Communication Quality Of Service Research Articles

Research on multi-layer network topology optimization strategy for railway internet of things based on game theory benefits

In the railway system environment, the interconnection of a vast array of intelligent sensing devices has brought about revolutionary changes in the management and monitoring of railway transportation. However, this also poses challenges to the communication service quality within the railway Internet of Things (IoT). Through collective intelligence and collaboration, the nodes within the railway IoT can not only share data and information but also work synergistically to enhance the overall intelligence level and improve decision-making quality of the network. Therefore, this paper proposes a reconnection mechanism based on the computation of node game-theoretic benefits and optimizes this process with the concept of swarm intelligence collaboration. Initially, the game-theoretic benefit values of the nodes in the railway IoT network are calculated. Subsequently, based on the weight priority of the edges, the two edges with the larger weights are selected, and connections are established between nodes with similar game-theoretic benefit values to enhance the network’s robustness. This approach enables rapid networking and efficient communication transmission within the railway IoT, providing robust assurance for the safe and stable operation of the railway.

Transforming the Judiciary: Unveiling the Influence of Interpersonal Communication on Indonesia's Court System

Public service in government institutions, particularly in one of court in Indonesia, has become the primary focus in addressing negative stigma and public complaints related to service performance and efficiency. During the pandemic, technology integration emerged as a solution, with the execution of the comprehensive One-Stop Integrated Service Program (PTSP) and drive-thru services at one of the courts in Indonesia. This research aims to measure the influence of interpersonal communication between officers and lawyers on service quality in PTSP and drive-thru services, as well as to identify the role of technology in these processes. The research methodology employs multiple regression analysis to comprehend the cause-and-effect relationship between interpersonal communication variables and service quality. Focusing on openness, empathy, supportive attitude, positive attitude, and equality, this study also considers the impact of organizational culture and the role of lawyers as key stakeholders. The expected results aim to provide recommendations for enhancing public services at one of the courts in Indonesia, including technology development, staff training, and organizational culture changes. The research hypothesis states that interpersonal communication significantly influences service quality at the court. The findings of this research are intended to contribute to a deeper understanding of the dynamics of public service in government institutions.

Joint user association, service caching, and task offloading in multi-tier communication/multi-tier edge computing heterogeneous networks

Due to the wide range of intensive computational applications and ubiquitous connectivity of the Internet of Things (IoT) paradigms, it has become crucial to develop a new platform that can achieve low delay, high network throughput, and enhanced quality of service (QoS). This paper proposes a joint user association, service caching, and task offloading strategy to reduce delay and enhance users’ QoS in multi-tier communication and multi-tier edge computing heterogeneous networks (HetNets). The considered system model consists of multi-users with different tasks and service data sizes communicating in a heterogeneous network of one massive multiple-input multiple-output (M-MIMO) macro base station and some small base stations. The proposed work investigates user association, power allocation, optimum service data caching, and task offloading strategies at the computing network edges. Thereby, the objectives of this work are to propose an efficient framework to reduce the system delay, increase the network throughput, and meet the user requirements in multi-tier communication and multi-tier edge computing heterogeneous networks. The simulation results show that the proposed algorithm outperforms the state-of-the-art with a 49.48% decrease in system delay, 80% reduction in cost and hardware complexity in terms of the reduced number of installed antennas, and 48.58% enhancement in the network throughput.

Robust Beamforming for Downlink Multi-Cell Systems: A Bilevel Optimization Perspective

Utilization of inter-base station cooperation for information processing has shown great potential in enhancing the overall quality of communication services (QoS) in wireless communication networks. Nevertheless, such cooperations require the knowledge of channel state information (CSI) at base stations (BSs), which is assumed to be perfectly known. However, CSI errors are inevitable in practice which necessitates beamforming technique that can achieve robust performance in the presence of channel estimation errors. Existing approaches relax the robust beamforming design problems into semidefinite programming (SDP), which can only achieve a solution that is far from being optimal. To this end, this paper views robust beamforming design problems from a bilevel optimization perspective. In particular, we focus on maximizing the worst-case weighted sum-rate (WSR) in the downlink multi-cell multi-user multiple-input single-output (MISO) system considering bounded CSI errors. We first reformulate this problem into a bilevel optimization problem and then develop an efficient algorithm based on the cutting plane method. A distributed optimization algorithm has also been developed to facilitate the parallel processing in practical settings. Numerical results are provided to confirm the effectiveness of the proposed algorithm in terms of performance and complexity, particularly in the presence of CSI uncertainties.

