FIGURE 1 - available via license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Content may be subject to copyright.
Source publication
The 5G technology offers a higher complexity than earlier generations, introducing a new type of network designed to connect virtually everyone and everything together, including vehicles, smart devices, and road infrastructure, while ensuring security, coverage, and increased performance. Therefore, following all these aspects introduced by 5G tec...
Contexts in source publication
Context 1
... evolution of cellular networks intended to improve the capabilities of the network in terms of flexibility and efficiency as the number of users had increased year by year. A general architecture of the 5G network is presented in Fig. 1 and is composed by 2 parts: a Radio Access Network (RAN) and a Core Network (CN) [16]. The RAN component makes the link between the user equipment (UE), illustrated as Internet-of-Things (IoT) devices in Fig. 1 and the base station, which in case of 5G network is called Next Generation Node Base (gNodeB or gNB). It is responsible of ...
Context 2
... of flexibility and efficiency as the number of users had increased year by year. A general architecture of the 5G network is presented in Fig. 1 and is composed by 2 parts: a Radio Access Network (RAN) and a Core Network (CN) [16]. The RAN component makes the link between the user equipment (UE), illustrated as Internet-of-Things (IoT) devices in Fig. 1 and the base station, which in case of 5G network is called Next Generation Node Base (gNodeB or gNB). It is responsible of the radio resources management, mobility management, and control radio bearer of the network plane [17]. In consequence of the challenges that high mobility requires, in [18] are presented various RAN ...
Context 3
... results obtained in the presented measurement setup are illustrated in Fig. 10, from the point of view of highlighting the route taken, the type of cellular communication, and the connections with gNBs. The measurements were made for 600 seconds, the related AT commands being sent every second, as presented in the previous section. The method of data plotting shown in Fig. 10 was made using Leaflet [40], which is ...
Context 4
... presented measurement setup are illustrated in Fig. 10, from the point of view of highlighting the route taken, the type of cellular communication, and the connections with gNBs. The measurements were made for 600 seconds, the related AT commands being sent every second, as presented in the previous section. The method of data plotting shown in Fig. 10 was made using Leaflet [40], which is an open-source JavaScript library for mobilefriendly interactive maps. Therefore, the following steps were used to obtain this representation on a real map: i) the representation on the map of gNBs, using the orange signal icons, with the help of the received information from the Orange Romania ...
Context 5
... the 4G communication is marked with red dots and 5G communication with blue dots; iii) making for 5G communication the connections between the gNBs and the points where the measurements were made, this being achieved by associating the physical identifier of the cell to which the module was connected with that of the gNBs. Therefore, Fig. 10 illustrates the coverage of the cellular network for the chosen test route. Depending on the GPS information, the areas with 4G and 5G coverage were represented. Furthermore, for each measurement it is possible to see to which gNB the SIM8200EA-M2 module was connected. For a more consistent analysis, in Fig. 11 is illustrated the ...
Context 6
... with that of the gNBs. Therefore, Fig. 10 illustrates the coverage of the cellular network for the chosen test route. Depending on the GPS information, the areas with 4G and 5G coverage were represented. Furthermore, for each measurement it is possible to see to which gNB the SIM8200EA-M2 module was connected. For a more consistent analysis, in Fig. 11 is illustrated the vehicle speed for the entire duration of the measurements, where it can be seen that the average speed with which the vehicle moved was 35 km/h. Fig. 12 shows the distance between the UE and each gNB to which it was connected during the measurement. More precisely, the distance is illustrated only for the moment when ...
Context 7
... and 5G coverage were represented. Furthermore, for each measurement it is possible to see to which gNB the SIM8200EA-M2 module was connected. For a more consistent analysis, in Fig. 11 is illustrated the vehicle speed for the entire duration of the measurements, where it can be seen that the average speed with which the vehicle moved was 35 km/h. Fig. 12 shows the distance between the UE and each gNB to which it was connected during the measurement. More precisely, the distance is illustrated only for the moment when there was a cellular connection between the UE and the respective gNB. Distance between UE and gNB1 Distance between UE and gNB2 Distance between UE and gNB3 Distance ...
