Telecommunication Systems最新文献

This paper proposes the height-dependent channel correlation coefficient and leverages it to produce a hybrid correlated channel. The efficacy of the drone-assisted cooperation (DAC) system has been assessed using the hybrid correlated channel coefficient, and the findings are contrasted with those obtained using the uncorrelated hybrid channel coefficient. Maximal ratio combining (MRC), a diversity combining technique, is employed at the destination node. Amplify-and-forward (AF) and decode-and-forward (DF) are utilized at the relay node (drone) to assess the overall performance of the DAC system in the proposed scenario. The paper introduces two algorithms designed to calculate the capacity and outage probability for DAC systems within a correlated hybrid channel environment. Finally, the effectiveness of the proposed model has been depicted in the simulation results. The proposal might prove helpful in a dire situation where the base station faces disruptions.

Abstract

This paper presents a multi-relay Coded-Cooperative system that integrates Hybrid Automatic Repeat Request and Coded Cooperative Cooperation. It utilizes powerful cyclic Totally Decomposed Cumulative Goppa codes (TDCG codes) known for exceptional performance as best-known linear codes. The destination code is jointly designed by combining TDCG codes from relay and source codes. Optimized relay channel codes improve overall system bit-error-rate performance, aided by a proposed optimization technique. Numerical simulations assess BER performance under various channel conditions with BPSK modulation and coherence detection over flat Rayleigh fading channels. Results show that the TDCG coded-cooperative scheme outperforms non-cooperative approaches and similar coded cooperation techniques with comparable code rates. The integration of HARQ and Coded Cooperative Cooperation enhances wireless communication system reliability and efficiency.

Random Linear Network Coding (RLNC) is well-known to provide high throughput and low latency for vast communication networks. However, RLNC often suffers from high coefficients overhead, specifically, when it’s applied to limited resource or short-packet networks. Herein, the problem of RLNC coefficients vector overhead is revisited. A novel framework, based on modular arithmetic and prime numbers, and influenced by the Chinese remainder theorem (CRT), is proposed to reduce the coefficients overhead by augmenting only a tiny one item coefficient instead of the entire coefficients vector. The proposed method successfully addresses all the shortcomings of previous methods, including restrictions on generation size and packet density, recoding on intermediate nodes, and creating innovative coding vectors. Theoretical analysis and experimental demonstrate the superior performance of the proposed scheme in terms of coefficients overhead ratio, download time, throughput, and packet drop rate. This evaluation has considered two types of networks: wireless sensors network for Internet of things, and conventional wireline Ethernet.

The constant growth in the demand for communication services has implied an increase the transmitted data rate and bandwidth. Optical satellite communications have provided a solution to this problem, allowing to increase exponentially the transfer rate between the ground station and an in-orbit satellite. However, although this technology offers numerous advantages, such as higher bandwidth, lower power consumption, narrower beam width, as well as greater simplicity of development, when the transmitted light signal passes through the atmosphere it experiences attenuation and fluctuations due to atmospheric turbulence. In this work, optical power fluctuations are modelled by means of a Gamma-Gamma optical turbulence model, so strong turbulence conditions are established according to Rytov’s turbulence theory, considering a measure of the intensity of the optical turbulence when extended to strong fluctuation conditions, depending on the zenith angle variations from 0(^circ ) to 60(^circ ). Finally, the performance evaluation of BPSK and OOK modulation schemes for conditions with variations of pointing angle, based on atmospheric attenuation, signal scattering and absorption is given. The results show better performance of the modulation schemes at low zenith pointing angles and wavelengths of 1550 nm, over 850 nm and 1064 nm. Moreover, BPSK modulation shows to be able to provide lower bit error (BER) values for a given signal-to-noise ratio, outperforming OOK modulation scheme in this sense.

Reconfigurable intelligent surface (RIS) is a novel technology that can help enhance the wireless propagation environment by altering the electromagnetic properties of its massive low-cost passive reflecting elements. This paper aims to explore the mechanism of how the deployment of RIS influences cell coverage from the system level and to obtain valuable guidance for actual RIS deployment design. We derive the coverage area gain (CAG) brought by deploying RIS to the whole system and analyze how the deployment parameters influence performance. The results reveal that it is more favorable to deploy the RIS close to the base station (BS) to gain more long-range coverage, and the coverage area gain can keep approximately constant as long as the ratio of the RIS element number to the deployment distance (between the BS and the RIS) remains unchanged. The scaling law between the CAG and the ratio is obtained. Furthermore, we extend the analysis to the scenario with two RISs deployed and respectively derive the coverage area gains brought by the two RISs when they are symmetrically and vertically deployed. We find that the aforementioned ratio rule still holds here, and the vertical deployment can achieve higher CAG than the symmetric deployment.

Abstract

Studies on the delay characteristics under the Internet macro-topology provides a reference for resolving the real-time performance issue of the data transmission of Internet devices. With the overall advancement of IPv6 Internet deployment, the changes in network structure and paths will generate different degrees of delay. In this context, a comparative analysis of the behavioral characteristics of IPv4 and IPv6 network delay was performed in this study. We selected the sampled data of valid paths located at four monitors on different continents under the CAIDA_Ark project to obtain statistics for the network delay and communication diameter on the IPv4 and IPv6 Internet and found that their correlation was extremely weak. Furthermore, the communication diameter on IPv6 Internet was slightly shorter than that on IPv4 Internet. The network delay exhibited a bimodal or multimodal heavy-tailed distribution. The network delay and maximum link delay for IPv4 and IPv6 Internet were strongly correlated, indicating that the bottleneck delay affects the relationship between the network delay and communication diameter. Next, we analyzed the relationship between network delay and bottleneck delay for IPv4 and IPv6 Internet and found that bottleneck delay has a more significant impact on the network delay on the valid paths for IPv4 Internet than for IPv6 Internet. After mapping the IP addresses at both ends of the bottleneck delay to the Autonomous Systems (ASes), we found that the bottleneck delay on the valid paths for the IPv4 Internet was mostly distributed in the intra-AS, whereas it was in the inter-AS for the IPv6 Internet. Finally, we analyzed the factors affecting bottleneck delay and found that propagation delay in the long-distance range is an important factor (L > 4000 km on IPv4 Internet and L > 7000 km on IPv6 Internet). In addition, for IPv4 Internet, queuing delay is an important factor affecting bottleneck delay, whereas in the process of data communication on the IPv6 Internet, the impact of propagation and queuing delays on the bottleneck delay is weakened.

