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Streamline the O-RAN IOT badge compliant test with AEGIS-O

[O-RAN Certification and Badging Program] The O-RAN certification and badging program aims to minimize repetition of fundamental and common tests performed to verify and validate O-RAN based products and solutions before their deployment in operator networks. It defines and unifies processes, procedures, templates, data format, etc. which are provided to ensure sharing of the test results and repeatability of the executed tests. Currently, the O-RAN certificates, IOT badges and E2E badges have been defined for the following products (and interfaces). ● O-RAN certificates for- O-RU with Open Fronthaul interface (WG4)- O-DU (or combined O-DU/O-CU) with Open Fronthaul interface (WG4) ● O-RAN IOT badges for- O-RU and O-DU (or combined O-DU/O-CU) connected via Open Fronthaul interface(WG4)- eNB and en-gNB connected via X2 interface(WG5) - gNB-DU and gNB-CU connected via F1-C interface(WG5) - two gNBs connected via Xn-C interface (WG5)● O-RAN E2E badges for -O-RU, O-DU and O-CU (or their combinations) included in the E2E system or subsystem(TIFG)The O-RAN certification and badging refers to tests defined in O-RAN test specifications produced by related O-RAN Work/Focus Groups. Through O-RAN certification and badging program, any O-RAN vendor regardless of their size can have an opportunity to showcase their products and solutions, improve interoperability, and ultimately increase vendor diversity and supply chain resilience for operators embracing open RAN.O-RAN certification and badging can improve operator confidence in their chosen O-RAN based blueprint and can reduce the complexity and duration of pre-deployment testing.[AEGIS-O supports Automated Test and Report Development for O-RAN IOT Badging(WG5)] AEGIS-O introduces a new feature that provides automated testing functionality for O-RAN IOT badges, encompassing all test cases defined in the O-RAN Open F1/X2/Xn Interface, as outlined by the Interoperability Test Specification of the O-RAN Alliance Working Group (WG5). Operators can easily examine the compatibility of multi-vendor systems based on the O-RAN Test Specification and precisely analyze interoperability problems. Accuver (Innowireless) is an active member of the O-RAN Alliance. AEGIS-O was developed to automatically perform and report the same tests conducted by OTIC. Operators and vendors can independently conduct the same level of interoperability tests as OTIC using AEGIS-O. AEGIS-O not only executes tests defined in the IOT Badge specification but also provides features to analyze each test case in detail, such as the Packet Viewer, CDR Viewer, and Detail Report. Users can access statistical information about all test cases and investigate each test case for troubleshooting. This helps both operator and vendor communities prepare for OTIC tests and ensures confidence in O-RAN based products and solutions. Vendors can enhance interoperability and prepare for OTIC certification tests by proactively preparing the test cases defined in the standard. By conducting tests with AEGIS-O, operators can ensure interoperability at the OTIC level when configuring systems with products from different vendors. This reduces testing efforts for network operators and promotes vendors\' O-RAN based products and solutions, creating an opportunity for interoperability among different vendors and gaining acceptance from others. [AEGIS-O O-RAN IOT Badging( WG5) Test Procedure] AEGIS-O provides an automated testing feature for eNB and gNB connected via the X2 interface, gNB-DU and gNB-CU connected via the F1-C interface, and two gNBs connected via the Xn-C interface. It supports all the test cases specified in the O-RAN Open F1/X2/Xn Interface Working Group Interoperability Test Specification. In AEGIS-O, once the user selects the interface and test case and initiates the test, the results are assessed according to the criteria established within the O-RAN ALLIANCE framework. AEGIS-O offers Badge Reports that present the test results, and users can comprehensively investigate individual test cases using tools such as the Packet Viewer, CDR Viewer, and Detail Report. Midhaul traffic is tapped and flow into AEGSI-O by capture card and Packet Broker. When the user clicks WG5.IOT on the menu screen of AEGIS-O and selects the interface to be tested the Badge Setting screen is displayed. On the Badge Setting window, users can select test cases and configure profile information such as DUT information and network profile, etc. The Badge Status window shows the status of all scheduled test cases. Upon completion of each test case run, the test result is immediately displayed. Users have the option to save or submit results by exporting both the Badge Report and Detail Report. AEGIS-O’s Badge report form aligns with the O-RAN Alliance Badge program’s report structure, enabling vendors to prepare OTIC Tests, and allowing operators to easily compare it with other Badge reports. Users can also investigate packets and CDRs related to the particular test case if needed. In AEGIS-O, O-RAN WG5.IOT automated tests make it possible for operators to quickly and easily detect and analyze IOT problems with a real-time packet analysis feature. This approach offers a cost-effective way to verify the interoperability of operators\' O-RAN systems, which consist of products from multiple vendors. References [1] Overview of Open Testing and Integration Centre (OTIC) and O-RAN Certification and Badging Program: O-RAN ALLIANCE Test and Integration Focus Group, White Paper, April 2023