Speech Inpainting Based on Multi-Layer Long Short-Term Memory Networks

Audio inpainting plays an important role in addressing incomplete, damaged, or missing audio signals, contributing to improved quality of service and overall user experience in multimedia communications over the Internet and mobile networks. This paper presents an innovative solution for speech inpainting using Long Short-Term Memory (LSTM) networks, i.e., a restoring task where the missing parts of speech signals are recovered from the previous information in the time domain. The lost or corrupted speech signals are also referred to as gaps. We regard the speech inpainting task as a time-series prediction problem in this research work. To address this problem, we designed multi-layer LSTM networks and trained them on different speech datasets. Our study aims to investigate the inpainting performance of the proposed models on different datasets and with varying LSTM layers and explore the effect of multi-layer LSTM networks on the prediction of speech samples in terms of perceived audio quality. The inpainted speech quality is evaluated through the Mean Opinion Score (MOS) and a frequency analysis of the spectrogram. Our proposed multi-layer LSTM models are able to restore up to 1 s of gaps with high perceptual audio quality using the features captured from the time domain only. Specifically, for gap lengths under 500 ms, the MOS can reach up to 3~4, and for gap lengths ranging between 500 ms and 1 s, the MOS can reach up to 2~3. In the time domain, the proposed models can proficiently restore the envelope and trend of lost speech signals. In the frequency domain, the proposed models can restore spectrogram blocks with higher similarity to the original signals at frequencies less than 2.0 kHz and comparatively lower similarity at frequencies in the range of 2.0 kHz~8.0 kHz.

Multicriteria and Quality of Service- Aware Vertical Handover Solution for Vehicle-to-Infrastructure Communication in Multitier Heterogeneous Networks.

The growing integration of vehicle-to-infrastructure (V2I) communication within multitier heterogeneous networks (HetNets) introduces challenges in maintaining seamless connectivity and Quality of Service (QoS) for vehicular users. This paper introduces a modified Multicriteria and QoS-aware Vertical Handover Decision Algorithm (mV2I-MHA) tailored to address these challenges. By considering multiple criteria - such as packet loss ratio, cost, available bandwidth and packet latency - the proposed solution intelligently manages vertical handovers between different network tiers. Numerous Multi-Criteria Decision-Making (MCDM) techniques have been proposed to address the right target network selection aiming to reduce unnecessary handovers, incorrect network selections and the associated processing time. However, many of these solutions overlook the significance of varying criteria weights in vertical handover decisions made by their selection algorithms. Through comprehensive simulations and comparisons with existing techniques, the effectiveness of the proposed – in this paper - solution is demonstrated in enhancing handover success rate, reducing handover failure rate, minimizing latency, and overall elevating the QoS for V2I communication in multitier HetNets. MATLAB R2020a was utilized to simulate the work. Using packet latency and handover failure as the metrics for performance, the results were contrasted with those of an existing works in terms of handover failure rate and packet delay. The developed mV2I-MHA showed considerable percentage reductions of 10.5% and 23.9% in packet latency and handover failure rate, respectively.