Smart agriculture is an emerging concept that helps modern farm management using technologies such as the Internet of Things (IoT), robotics, drones, and artificial intelligence, so that this leads to an increase in the quantity and quality of farm products and optimization of human resources. Efforts have been made in the past to control pests and plant diseases, and this has led to an increase in agricultural products. Control and prevention of crop diseases is the least expensive method of pest control, which also has good results in reducing insect pests. This study develops a crop pest control system based on IoT technology, which includes two parts: (1) hardware as a plant protection machine, and (2) software as an information management system. Here, light trap technology and ozone sterilization are incorporated in the proposed system to control insect pests and diseases of agricultural crops. The information management system consists of IoT technology and a mobile app, which provides remote control capability. In this system, several IoT-based sensor devices are responsible for collecting environmental information in real time. The basic routing protocol for the system implementation is Open Shortest Path First . We present a fuzzy logic-based method for energy-aware routing. We proved the effectiveness of the proposed system through implementation on a greenhouse facility.

Abstract

Spectrum sharing provides a rapid migration pathway toward 5G by enabling the coexistence of 4G LTE and 5G new radio (NR) that share the same spectrum. Due to significant differences in the LTE and 5G-NR air interfaces, several enablers are required to facilitate the spectrum sharing. In this study, we explore the coexistence features and investigate their impacts on network performance. For static and dynamic spectrum sharing scenarios, we assess the impacts of different spectrum sharing ratios, user ratios, MIMO configurations, mixed numerology profiles and traffic patterns on the user throughput and network capacities of spectrum sharing networks, compared with the LTE only and 5G-NR only networks with exclusive spectrum access. The key results show that spectrum sharing leads to a marginal capacity gain over LTE only network and achieves considerably lower capacity than the 5G-NR only network. Also, the results show that mixed numerology profiles between the LTE and 5G-NR lead to capacity losses due to inter-numerology interference. In addition, user and spectrum sharing ratios between LTE and 5G-NR have critical impacts on performance. Reduced spectrum per device as the number of 5G devices increases, higher signaling overhead and higher scheduling complexity are other limiting factors for spectrum sharing networks. The results show limited capacity benefits and reinforce spectrum sharing between LTE and 5G-NR as mainly an evolutionary path to accommodate 5G users in the same LTE spectrum while migrating to the fully-fledged 5G networks. For significant capacity increase, other features such as carrier aggregation, overlay of small cells and higher order MIMO would need to be incorporated into the network.

With the increasing use of cloud storage for sensitive and personal information, ensuring data security has become a top priority. It is important to prevent sensitive data from being identified by unauthorized users during the distribution of cloud files. The main aim is to transmit the data in a secured manner without encrypting the entire file. Hence a novel design for remote data integrity auditing and data sanitizing that enables users to access files without revealing sensitive information. Our approach includes identity-based shared data integrity auditing, which is performed using different zero-knowledge proof protocols such as ZK-SNARK and ZK-STARK. We also propose a pinhole-imaging-based learning butterfly optimization algorithm with a lightweight convolutional neural network (PILBOA-LCNN) technique for data sanitization and security. The LCNN is used to identify sensitive terms in the document and safeguard them to maintain confidentiality. In the proposed PILBOA-LCNN technique, key extraction is a critical task during data restoration and sanitization. The PILBOA algorithm is used for key optimization during data sanitization. We evaluate the performance of our proposed model in terms of privacy preservation and document sanitization using the UPC and bus user datasets. The experimentation results revealed that the proposed method enhanced recall, F-measure, and precision scores as 90%, 89%, and 92%. It also has a low computation time of 109.2 s and 113.5 s. Our experimental results demonstrate that our proposed model outperforms existing techniques and offers improved cloud data storage privacy and accessibility.

This article focuses on the urgent cybersecurity concerns in the Internet of Things (IoT) environment, highlighting the crucial importance of protecting these networks in the face of increasing amounts of IoT data. The paper explores the intricacies of deploying security mechanisms for Internet of Things (IoT) devices, specifically those that are restricted by limited resources. This study examines the inherent weaknesses in IoT systems and analyses the strategies used by malicious individuals to gain control and privileges. In order to tackle these difficulties, the study suggests a sophisticated security system that combines artificial intelligence and an intelligent attack graph. An outstanding characteristic of the model incorporates a method devised to restrain virus spread and accelerate network restoration by introducing virtual nodes. The research showcases the results of the vulnerable attack path predictor (VAPP) module of the proposed model, emphasising its exceptional accuracy in distinguishing between black (0) and red (1) attack paths compared to alternative Machine Learning techniques. Moreover, a thorough evaluation of the module's performance is carried out, with a specific emphasis on security concerns and predictive capacities. Proverif is utilised to validate the security settings and evaluate the resilience of the secret keys. The findings demonstrate a detection rate of 98.48% and an authentication rate of 85%, outperforming the achievements of earlier studies. The contributions greatly enhance the ability of IoT networks to withstand challenges, and the use of cryptographic verification confirms its dependability in the ever-changing digital environment.