Oct 30, 2023
Self-Attention-based Uplink Radio Resource Prediction in 5G Dual Connectivity

Sungkyunkwan University conducted this study with the support of Accuver (XCAL-Solo III). They have proposed a self-attention-based deep learning model to predict uplink radio resource in 5G Dual Connectivity (5G DC). The model was trained on commercial 5G DC traffic data from three major carriers in South Korea and achieved an average prediction accuracy of 95.08% under various mobility and cell-load conditions.

Oct 27, 2023
Tackling Beamforming Test Hurdles with XCAT-MAIS′s mMIMO Expertise

By Dr. Joseph Lee [The definition and value of beamforming]Beamforming is a transmission technique that uses multiple array antennas to concentrate the power of a transmitted RF signal onto a particular user. A digital signal processing algorithm is used to apply relative amplitude and phase shifts to antenna elements in such a way that the signals join together towards a user’s location and cancel each other out in the opposite direction [1]. Figure 1. Massive MIMO antenna performing 3D (azimuth and elevation) beamforming. Beamforming plays a key role in performing multi-user multiple input, multiple output (MU-MIMO), in which concurrent users share time and frequency resources to dramatically increase the capacity of a channel. In a Massive MIMO antenna array, a large number of antenna elements (i.e., 64T/64R) serve users in different locations using beamforming. Using RF environments constructed for users that 2 employ signal concentration and canceling, multiple users achieve higher throughput at the same time and frequency. Together with higher carrier aggregation, higher-order modulation and enhanced use of unlicensed spectrum, beamforming/Massive MIMO can deliver Gigabit throughput in LTE-Advanced and 5G networks [2]. In urban, high data traffic environments where spectrum is limited, Massive MIMO’s beamforming technique is a significant advantage. By accommodating more concurrent users and giving them a better quality of service, beamforming allows mobile operators to attain a better return from their capital expenditure under limited resources. [How beamforming is performed between the base station and UE]There are two types of beam: a common beam used for the initial connection, and a dedicated beam used once that connection is established. Since a base station cannot locate a User Equipment (UE) at the time of its connection, the base station secures coverage through a time-sweep, with beams uniformly divided over space. Each beam contains a unique Synchronization Signal Block Beam ID (SSB ID) and Physical Beam Index (PBI). The UE informs the base station of its status, including SSB IDs and power information, in real time. Once the UE is connected to the base station, a dedicated beam for data transmission can be concentrated on the UE. The base station tracks the UE by measuring an uplink channel via a Sounding Reference Signal (SRS) transmitted from the UE. Then, the base station applies the uplink channel value to downlink channel value by using TDD channel reciprocity. Now, beamforming coefficients for each antenna can be calculated using channel value and a linear algebraic zero-forcing method, which helps minimize interference from other antennas. Multi-user MIMO is now performed through beamforming gain and interference rejection gain.[Beamforming KPIs] The list below highlights beamforming key performance indicators (KPIs) and illustrates why they are important to measure and analyze. The goalㅡTo verify whether throughput matches channel capacity, and if not, why. KPIs related to SSB/Common Beam ㆍNumber of detected SSBs A maximum of 64 SSBs can be transmitted. A base station can measure and estimate the location and direction of a UE using SSB IDsㅡor PBIsㅡthat it receives and reports. ㆍPBI and RSRP/RSRQ PBIs and associated power information received by a UE can be used to predict the handover situation of the UE. ㆍDMRS SINR Demodulation Reference Signal (DMRS) SINR can be used to estimate and receive channel characteristics. ㆍBeamforming gain This parameter can be used to estimate the efficiency of beamforming at the time of measurement. KPIs related to User/Dedicated-beam ㆍDMRS SINR Since multiple orthogonal DMRS signals can be allocated and beamformed to support MIMO transmission, DMRS SINR be used to estimate the degree of interference in each user signal in the corresponding physical channel. ㆍBeamforming Gain and Interference Rejection Gain Analyzing these KPIs can help estimate the performance of both channel estimation and interference rejection. [The challenges of measuring antenna beamforming performance]One way to measure a Massive MIMO’s beamforming performance is through field testing. Testing must be conducted among a representative number of UEs located in the sector (e.g. 16 UEs) and the UEs must be in different positions, i.e., not bunched together in a single location or line-of-sight spot. The UEs also need to support Transmission Mode 8 or 9 (TM8 or TM9) to report beam-specific KPIs. The idea is to measure how much gain a Massive MIMO antenna provides compared with a conventional antenna system. Through beamforming, a Massive MIMO antenna should provide better signal quality to each user. Hence, user throughput and sector throughput should be higher. For efficient field testing, Accuver XCAL-Manager and XCAL-Solo tools can be used. XCAL-Manager is a cloud-based server that allows users to assign test cases remotely to test UEs and monitor their status and locations in real time. It also allows users to choose which UEs to aggregate, so that they can see sector throughput in addition to user throughput. Indeed, Signals Research performed a similar Massive MIMO test recently using Accuver XCAL-Manager and XCAL-Solo tools [3]. If