Evaluation Model of Supervision of Service Quality of The Final Paper in The Management Study Program, Faculty of Economics and Business, Ahmad Dahlan University

This research aimed to test influence between service quality, student satisfaction also interaction between service quality and student satisfaction in the building word of mouth communication. Research conducted by Department of Management, Faculty of Economics and Business, University Ahmad Dahlan. Sample categorized with sampling convenience method and purposive sampling. Data collection efforted by giving list of question to the respondent that is contains about service quality, student satisfaction and word of mouth communication. This research use Moderator Regression Analysis. In the other side, T test and F test are used to test asked hypothesis. The result of partially regression coefficient test with T test shows that service quality, student satisfaction, interaction between them influence significantly to word of mouth communication. In the other side coefficient regression test’s result shows that variables of service quality student’s satisfaction also interaction between them both influence to word of mouth communication. Variables of service quality and student’s satisfaction are able to explain word of mouth communication variable up to 78,2% and the rest is 21,8% caused by another variable that is not included in the research model

Joint design of transmit precoding and antenna selection for multi-user multi-target MIMO DFRC

Dual-function radar and communications (DFRC) systems based on multiple-input multiple-output (MIMO) arrays have received considerable attention in recent years due to their excellent ability to alleviate spectrum congestion. The MIMO DFRC systems enable high-resolution detection of multiple targets while communicating with multiple users simultaneously. However, MIMO arrays require numerous radio frequency (RF) units and suffer a strong mutual coupling among antennas, resulting in significant system overhead and performance degradation, respectively. In light of this, this paper investigates the joint optimization of transmit precoding and antenna selection for MIMO DFRC systems, aiming to improve the angular ambiguity function with a guaranteed communication quality of service (QoS) using a small number of antennas. To address the resultant non-convex optimization problem, both the indirect and direct precoding methods are proposed. In the former, the waveform covariance and antenna selection vector are first jointly optimized via a promoted sparsity along the covariance diagonal, followed by the precoding matrix indirectly derived from the optimal covariance. In the latter, the precoding matrix is directly optimized via an imposed group sparsity under the communication QoS and power constraints. Simulation results demonstrate that the proposed sparse MIMO DFRC system with fewer active antennas can achieve comparable dual-functional performance to that of the full array system.

Hizmet Kalitesinin Ağızdan Ağza İletişime Etkisi Çalışmalarına Yönelik Meta Analiz

Service quality refers to how effectively and satisfactorily a service meets customer expectations. This is based on factors such as the manner in which the service is provided, the level of satisfaction, conformity to customer needs, and the ability to exceed expectations. High-quality service adds value to customers, provides reliability, and supports long-term customer relationships. Word of mouth communication is a form of oral communication that occurs between individuals. It is a means by which individuals share information, feelings, or thoughts through oral communication tools such as face-to-face conversations, phone calls, and voice messages. The aim of this study is to bring together studies examining the relationship between service quality and word of mouth communication, conduct a reanalysis using meta-analysis, and make a significant contribution to the literature. The study data were obtained through a national and international literature review, and a total of 15 studies and 4600 samples were reached between 2011 and 2022, with specific limitations. The effect size (ES) obtained for the relationship between service quality and word of mouth communication through meta-analysis applied in the Jamovi program was determined as 0.569. The results indicate a high level of relationship between the two variables. Key Words: Word of Mouth Communication, Meta-Analysis, Service Quality, Communication, Service

Handover Analysis Of 4G LTE (Long Term Evolution) At A Frequency Of 2400 Mhz

Information technology has now become a primary need for many individuals, facilitating access to various needs, including work, learning, and other activities. Mobile phones allow users to stay connected to the internet without interruption, even when traveling out of town, thanks to their ability to switch between cells or through a process known as handover. The focus of this article is on the impact of handover on 4G LTE networks. The data collection approach in this research uses the drive test method by utilizing the tems pocket application to retrieve internet network data. The research results highlight the importance of understanding how handover can affect 4G LTE network performance. With the role of information technology increasingly dominating everyday life, a deep understanding of technical aspects such as handover has become essential to maintaining the quality and efficient availability of cellular communications services.