Context 8
... the distribution of transmission power of the module over the measurements can be seen in Fig. 13. The network performance indicators are associated differently for 4G compared to 5G. In 4G, they are associated with Cell Specific Reference Signal (CRS), and in the case of 5G communication, CRS is not used. In contrast, the Channel State Information (CSI) and Synchronization Signal (SS) are used for performance indicators, which are ...
Context 9
... with Cell Specific Reference Signal (CRS), and in the case of 5G communication, CRS is not used. In contrast, the Channel State Information (CSI) and Synchronization Signal (SS) are used for performance indicators, which are defined for FR1 and FR2. The performance indicators chosen to evaluate the cellular communication for the route from Fig. 10 are presented in detail in the following [41] [42]: 1) RSRP -reports the average power over the received signal from the base station. Besides this, this indicator can be used for DL positioning measurements, cell selection for UE, reselection, and handover. The RSRP value is measured in dBm, and a too low value for this indicator may ...
Context 10
... of the channel can be reported and validated. Moreover, the value of this indicator can take scalar values between 0 and 15, the highest value describing a high quality of the channel. Furthermore, this value can indicate the level of modulation and coding that the UE could operate on. The indicators for 4G communication are illustrated in Fig. 14, where the values for RSRP, RSRQ, and RSSI can be observed. Being a NSA architecture, the module measures these parameters for both 4G and 5G. Therefore, according to the SIM8200EA-M2 module specifications, the range of reported values for RSRP is between -44 dBm and -140 dBm, between -20 dB and -3 dB for RSRQ, and between -120 dBm and ...
Context 11
... the values for RSRP, RSRQ, and RSSI from Fig. 14 lower than RSSI, a smaller difference between the two guarantees less interference, which implies a better quality of the received signal. According to Fig. 14, for 4G, the measured values for RSRP have values between -120 dBm and -67.4 dBm, with an average value of -90.99 dBm. The RSRP level varies depending on the proximity to the ...
Context 12
... the values for RSRP, RSRQ, and RSSI from Fig. 14 lower than RSSI, a smaller difference between the two guarantees less interference, which implies a better quality of the received signal. According to Fig. 14, for 4G, the measured values for RSRP have values between -120 dBm and -67.4 dBm, with an average value of -90.99 dBm. The RSRP level varies depending on the proximity to the LTE cell, the signal has a value of approximately -75 dBm near a cell to -120 dBm at the edge of the LTE coverage. Moreover, values higher than -80 dBm mean an ...
Context 13
... to 5G communication, in Fig. 15, the values for the RSRP and RSRQ indicators are presented. Another important performance indicator for 5G communication is represented in Fig. 16, i.e., the SNR indicator. The distribution of values for RSRP is between -124 dBm and -96 dBm, the average value for the entire duration being -108.64 dBm. Moreover, for the RSRQ indicator, ...
Context 14
... to 5G communication, in Fig. 15, the values for the RSRP and RSRQ indicators are presented. Another important performance indicator for 5G communication is represented in Fig. 16, i.e., the SNR indicator. The distribution of values for RSRP is between -124 dBm and -96 dBm, the average value for the entire duration being -108.64 dBm. Moreover, for the RSRQ indicator, values between -18 dB and -11 dB were obtained, with an average value of -12.74 dB. In the case of the performed measurement shown in Fig. 10, the ...
Context 15
... represented in Fig. 16, i.e., the SNR indicator. The distribution of values for RSRP is between -124 dBm and -96 dBm, the average value for the entire duration being -108.64 dBm. Moreover, for the RSRQ indicator, values between -18 dB and -11 dB were obtained, with an average value of -12.74 dB. In the case of the performed measurement shown in Fig. 10, the measured values for SNR indicator are between -1 dB and 31 dB, with an average value of 9.75 ...
Context 16
... minimum SNR of -20 dB is needed to detect RSRP or RSRQ. Comparing Figs. 15 and 16, a relationship between RSRP and SNR can be deduced. Thus, they are directly proportional on average, showing similar variations in certain measurement points. ...