one conducts Massive MIMO/beamforming tests repeatedly, field tests are time- and resourceconsuming. Moreover, field tests don’t offer a repetitive and consistent test environment to verify Massive MIMO’s beamforming performance, or identify problems caused by multiple sources. One way to perform the test in a simpler way is to bring the field RF environment into a lab and test it repeatedly using a channel emulator. A channel emulator is an instrument that takes RF inputs to generate RF outputs and combines internally-generated multi-path signals with individual amplitude and phase gain control, including propagation delay and path loss implementation. To measure beamforming performance accurately, a channel emulator should secure ‘channel reciprocity,’ in which a downlink channel is equal to an uplink channelㅡsimilar to a real, over-the-air channel. However, a channel emulator is an electronic instrument incorporating RF and digital circuits which would not usually satisfy the channel reciprocity requirement. Hence, to meet that requirement, the channel emulator must be equipped with an internal or external calibration function. Since by nature RF components’ characteristics drift with temperature, calibration should be performed on a regular basis. Therefore, it is critical that the calibration function does its job in a relatively short period of timeㅡlest too much time is wasted on calibrations. [Introducing Accuver XCAT-MAIS]The Accuver Massive MIMO Channel Emulator (MAIS) is the latest addition to the Radio Access Network (RAN) Testing portfolioㅡpart of Accuver’s Field-to-Lab (F2L) testing solutions. F2L products deliver quick, cost-effective RAN software verification in real-world-like lab environments prior to field deployment. XCAT-MAIS is a channel emulator with M inputs to connect to BS antenna ports, and N outputs to connect to UE antenna ports. MAIS supports various M x N configurations, allowing users to test the performance ofㅡfor exampleㅡa 16 x 16 LTE FD-MIMO or a 64 x 64 5G Massive MIMO system. For RAN vendors, MAIS provides a repetitive, consistent test environment to verify Massive MIMO performance. For wireless operators, MAIS enables the comparison of FD/Massive MIMO performance from different RAN vendors in the same RF environment. Both these use cases are difficult to achieve with field testing due to variables present in the field environment. Figure 2. Accuver MAIS systemThe MAIS system supports a 100 MHz channel bandwidth for 5G testing, and frequencies of between 300 MHz to 6 GHz. It features a built-in calibration kit that is fast and accurate; and typically achieves the following specification within 15 minutes: |amplitude| < 0.35dB and |phase| < 3 degree; and it sustains the calibrated state for up to 72 hours. [XCAT-MAIS benefits]MAIS offers users the following benefits: ㆍ Adjustable amplitude and phase rotation ㆍ Monitoring of BS and UE outputs ㆍ Support of ITU channel models and user-defined models ㆍ Support for distributed, remote testing configuration ㆍ Measurement of beam tracking performance. MAIS has signal capturing function at both the BS and UE sides to measure all beamforming KPIs listed above. ㆍ Fast self-calibrationㅡtypically within 15 minutes. Calibration hardware is included in MAIS to ensure it creates channel conditions properly and achieves channel reciprocity within the specified tolerance [XCAT-MAIS specifications] ㆍ Channel bandwidth of up to 100 MHz ㆍ Frequency: 300 MHz to 6 GHz ㆍ RF port capacity: a single MAIS chassis can support up to 64 RF ports (16 slots, 4 RF ports per slot) ㆍ Channel reciprocity (for TDD) with calibration tolerances of: o Amplitude = ±0.35 dB and phase ±3 degrees from any BS port to any UE port ㆍ Support for DL 256QAM and UL 256 QAM, at a frequency of < 4 GHz ㆍ Channel fading models: ITU Ped. A/B, Veh. A/B, EPA, EVA, ETU, 2D/3D SCM, HST, and user-defined ㆍ Number of multipaths: 8 (expandable to 20) ㆍ Doppler frequency of up to 1350 Hz (560km/h @ 2.6 GHz) ㆍ AWGN built-in at each RF port[Signal and beamforming analysis with XCAT-MAIS]MAIS supports the following analysis: 1. Signal analysis on: a. Each RF port b. gNB and UE c. Relative power, OFDM, OBW and I/Q samples 2. Beamforming analysis on: a. RF ports b. SSB/common beam i. PCI, PBI, power, correlation accuracy, EVM, SINR ii. Relative phase-consistency c. PDSCH/dedicated-beam i. Relative phase-consistency ii. Beam-forming accuracy [Conclusion]Wireless technology is changing fast every day, and the complexity of testing and validating its features also grows exponentially. Such is the case with validating the performance of beamforming and Massive MIMO, two important features of 5G. Massive MIMO’s beamforming performance can be measured using field testing but doing so is very time- and resource-consuming. Moreover, the field doesn’t offer a repetitive and consistent test environment to troubleshoot problems that may be caused by multiple sources. Accuver MAIS (Massive MIMO Channel Emulator) provides a repetitive and consistent real-world-like test environment to verify and compare Massive MIMO product performance. MAIS system supports 100 MHz channel bandwidth for 5G testing and frequencies from 300 MHz to 6 GHz. It has a built-in calibration kit that is fast (within 15 minutes) and highly accurate ㅡ ensuring that little time is wasted in calibration ? so that users can get on with Massive MIMO testing quickly. References 1. Masterson, C. (2017, June). Massive MIMO and beamforming: The signal processing behind the 5G buzzwords. Analog Dialogue, 51. 2. Qualcomm. (2017, February). The essential role of Gigabit LTE & LTE Advanced Pro in a 5G World. 3. Thelander, M. (2018, November). The matrix: Quantifying the benefits of 64T64R Massive MIMO with beamforming and multi-user MIMO capabilities. Signals Ahead, 14, no. 9