Unimodular Waveform Design for the DFRC System with Constrained Communication QoS

In this study, we investigated two waveform design problems for a dual-functional radar communication (DFRC) system, taking into consideration different constrained communication quality-of-service (QoS) requirements. Our objective was to minimize the mean-square error (MSE) of radar beampattern matching as the cost function. To this end, the multi-user interference (MUI) energy constraint and constructive interference (CI) constraint were, respectively, formulated to ensure the communication QoS. It is important to note that we designed a strict per-user MUI energy constraint at each sampling moment to achieve more accurate control over communication performance. Additionally, we introduced a constant-modulus constraint to optimize the efficiency of the radio frequency (RF) amplifier. To tackle the nonconvex waveform design problems encountered, we employed the alternative direction methods of multipliers (ADMM) technique. This allowed us to decompose the original problem into two solvable subproblems, which were then solved using the majorization–minimization (MM) method and geometrical structure. Finally, we obtained extensive simulation results which demonstrate the effectiveness and superiority of the proposed algorithm.

Vehicular Connectivity on Complex Trajectories: Roadway-Geometry Aware ISAC Beam-Tracking

In this paper, we propose sensing-assisted beamforming designs for vehicles on arbitrarily shaped roads by relying on integrated sensing and communication (ISAC) signalling. Specifically, we aim to address the limitations of conventional ISAC beam-tracking schemes that do not apply to complex road geometries. To improve the tracking accuracy and communication quality of service (QoS) in vehicle to infrastructure (V2I) networks, it is essential to model the complicated roadway geometry. To that end, we impose the curvilinear coordinate system (CCS) in an interacting multiple model extended Kalman filter (IMM-EKF) framework. By doing so, both the position and the motion of the vehicle on a complicated road can be explicitly modeled and precisely tracked attributing to the benefits from the CCS. Furthermore, an optimization problem is formulated to maximize the array gain by dynamically adjusting the array size and thereby controlling the beamwidth, which takes the performance loss caused by beam misalignment into account. Numerical simulations demonstrate that the roadway geometry-aware ISAC beamforming approach outperforms the communication-only-based and ISAC kinematic-only-based technique in tracking performance. Moreover, the effectiveness of the dynamic beamwidth design is also verified by our numerical results.

Dynamic redeployment of UAV base stations in large-scale and unreliable environments

The deployment of Unmanned Aerial Vehicles (UAVs) as aerial base stations (UAV-BSs) has emerged as a promising solution to enhance communication services provided to ground users. However, deploying UAV-BSs faces challenges including the cooperation of multiple UAVs, dynamic user distribution, low-reliability issues of UAVs, and efficient redeployment in large environments. Existing literature addresses some of these challenges but lacks a comprehensive approach. In this paper, we investigate all these challenges and propose a novel deployment framework with the objective of maximizing the quality of communication service by dynamically deploying UAV-BSs. The proposed framework employs a decentralized approach, allowing UAV-BSs to locally adjust their locations and rapidly respond to changes, thus ensuring stable and efficient service supply to ground users. In addition, we implement multiple simulation experiments to evaluate the performance of the proposed framework in solving the UAV-BSs redeployment problem in large and dynamic environments. The results demonstrate its ability to effectively improve the quality of communication services.

INVESTIGATING THE EFFECT OF INTERNET BANKING QUALITY DURING AND AFTER THE PANDEMIC: A COMPARATIVE ANALYSIS

This study aims to analyze the quality of Internet Banking services and their impact on customer satisfaction at State Owned Banks in Bandung before and after the COVID-19 pandemic. The seven independent variables used are response speed, data security, ease of use, user interface quality, accessibility, service availability, service quality, and information and communication technology, while the dependent variable is customer satisfaction. The survey method was used to collect data from 100 respondents who are customers of State-Owned Banks in Bandung. Multiple regression analysis was carried out to determine the relationship between the independent variable and the dependent variable accompanied by a different test. The results showed that Internet Banking Service Quality during and after the Covid 19 Pandemic period had a positive and significant effect simultaneously, while partially only the Service Quality and Information and Communication Technology variables had a positive and significant effect during and after Covid 19, while other variables had a positive effect but not significant. In addition, this study also concluded that there was a decrease in the Information and Communication Technology and Service Quality variables after the pandemic compared to during the pandemic from customer perceptions. The implication is that in the New Normal era, apart from the two dominant aspects mentioned above, there are indications that State Owned Bank is trying to improve its service quality through other variables to increase customer satisfaction.

