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Vehicle-to-Infrastructure (V2I) communication is expected to bring tremendous benefits in terms of increased road safety, improved traffic efficiency and decreased environmental impact. In 2017, The 3rd Generation Partnership Project (3GPP) released 3GPP Release 14, which introduced Cellular Vehicle-to-Everything communication (C-V2X), bringing Vehicle-to-Everything (V2X) communication capabilities to cellular networks, hence creating an alternative to Dedicated Short-Range Communications (DSRC) technology. Since then, every new 3GPP Release including Release 15, a first full set of 5G standards, offered V2X capabilities. In this paper, we present a complex simulation study, which benchmarks the performance of LTE-based and 5G-based C-V2X technologies deployed for V2I communication in an urban setting. The study compares LTE and 5G deployed both in the Device-to-Device in mode 3 and in infrastructural mode. Target performance indicators used for comparison are average end-to-end (E2E) latency and Packet Delivery Ratio (PDR). The performance of those technologies is studied under varying communication conditions realized by a variation of vehicle traffic intensity, communication perimeter and message generation frequency. Furthermore, the effects of infrastructure deployment density on the performance of selected C-V2X communication technologies are explored by comparing the performance of the investigated technologies for three infrastructure density scenarios, i.e., involving two, four and eight base stations (BSs). The performance results are put into a context of the connectivity requirements of the most popular V2I communication services. The results indicate that both C-V2X technologies can support all the considered V2I services without any limitations in terms of the communication perimeter, traffic intensity and message generation frequency. When it comes to the infrastructure density deployment, the results show that increasing the density of the infrastructure deployment from two BSs to four BSs offers a remarkable performance improvement for all the considered V2I services as well as investigated technologies and their modes. Further infrastructure density increase (from four BSs to eight BSs) does not yield any practical benefits in the investigated urban scenario.

The transmission of massive amounts of small packets generated by access networks through high-speed Internet core networks to other access networks or cloud computing data centres has introduced several challenges such as poor throughput, underutilisation of network resources, and higher energy consumption. Therefore, it is essential to develop strategies to deal with these challenges. One of them is to aggregate smaller packets into a larger payload packet, and these groups of aggregated packets will share the same header, hence increasing throughput, improved resource utilisation, and reduction in energy consumption. This paper presents a review of packet aggregation applications in access networks (e.g., IoT and 4G/5G mobile networks), optical core networks, and cloud computing data centre networks. Then we propose new analytical models based on diffusion approximation for the evaluation of the performance of packet aggregation mechanisms. We demonstrate the use of measured traffic from real networks to evaluate the performance of packet aggregation mechanisms analytically. The use of diffusion approximation allows us to consider time-dependent queueing models with general interarrival and service time distributions. Therefore these models are more general than others presented till now.

This book is an in-depth, systematic and structured technical reference on 3GPP's LTE-Advanced (Releases 10 and 11), covering theory, technology and implementation, written by an author who has been involved in the inception and development of these technologies for over 20 years. The book not only describes the operation of individual components, but also shows how they fit into the overall system and operate from a systems perspective. Uniquely, this book gives in-depth information on upper protocol layers, implementation and deployment issues, and services, making it suitable for engineers who are implementing the technology into future products and services.

Reaching a flat network is the main target of future evolved packet core for the 5G mobile networks. The current 4th generation core network is centralized architecture, including Serving Gateway and Packet-data-network Gateway; both act as mobility and IP anchors. However, this architecture suffers from non-optimal routing and intolerable latency due to many control messages. To overcome these challenges, we propose a partially distributed architecture for 5th generation networks, such that the control plane and data plane are fully decoupled. The proposed architecture is based on including a node Multi-session Gateway to merge the mobility and IP anchor gateway functionality. This work presented a control entity with the full implementation of the control plane to achieve an optimal flat network architecture. The impact of the proposed evolved packet Core structure in attachment, data delivery, and mobility procedures is validated through simulation. Several experiments were carried out by using NS-3 simulation to validate the results of the proposed architecture. The Numerical analysis is evaluated in terms of total transmission delay, inter and intra handover delay, queuing delay, and total attachment time. Simulation results show that the proposed architecture performance-enhanced end-to-end latency over the legacy architecture.

The present work seeks to address the following question which serves a key motivation behind this research: 'What if there is a guide on the University of Ilorin website or in the weekly published magazine within the school, guiding the student on which MNO is best for internet connectivity based on the location which they are at any point in time?″. This research is key to answering the question. Data was gathered through a walk test using TEMS Investigation 16.3.4 and analyzed using TEMS Discovery Device 10. The test was based on internet access on the 4G Network by users who are subscribed to the various MNOs that are serving within the school premises.

Automating performance improvement in 4G cellular networks is a challenging research area due to existing limitations in artificial intelligence and machine learning applications. This study addresses these challenges by developing a data analysis model using Hidden Markov Models (HMM) to predict Key Performance Indicators (KPIs) and automate performance assessments. Data was analyzed from 1600 new sites of a mobile operator in Indonesia, collected from July 2023 to January 2024. The methodology follows Knowledge Discovery in Database (KDD) for data mining and applying HMMs to forecast KPIs such as eRAB Drop Rate and Setup Success Rate. The model achieved a Mean Absolute Error (MAE) of 0.005 and a Root Mean Square Error (RMSE) of 0.069 for eRAB Drop Rate, with an F1 Score reaching up to 99.76%. The performance of the model improves with an increasing number of observation states, particularly for Inter Frequency Handover Success Rate (HOSR) and RRC Connection Setup Success Rate. Despite strong performance, there is potential for further enhancement, especially for KPIs with high variability like Intra Frequency HOSR. This research demonstrates that HMMs are effective in predicting KPIs with high accuracy, rather than traditional time-series models. The results align with recent studies and suggest that combining HMMs with techniques such as LSTM or Random Forests could improve predictive accuracy. These methods are also applicable to another technology, especially 5G networks, offering valuable insights for more effective network management and performance optimization.