Oct 25, 2023
[Signals Flash] WE′VE GOT YOU COVERED (TO VARYING DEGREES)

SRG(Signal Research Group) did this study with the support of Accuver Americas (XCAL5 and XCAP). SRG used a Galaxy S23 smartphone to test the downlink performance in a cluster of 10 Gbps cell sites that had 1x180 MHz of Band n41, 2x20 MHz of Band n25, and 2x20 MHz of Band n71. We primarily did drive tests along the rural roads as well as in the suburban neighborhoods, which were ideal for a fixed wireless access (FWA) service offering.For more detailed information, please refer to attachment.

Oct 19, 2023
Accuver Benchmarking Test Solutions

As the advancement of 5G technology leads to increased mobile data usage, the necessity for benchmarking tests is growing in order to assess and compare network performance effectively. With over 20 years of experience in network optimization, Accuver offers a comprehensive solution to evaluate and compare mobile network performance, coverage, and service quality from the user\'s perspective. ▶ Click to get full version of Accuver Benchmarking Test Solutions

Aug 29, 2023
[Signals Flash] IT′S GETTING HOT N HERE, SO...

SRG(Signal Research Group) did this study with the support of Accuver Americas (XCAL5/XCAL-Solo and XCAP). SRG just completed its 32nd 5G benchmark study. For this endeavor SRG collaborated with Accuver Americas to conduct an independentbenchmark study of 5G mmWave 4 component carrier (4CC) uplink performance, using AT&T’s commercial network in Glendale, AZ.For more detailed information, please refer to attachment.