Context-Aware Vertical Handoff Algorithms for IoT-enabled Environments

-The proliferation of Internet of Things (IoT) devices has ushered in a paradigm shift in the way we interact with our surroundings. As these devices seamlessly exchange data across heterogeneous networks, maintaining uninterrupted connectivity and optimal quality of service (QoS) becomes a paramount concern. The process of vertical handoff, which facilitates the seamless transfer of communication sessions between different networks, is of particular significance in this dynamic IoT landscape. This research paper delves into the realm of "Context-Aware Vertical Handoff Algorithms for IoT-enabled Environments," aiming to harness the power of context-awareness to enhance the efficacy of vertical handoff decisions in IoT scenarios. The introduction highlights the intricate network challenges posed by IoT's diverse devices and applications. These challenges necessitate the development of innovative solutions that can adapt to varying communication technologies, device constraints, and QoS demands. The focal point of this exploration lies in the integration of context-awareness into vertical handoff algorithms. Context-awareness leverages real-time contextual information, encompassing factors such as device location, network conditions, application requirements, and user preferences, to make informed handoff decisions that align with the unique demands of each IoT situation. Drawing from the wellspring of context- aware computing, the paper delves into the mechanics of context-aware vertical handoff algorithms. It explores their attributes and capabilities, shedding light on how these algorithms leverage context to optimize handoff decisions. The paper discusses the diversity of International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 07 Issue: 09 | September - 2023 SJIF Rating: 8.176 ISSN: 2582-3930 © 2023, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM25730 | Page 2 context-aware algorithms, including fuzzy logic- based, machine learning-driven, and rule-based approaches, and their adaptability to the distinct challenges posed by IoT environments. As the IoT landscape brings forth its own set of challenges, the paper addresses considerations like limited resources, heterogeneous data, and intermittent connectivity. It delves into the spectrum of algorithm types and approaches that align with the IoT's intricacies, ensuring that vertical handoff decisions resonate with the unique characteristics of IoT devices. In the quest to gauge the effectiveness of context-aware vertical handoff algorithms in IoT scenarios, the paper outlines a comprehensive methodology for performance evaluation. This methodology involves defining IoT-centric performance metrics, such as data delivery reliability, energy efficiency, latency, and adaptive decision-making, which accurately capture the impact of context-awareness on QoS enhancement and device efficiency. Through practical case studies, the paper demonstrates how context-aware vertical handoff algorithms find application across various IoT domains, from smart cities to healthcare. It unveils how these algorithms address the dynamic challenges presented by real- world scenarios, where devices navigate between heterogeneous networks and diverse application requirements. Keywords: IoT ,QoS, LPWAN,

An Overview on On-chip Network Routing Optimisation

As the number of cores in multi-core systems increases, bus-based systems face significant challenges in terms of scalability, average transmission latency and power consumption. In this context, on-chip networks emerged as a suitable communication architecture for System On Chip (SoC) based entirely on the communication ideas in computer networks and taking into account the characteristics of the system on chip in SoCs. With the introduction of on-chip networks, related research has been developed, such as on-chip network topology, communication quality of service, on-chip network routing algorithms, and on-chip network fault tolerance. He then introduces on-chip network routing algorithms and fault-tolerant routing algorithms from different perspectives, and finally points out the directions of fault-tolerant routing algorithms worthy of research.

Optimization of Quality of AI Service in 6G Native AI Wireless Networks

To comply with the trend of ubiquitous intelligence in 6G, native AI wireless networks are proposed to orchestrate and control communication, computing, data, and AI model resources according to network status, and efficiently provide users with quality-guaranteed AI services. In addition to the quality of communication services, the quality of AI services (QoAISs) includes multiple dimensions, such as AI model accuracy, overhead, and data privacy. This paper proposes a QoAIS optimization method for AI training services in 6G native AI wireless networks. To improve the accuracy and reduce the delay of AI services, we formulate an integer programming problem to obtain proper task scheduling and resource allocation decisions. To quickly obtain decisions that meet the requirements of each dimension of QoAIS, we further transform the single-objective optimization problem into a multi-objective format to facilitate the QoAIS configuration of network protocols. Considering the computational complexity, we propose G-TSRA and NSG-TSRA heuristic algorithms to solve the proposed problems. Finally, the feasibility and performance of QoAIS optimization are verified by simulation.