Context 17
... the distances between UE and gNBs, from Fig. 12, it can be highlighted that the RSRP and RSRQ indicators are directly impacted by this distance. For the connection between UE and gNB1, where the distance was around 200 m, the best values for RSRP, RSRQ, and SNR can be observed. As this distance increases, reaching the range of 800 -1000 m, one can see that the performance decrease, ...
Context 18
... quality of the channel for cellular communication between the module and the gNBs, for the entire measurement period, is illustrated by the CQI indicator and can be seen in Fig. 17. The module returns a decimal value between 0 and 15, the higher value meaning the better quality of the channel. The average value measured for this indicator was 8.46. Observing the waveforms from Fig. 16 and 17, it can be seen that the CQI is calculated based on the SNR value. Thus, where the SNR values fall below the average of ...
Context 19
... communication between the module and the gNBs, for the entire measurement period, is illustrated by the CQI indicator and can be seen in Fig. 17. The module returns a decimal value between 0 and 15, the higher value meaning the better quality of the channel. The average value measured for this indicator was 8.46. Observing the waveforms from Fig. 16 and 17, it can be seen that the CQI is calculated based on the SNR value. Thus, where the SNR values fall below the average of 9.75 dB, the channel quality also drops significantly. Considering that it is about dynamic measurements, where the module is not in the same position, the vehicle moving at different speeds, and there are several ...
Context 20
... Systems (OSS). These are a collection of hardware and software tools designed to help telcos monitor, analyze and manage telecom networks. Any UE camping on the cells of a gNB communicates with it a Temporary Mobile Subscriber Identity (TMSI). For the measurement method, this TMSI is used to identify the UE on a gNB, following the UE monitoring. Fig. 19 shows a capture from the OSS interface, where one can see all the information about the connection between the UE and gNB, but also about different performance indicators relevant for the communication between ...
Context 21
... the same way as for the dynamic measurements, the static ones were also carried out in a dense urban area in the city of Iasi, Romania. The positioning of the hardware setup, noted as UE, but also that of the gNB can be seen in Fig. 18, the distance between the two being 300 m. The data was collected for a duration of 35 minutes, from 16:55 PM to 17:30 PM. For the communication between the UE and the gNB, from the point of view of the used spectrum, the same frequency bands were used as in the case of the dynamic measurements. During all this period, the UE was ...
Context 22
... more detailed analysis can be seen in Figs. 21, 22, where one can observe the results obtained by the measurement method presented in comparison with the results measured by Orange Romania. The two figures illustrate some of the most important performance indicators, in Fig. 21 values for RSRP can be observed, and in Fig. 22 values for SNR. Related to the two figures, it can be seen ...
Context 23
... more detailed analysis can be seen in Figs. 21, 22, where one can observe the results obtained by the measurement method presented in comparison with the results measured by Orange Romania. The two figures illustrate some of the most important performance indicators, in Fig. 21 values for RSRP can be observed, and in Fig. 22 values for SNR. Related to the two figures, it can be seen that the values obtained with the SIM8200EA-M2 module are quite close to the measurements made by the cellular network provider, which indicates that the data collection method, presented in this paper, is stable and offers a ...
Citations
... automated vehicles for low latency communication, autonomous unmanned aerial vehicle, and video streaming. On the other hand, Lazar et al. [20] provided an insight into the practical method of real-time data measurement for 5G using SIM8200EA-M2 hardware module. They choose various key performance parameters viz. ...