Jul 10, 2023
Accuver Airspace Network Test Solution (Korean case study)

Airspace Network in 5G The development of a unified network infrastructure integrating Non-Terrestrial Network (NTN) platforms within the scope of 5G and future 6G technology is currently in progress. Standardization organizations like 3GPP are actively working on defining communication standards specifically tailored for Unmanned Aerial Vehicles (UAVs). Efficient performance testing and optimization of airspace networks are crucial to ensure seamless integration of communication services with UAV operations.The implementation of an airspace network in 5G technology presents unique considerations and challenges compared to traditional terrestrial networks Weak signal power from base stations to UAVs:Terrestrial networks are primarily optimized for User Equipment (UE) operating at heights ranging from 1 to 2 meters above ground level (AGL). Radio waves propagating skywards experience a decrease in signal strength compared to the ground. Establishing communication with UAVs may require the use of supplementary base stations or antenna uptilting techniques.Impact of UAV communication on ground users:Radio waves emitted by UAVs can extend to distant areas and potentially interfere with nearby base stations, smartphones, and other devices. Ensuring minimal interference and maintaining the quality of service for ground users is a critical challenge.New use cases (Korea):With the ongoing deployment of NR (New Radio) mobile networks, novel use cases will emerge as UAVs enter the market and leverage the ultra-high speed, large-capacity, ultra-reliable, low-latency communications, and multiple simultaneous connection features offered by NR.Overcoming these challenges requires optimizing signal strength for UAVs, mitigating interference with ground users, and exploring new use cases enabled by the capabilities of NR. Efforts by standardization organizations and the industry as a whole aim to address these challenges and pave the way for seamless integration of airspace networks within the 5G ecosystem.UAM Grand Challenge Korea The deployment and optimization of 5G airspace networks in Korea are driven by the objective of facilitating the commercialization of Urban Air Mobility services by 2025. To ensure a reliable and robust network infrastructure at altitudes ranging from 300 meters to 600 meters above the ground, Korean operators are employing dedicated gNBs and implementing antenna tilting and beam pattern optimization techniques. These strategies aim to provide seamless connectivity, enhanced signal strength, and reduced latency for UAM operations, thus supporting the realization of a safe and efficient urban air transportation ecosystem. Accuver Airspace Network Test Solution XCAL-Air is an advanced and comprehensive package specifically developed for measuring and analyzing the performance of airspace networks. It is designed to effectively identify and rectify coverage gaps to ensure optimal network performance in airspace environments. This technologically advanced solution incorporates various network equipment, including spectrum analyzers, scanners, and mobile network measurement devices. It offers a comprehensive set of features to enable efficient network verification in airspace environments.[ Key Features of XCAL-Air ]Airspace Network Performance Measurement:XCAL-Air provides a range of powerful measurement capabilities to assess the performance of airspace networks.It captures and analyzes various network parameters such as signal strength, signal quality, throughput, latency, and other key performance indicators (KPIs) in real-time.These measurements help in evaluating the network\'s coverage, capacity, and overall performance, enabling operators to identify areas of improvement.Integration with XCAL-Manager Air:The measured data collected by XCAL-Air is seamlessly transferred to XCAL-Manager Air for further analysis and evaluation.XCAL-Manager Air is a centralized management platform equipped with advanced analytics tools, allowing for in-depth assessment of airspace network performance.Accurate Global Navigation Satellite System (GNSS) information is associated with the measured data, facilitating precise location-based analysis of airspace network performance.[ Benefits of XCAL-Air ]Comprehensive Performance Analysis: XCAL-Air provides a comprehensive set of measurements, enabling operators to gain valuable insights into the performance of airspace networks.Coverage Gap Identification: By analyzing the collected data, XCAL-Air identifies coverage gaps and areas with suboptimal network performance, allowing operators to take corrective actions.Real-Time Monitoring: The solution offers real-time monitoring capabilities, providing operators with immediate visibility into network performance and enabling proactive troubleshooting.Data-Driven Decision Making: XCAL-Air\'s integration with XCAL-Manager Air enables operators to perform advanced analytics and make data-driven decisions for optimizing airspace network performance.Ground Management SystemThe XCAL-Air Ground Management System comprises two key components: XCAL-Manager Air and DROW4D. These components work in tandem to control and schedule remote tests for XCAL-Air, a specialized network testing tool designed for airspace networks. The XCAL-Air ground management system ensures efficient management, analysis, and verification of network performance.[ XCAL-Manager Air ]XCAL-Manager Air serves as the central control system for managing and scheduling remote tests conducted by XCAL-Air drones. It facilitates the planning and scheduling of network performance measurements in the air, based on predefined test scenarios. XCAL-Manager Air collects and analyzes the test results generated by XCAL-Air, providing valuable insights into network performance. [ DROW4D ]DROW4D is an integral part of the XCAL-Air ground management system, specifically designed to control and manage XCAL-Air drones. It enables the autonomous operation of multiple drones, ensuring coordinated and synchronized flights for efficient network testing.DROW4D assigns missions to the drones based on the test scenarios set in XCAL-Manager Air, pre-configures flight routes, and controls the drones during the testing process.Key Features of the XCAL-Air Ground Management System:Real-time Network Performance Monitoring on 3D Map:The measured key performance indicators (KPIs) obtained from the network tests are displayed on a 3D map, providing a visual representation of network performance.This visualization aids in identifying coverage gaps and areas requiring optimization or further investigation.Autonomous Drone Control:DROW4D enables autonomous operation of XCAL-Air drones, leveraging real-time wireless network environment data for precise aircraft control.Advanced drone control capabilities, including fail-safe return, extended measurement functionality, and mission reconfiguration in response to specific wireless network events, are facilitated by the DROW4D system. The XCAL-Air and XCAL-Manager Air packages represent a robust and all-encompassing solution for measuring and analyzing the performance of airspace networks. With their powerful capabilities, operators gain the ability to identify coverage gaps, obtain precise measurements, and efficiently manage remote tests while analyzing test results. Moreover, the visual representation of network performance on a 3D map adds an extra layer of insight and understanding. By leveraging these comprehensive packages, operators can optimize network performance, enhance coverage, and deliver a seamless and dependable communication experience in airspace environments.