Energy-efficient power control strategy of the delay tolerable service based on the reinforcement learning

In recent years, the rapid development of Internet technology and its applications has led to an exponential growth in the number of Internet users and wireless terminal devices, resulting in a corresponding increase in energy consumption. This has necessitated the need to reduce energy consumption while maintaining the quality of communication services. To this end, we investigate the possibility of improving energy efficiency (EE) of delay tolerable (DT) services by allocating resources based on the time-domain water-filling algorithm. We first transform the non-convex problem of maximizing EE into a convex problem of minimizing transmission power to obtain the optimal solution, and then use the greedy algorithm to obtain an upper bound. Furthermore, to capture a more realistic scenario, an Approximate Statistical Dynamic Programming (ASDP) algorithm is introduced, but its effect on enhancing EE is limited. To overcome this limitation, three Deep Reinforcement Learning (DRL) algorithms are implemented. The simulations results show that the settings of maximum transmit power and SNR during agent training have an impact on the performance of the agent. Finally, by comparing the mean values of transmission power, outage probability, equilibrium power and performance improvement percentage of several algorithms, we conclude that the Deep Deterministic Policy Gradient (DDPG) algorithm produces the best agent performance in the environment with a fixed SNR of 2 (dB).

Physical Layer Security Performance Analysis for Relay-Aided Visible Light Communication System

The risk of information leakage increases when the relay technology is introduced to extend the communication range and improve the quality of communication services of cell-edge users in visible light communication (VLC) systems. To evaluate these security risks, physical layer security (PLS) performance for decode-and-forward (DF) relay-aided VLC system is investigated in this paper. Specifically, the theoretical expressions of the upper and lower bounds of the security outage probability (SOP) for the DF relay-aided VLC system under the amplitude constraint are obtained based on a stochastic geometry analysis method. Monte Carlo simulation validates the correctness of the derived theoretical expressions of the upper and lower bounds of the SOP. Moreover, simulation results show that the security outage performance of the DF relay-aided VLC system is deteriorated compared with the non-relay VLC system. Furthermore, the influences of the eavesdroppers' distribution density, the radiation radius of LED source, the radiation radius and deployment height of the relay on the SOP have been investigated. Last but not least, the optimal deployment height of the relay can be determined for achieving the optimum security outage performance. These parameters can effectively guide the design of the secure relay-aided VLC system.

Unsuspicious User Enabled Proactive Eavesdropping in Interference Networks Using Improper Gaussian Signaling

Proactive eavesdropping is an effective approach to improve the performance of wireless information surveillance, where suspicious users are legitimately eavesdropped by authorized monitors. For the situation when no monitor is available, we propose to authorize unsuspicious users to surveil suspicious users provided that the quality-of-service (QoS) of unsuspicious users is guaranteed. This paper considers an interference network consisting of a suspicious-transmitter (STx)/suspicious-receiver (SRx) pair and an unsuspicious-transmitter (UTx)/unsuspicious-receiver (URx) pair. We assume that URx acts as a monitor to eavesdrop the suspicious communication, and UTx adopts improper Gaussian signaling (IGS) for flexibly managing the interference to SRx. The QoS of the unsuspicious communication is guaranteed by enforcing its outage performance to be higher than a desirable level. The problem of optimizing the transmit power and the IGS circularity coefficient of UTx to maximize the average eavesdropping rate is optimally solved by the Lagrange duality method. Theoretical results show that IGS is effective when the eavesdropping is successful and the unsuspicious communication is in non-outage status. Simulation results confirm that the proposed design works well even when no additional outage of the unsuspicious communication is allowed, and show that IGS can greatly outperform proper Gaussian signaling in most cases.