The present study focuses on the evaluation of the degradation of emotional expression in speech generated by a wireless telephone network. Two assessment approaches emerged: an objective one, deploying convolutional neural networks (CNNs) fed with spectrograms across three scales (Linear, Logarithmic, Mel), and a subjective method grounded in human perception. The study gathered expressive phrases in two different languages: from novice Arabic and proficient German speakers. These utterances underwent transmission on a real 4G network a rarity, as usual focus lies on bandwidth (BW) reduction or compression. Our innovation lies in utilizing the complete 4G infrastructure, accounting for all possible impairments. The results obtained indeed reveal a significant impact of transmission via the real 4G network on emotion recognition. Prior to transmission, the highest recognition rates, measured by the objective method using the Mel frequency scale, were 76% for Arabic and 91% for German. After transmission, these rates significantly decreased, reaching 70% for Arabic and 82% for German (a degradation of 6% and 9%), respectively. As for the subjective method, the recognition rates were 75% for Arabic and 70% for German before transmission and dropped to 67% for Arabic and 68% for German after transmission (a degradation of 8% and 2%). Our results were also compared to those found in the literature that used the same database.

Mobile wireless communication technologies have now become an everyday part of our lives, 24 hours a day, 7 days a week. Monitoring the autonomous system under exposition to electromagnetic fields may play an important role in broading of our still limited knowledge on their effect on human body. Thus, we studied the interaction of the high frequency electromagnetic field (HF EMF) with living body and its effect on the autonomic control of heart rate using Heart Rate Variability (HRV) linear and nonlinear analyses in healthy volunteers. A group of young healthy probands (n=30, age mean: 24.2 ± 3.5 years) without any symptoms of disease was exposed to EMF with f=2400 MHz (Wi Fi), and f=2600 MHz (4G) for 5 minutes applied on the chest area. The short-term heart rate variability (HRV) metrics were used as an indicator of complex cardiac autonomic control. The evaluated HRV parameters: RR interval (ms), high frequency spectral power (HF-HRV in [ln(ms2)]) as an index of cardiovagal control, and a symbolic dynamic index of 0V %, indicating cardiac sympathetic activity. The cardiac-linked parasympathetic index HF-HRV was significantly reduced (p =0.036) and sympathetically mediated HRV index 0V % was significantly higher (p=0.002) during EMF exposure at 2400 MHz (Wi-Fi), compared to simulated 4G frequency 2600 MHz. No significant differences were found in the RR intervals. Our results revealed a shift in cardiac autonomic regulation towards sympathetic overactivity and parasympathetic underactivity indexed by HRV parameters during EMF exposure in young healthy persons. It seems that HF EMF exposure results in abnormal complex cardiac autonomic regulatory integrity which may be associated with higher risk of later cardiovascular complications already in healthy probands.

This study investigates the impact of factors (network coverage, customer service, video calls, and downloading Speed) of 3G and 4G telecommunication services performance on customer satisfaction in the Punjab region of Pakistan. This research indicates how to make strong relations with customers and what factors of the 3G and 4G networks need to be improved to enhance the revenue of telecom operator companies. The study has recognized the four main hypotheses responsible for checking the level of customer satisfaction in the telecommunication industry of Pakistan in the Punjab region. The study depends on essential insights gathered on the arbitrary premise from 300 clients of significant telecom administrators in the Punjab area. The respondents have selected on irregular premises and were welcomed to express their sentiments through an organized survey. A complete questionnaire has been utilized for statistics collection and exists based on the analysis of descriptive measurement, correlation, and regression analysis and analyzed through SmartPLS software. They indicate that the independent variables network coverage, customer service, video calls, and downloading speed are key driving factors of customer satisfaction. Among all independent variables “Internet downloading speed” highly impacts the dependent variable “customer satisfaction” based on 3G and 4G network performance. There are a limited number of studies that focus on customer satisfaction in the telecommunication sector in Pakistan. The study will fill the gap in the literature and help service providers to increase the satisfaction level of their customers and captivate new customers.

In this study, we demonstrate an application for 5G networks in mobile and remote GPR scanning situations to detect buried objects by experts while the operator is performing the scans. Using a GSSI SIR-30 system in conjunction with the RealSense camera for visual mapping of the surveyed area, subsurface GPR scans were created and transmitted for remote processing. Using mobile networks, the raw B-scan files were transmitted at a sufficient rate, a maximum of 0.034 ms mean latency, to enable near real-time edge processing. The performance of 5G networks in handling the data transmission for the GPR scans and edge computing was compared to the performance of 4G networks. In addition, long-range low-power devices, namely Wi-Fi HaLow and Wi-Fi hotspots, were compared as local alternatives to cellular networks. Augmented reality headset representation of the F-scans is proposed as a method of assisting the operator in using the edge-processed scans. These promising results bode well for the potential of remote processing of GPR data in augmented reality applications.