Jun 15, 2023
Unattended, Remote-controlled Measurements Solution in 5G Private Network

by Jaechul Yoon[Testing Challenges in 5G Networks: Complexity and Continuous Quality Monitoring] 5G NR (New Radio) technology is a sophisticated network technology that adapts to its surroundings. Unlike previous technologies, 5G NR utilizes beamforming and intelligent adjustments based on device location and base station conditions. This dynamic nature of 5G NR poses challenges for traditional monitoring systems, as variations in the environment impact network performance. Traditional field tests using vehicle-mounted equipment were considered sufficient in the past, but the complexity of 5G NR requires continuous quality monitoring. However, existing solutions like Minimization of Drive Test (MDT) face limitations such as poor battery efficiency and inaccurate location data. To address these shortcomings, there is a growing demand for an advanced monitoring system that provides real-time insights into 5G NR network performance. By offering accurate and efficient monitoring capabilities, operators can effectively manage user experience and ensure optimal performance of their 5G NR networks.[Streamlining 5G Base Station Monitoring: Lessons from the Las Vegas Roll Out Trial] Accuver installed the XCAL-Ranger, an unattended base station monitoring solution, during the Roll Out Trial in Las Vegas. This deployment was crucial due to intermittent shutdowns caused by the Open Radio Access Network (O-RAN) architecture of 5G Standalone (SA) base stations.Based on our extensive Roll-out experience in India, Malaysia, USA, Mexico, and Canada, we discovered the importance of establishing a one-to-one correspondence between the base station and monitoring device. This ensures accurate identification and monitoring, even with adjacent stations.We also developed flexible functionality for configuring measurement intervals and scenarios, enabling tailored monitoring requirements with intervals ranging from 10 minutes to 2 hours.Additionally, we incorporated a Root Cause Analysis (RCA) detection function into our base station monitoring equipment. This function identifies various failure indicators such as Poor SS-RSRP, Poor SS-SINR, Low Throughput, Registration Failure, Overall RACH Failure, RRC Connection Setup Failure, RRC Drop, ENDC Setup LTE to 5G Failure, and ENDC Release 5G to LTE Failure.By identifying these failure events, operators gain insights into the causes impacting network performance, allowing them to take corrective measures for optimal operational efficiency. [Efficient Management and Analysis of High-Volume Measurement Data in Base Station Monitoring] When measuring with the shortest cycle, a total of 144 measurement data are generated per day. For instance, if there are 100 base stations being monitored, this results in 14,400 measurements. Similarly, with 1,000 base stations, the number of measurements increases to 144,000, all of which are uploaded to the server. To handle this large volume of data efficiently, an automated classification system based on base stations is implemented. Whenever an event occurs, the system automatically generates a report by comparing it with previous successful cases. Additionally, base stations are displayed on a map, visually representing their states with color-coded indications, enabling operators to quickly locate them. Operators can either search for specific base stations on the map or conveniently access event results from a list. For in-depth analysis of specific events, XCAL-Manager offers a one-click feature to generate graphs and tables. This allows operators to conduct detailed analysis while simultaneously viewing signaling messages in millisecond units, facilitating thorough examination of the event. [5G NR Launch with XCAL-Manager: Automated Detection, Classification, and Analysis] XCAL-Manager generates an automated report by comparing success test results obtained shortly before the occurrence of an event. It gathers base station configuration data through SIB and MIB, enabling quick problem detection and analysis by comparing successful and failed settings. Additionally, RF quality information for each base station is monitored in 10-minute intervals via a dashboard, ensuring a successful 5G NR launch and facilitating efficient problem detection and change analysis. Take your 5G NR implementation to new heights with XCAL-Manager and XCAL-Ranger, the ultimate solution for driving excellence in wireless networks. ▶Watch XCAL-Ranger video ▶Get more information for XCAL-Ranger