Fifth generation new radio (5G NR) is bringing revolutions in almost every field such as healthcare, industrial automation, smart farming, and defense. These fields utilize three major use case scenarios of 5G NR viz. eMBB, URLLC, and mMTC. 5G NR deployment relies on two major frequency bands such as sub-6 GHz and high-frequency bands (millimeter waves). Among all sub-6 GHz bands, the n78 band (3300–3800 MHz) is gaining popularity due to its unique characteristics viz. higher capacity and coverage, wide bandwidth, and higher data rate. Despite these unique characteristics, in the 5G standalone architecture, users expect high-speed video/voice transmission without delay and good quality of services (QoS) requirements. QoS is one of the important paradigms that indicates the quality of services experienced by end users instead of services claimed by service providers. In this work, we have designed a QoS scenario that utilizes the n78 band with an “urban macro mixed office scenario with low loss” path loss model. As per types of services are concerned, the scenario utilizes six different traffic templates (i.e., FTP, Voice, Video, COAP, CBR, and Email). The path loss model operates on non-line-of-sight scenarios with Rayleigh fading and eigen beamforming using 64 ×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times $$\end{document} 32 antenna elements. The performance of the proposed scenario is examined through different metrics i.e., throughput, packet drop ratio, and delay. Here, priorities to different traffic templates are assigned based on GBR and non-GBR resource types. In addition, the proportional fair scheduling algorithm is employed to schedule the resources. It was observed that video services achieved a higher throughput of 25.93 Mbps due to their prioritization in the QoS model. Conversely, FTP services experienced higher delay, measured at 64 ms, and a packet delivery ratio of 5.94%.
... In [11], the concept of Quality of Monitoring (QoM) is introduced for the evaluation and enhancement of M-plane data within the context of 5G networks, which integrates a data-driven algorithm in tandem with a lossycompression methodology. In [12], a real-time data measurement methodology based on hardware platform is proposed to evaluate and analyse the 5G network performance. In [13], the performance of 5G cognitive radio networks is assessed, where the numerical analysis of multiple network performance metrics is conducted to evaluate the Quality of Service (QoS) under different scenarios. ...
Network performance evaluation is crucial in ensuring the effective operation of 5G wireless networks, offering valuable insights into evaluating network status and user experience. However, the complexity of network conditions, characterized by high dynamics and diverse user requirements across various vertical applications, presents a significant challenge for generating accurate and detailed evaluation results using existing algorithms. To provide a feasible solution for this issue, an artificial intelligence-enabled 5G network performance evaluation scheme for private 5G networks is proposed. First, the network performance evaluation at different granularities is modeled with the deployment of network performance evaluation introduced. Furthermore, an intelligent network performance evaluation architecture based on residual networks with the attention mechanism is introduced, which can generate evaluation scores based on key performance indicators of reliability, accessibility, utilization, integrity, mobility and retainability. Additionally, the corresponding training strategies for the intelligent model, catering to different evaluation granularity, are thoroughly designed. Finally, to validate the effectiveness of the proposed scheme, comprehensive experiments are conducted using practical 5G network operation system data. The experimental results demonstrate the scheme’s ability to achieve highly accurate evaluations with fine spatial granularity. These findings establish the feasibility and efficacy of the proposed artificial intelligence-enabled scheme in enhancing 5G network performance evaluation.
... This is possible by periodically broadcasting a CAM message between connected vehicles and LTE-V2X supporting in-coverage, out-of-coverage, and partial-coverage scenarios. [113]. For 5G NR-V2X, two communication modes are defined, as in the case of LTE-V2X, mode 1 and mode 2. The advantages of 5G NR-V2X technology include increased capacity and speed, as well as reliability, but also a considerable decrease in latency [114]. ...
A suitable control architecture for connected vehicle platoons may be seen as a promising solution for today's traffic problems, by improving road safety and traffic flow, reducing emissions and fuel consumption, and increasing driver comfort. This paper provides a comprehensive overview concerning the defining levels of a general control architecture for connected vehicle platoons, intending to illustrate the options available in terms of sensor technologies, in-vehicle networks, vehicular communication, and control solutions. Moreover, starting from the proposed control architecture, a solution that implements a Cooperative Adaptive Cruise Control (CACC) functionality for a vehicle platoon is designed. Also, two control algorithms based on the distributed model-based predictive control (DMPC) strategy and the feedback gain matrix method for the control level of the CACC functionality are proposed. The designed architecture was tested in a simulation scenario, and the obtained results show the control performances achieved using the proposed solutions suitable for the longitudinal dynamics of vehicle platoons.
