfaces (IRS) have been proposed as a revolutionary technology owing to its capability of adaptively reconfiguring the propagation environment in a cost-effective and hardware-efficient fashion. While the application of IRS as a passive reflector to enhance the performance of wireless communications has been widely investigated in the literature, using IRS as a passive transmitter recently is emerging as a new concept and attracting steadily growing interest. In this paper, we propose two novel IRS-based passive information transmission systems using advanced symbol-level precoding. One is a standalone passive information transmission system, where the IRS operates as a passive transmitter serving multiple receivers by adjusting its elements to reflect unmodulated carrier signals. The other is a joint passive reflection and information transmission system, where the IRS not only enhances transmissions for multiple primary information receivers (PIRs) by passive reflection, but also simultaneously delivers additional information to a secondary information receiver (SIR) by embedding its information into the primary signals at the symbol level. Two typical optimization problems, i.e., power minimization and quality-of-service (QoS) balancing, are investigated for the proposed IRS-based passive information transmission systems. Simulation results demonstrate the feasibility of IRS-based passive information transmission and the effectiveness of our proposed algorithms, as compared to other benchmark schemes.

Implementation of Sparse Techniques for MIMO Channel Estimation

Channel estimation plays a very important role on the performance of wireless communication systems.Channel estimation can be carried out in different ways: with or without the help of a parametric model, using frequency and/or time correlation properties in the wireless channel, blind methods or those based on training pilots, adaptive or non-adaptive methods. As more antennas are added to Multiple Input Multiple Output (MIMO) system more computational resources and power are required. There is a need to address this problem of the overhead in training symbol based models for channel estimation. Compressed Sensing (CS) algorithms are beneficial in addressing these limitations in the system to increase the spectral efficiency can help free up resources and prevent additional taxing on the hardware. Compressed sensing the pilot symbols by using CS algorithms like OMP, SP, and CoSaMP algorithms. The channel coefficients are obtained through LS, MMSE and LMS techniques. Then, a very small amount of frequency-domain orthogonal pilots are used for the accurate channel estimation.The traditional algorithms like LS , MMSE and LMS combined with CS algorithms have better performance at low SNRs compared to conventional techniques alone in terms of computational time complexity and Normalised Mean Square Error(NMSE) performance. There is a halving of pilot symbols used for training by using the CS algorithm. MSE performance is increased with increase in sparsity level. CoSaMP performs better than SP and OMP at low SNRs. With increase in sparsity level after 50K, the performance of SP is comparable to that of CoSaMP. OMP is simple to implement but MSE performance is less and computational time is more compared to SP and CoSaMP.

Optical wireless communication performance enhancement using Hamming coding and an efficient adaptive equalizer with a deep-learning-based quality assessment.

Optical wireless communication (OWC) technology is one of several alternative technologies for addressing the radio frequency limitations for applications in both indoor and outdoor architectures. Indoor optical wireless systems suffer from noise and intersymbol interference (ISI). These degradations are produced by the wireless channel multipath effect, which causes data rate limitation and hence overall system performance degradation. On the other hand, outdoor OWC suffers from several physical impairments that affect transmission quality. Channel coding can play a vital role in the performance enhancement of OWC systems to ensure that data transmission is robust against channel impairments. In this paper, an efficient framework for OWC in developing African countries is introduced. It is suitable for OWC in both indoor and outdoor environments. The outdoor scenario will be suitable to wild areas in Africa. A detailed study of the system stages is presented to guarantee the suitable modulation, coding, equalization, and quality assessment scenarios for the OWC process, especially for tasks such as image and video communication. Hamming and low-density parity check coding techniques are utilized with an asymmetrically clipped DC-offset optical orthogonal frequency-division multiplexing (ADO-OFDM) scenario. The performance versus the complexity of both utilized techniques for channel coding is studied, and both coding techniques are compared at different coding rates. Another task studied in this paper is how to perform efficient adaptive channel estimation and hence equalization on the OWC systems to combat the effect of ISI. The proposed schemes for this task are based on the adaptive recursive least-squares (RLS) and the adaptive least mean squares (LMS) algorithms with activity detection guidance and tap decoupling techniques at the receiver side. These adaptive channel estimators are compared with the adaptive estimators based on the standard LMS and RLS algorithms. Moreover, this paper presents a new scenario for quality assessment of optical communication systems based on the regular transmission of images over the system and quality evaluation of these images at the receiver based on a trained convolutional neural network. The proposed OWC framework is very useful for developing countries in Africa due to its simplicity of implementation with high performance.

On the Performance Analysis of RIS-Empowered Communications Over Nakagami-m Fading

In this letter, we study the performance of wireless communications empowered by Reconfigurable Intelligent Surface (RISs) over Nakagami- m fading channels. We consider two phase configuration designs for the RIS, one random and another one based on coherent phase shifting. For both phase configuration cases, we present single-integral expressions for the outage probability and the bit error rate of binary modulation schemes, which can be efficiently evaluated numerically. In addition, we propose accurate closed-form approximations for the ergodic capacity of the considered system. For all considered metrics, we have also derived simple analytical expressions that become tight for large numbers of RIS reflecting elements. Numerically evaluated results compared with Monte Carlo simulations are presented in order to verify the correctness of the proposed analysis and showcase the impact of various system settings.

Intelligent Equalization Based on RBF LSSVM and Adaptive Channel Decoding in Faster-than-Nyquist Receiver

On one hand, aiming at the prominent problem of improving the reliability of Faster-than-Nyquist (FTN) wireless transmission, abandoning the channel estimation, we propose the Radial Basis Function Least Squares Support Vector Machine (RBF LSSVM) algorithm based on Intelligent Signal Processing for FTN equalization and form FTN time domain transverse filter equalizer. The model of FTN wireless communication system based on equalization of LSSVM algorithm is established by adding 50-bit training sample sequence module. On the other hand, in the FTN transmission BPSK modulation system receiving terminal, we propose joint research equalization of LSSVM algorithm and adaptive channel decoding scheme of Chase algorithm, to improve the reliable transmission performance of FTN wireless communication. The threshold value is 20, and the adaptive 2-D Turbo Product Codes (TPC) encoding and decoding is simulated by four iterations. The BER performance of FTN wireless communication combined with LSSVM algorithm and TPC adaptive decoding is simulated.

Mobility models for next generation wireless mesh network

<span>Wireless mesh network (WMN) is a new trend in wireless communication promising greater flexibility, reliability, and performance over traditional wireless local area network (WLAN). Test bed analysis and emulation plays an essential role in valuation of software defined wireless network and node mobility is the prominent feature of next generation software defined wireless network. In this study, the mobility models employed for moving mobile stations in software defined wireless network are explored. Moreover, the importance of mobility model within software defined wireless mesh network for enhancing the performance through handover-based load balancing is analyzed. The mobility models for the next generation software defined wireless network are explored. Furthermore, we have presented the mobility models in the mininet-Wi-Fi test bed, and evaluated the performance of Gauss Marko’s mobility model.</span>