Jun 13, 2023
URLLC in 5G Technology

[URLLC in 5G Technology] Ultra-Reliable Low-Latency Communication (URLLC) is a critical feature of 5G networks that provides fast, reliable, and low-latency communication links between devices. URLLC enables ultra-reliable and low-latency communication for a wide range of applications, including mission-critical and latency-sensitive applications, industrial automation, smart city applications, public safety, and gaming. This technology is expected to enable new innovative services and applications, promoting technological innovation in various industries and providing better user experiences. [VR and URLLC performance] VR plays a decisive role in connecting most of these URLLC applications to user experience. VR applications require reliable, low-latency communication to deliver a high-quality experience. If there is too much latency between the VR headset and the device generating the VR environment, the user may experience a lag or delay in their movements, breaking the sense of immersion and ruining the experience. Additionally, URLLC technology can benefit from VR applications in several ways, such as remote training, where VR can simulate complex situations requiring real-time responses, allowing trainees to practice and refine their skills in a safe, controlled environment. Combining AR (Augmented Reality) technology and VR technology, new technologies that fuse the real world and the virtual world are expected to be developed, allowing users to experience both at the same time. The combination of URLLC and VR has the potential to drive innovation in a wide range of industries, from healthcare to manufacturing, by enabling new types of applications that require low latency, high reliability, and immersive experiences. [How to measure and validate latency in VR using Accuver VR solution] Latency and delay are critical factors in URLLC, ensuring reliable and timely communication, and must be kept as low as possible to meet the stringent requirements of URLLC. Latency is the time it takes for data to travel from the source to the destination, while delay includes the additional time spent waiting in buffers or queues along the way. Both latency and delay can occur anywhere on the device, network, system, and application level. [AEGIS VR] AEGIS VR, provided by Accuver, offers users a solution to measure and display URLLC performance of VR applications, measuring packet transit time between nodes or systems, as well as overall delay. It intuitively displays the delay measured while using the VR application in real time on the graph. [VR Traffic and Delay Monitoring]▶Watch video AEGIS VR logs and analyzes each VR data session in detail, identifying the nodes or channels that cause critical delays. It also analyzes QoS and QoE, including packet loss and jitter. In the Packet Viewer, users can view network monitoring messages, data packets, and more, and analyze the packet flow for any specific time period using XCAL. [Packet Viewer] Auto Report provides users with the overall UL/DL delay results for a specific session. [Auto Report]▶Watch video [AEGIS VR verifying sectional and end to end URLLC Performance] Latency can manifest at various points in the end-to-end communication process, including the device, Radio Access Network (RAN), core network, and content server in both wired and wireless environments. To identify and rectify latency-related issues, it is necessary to perform a comprehensive analysis of each of these sections by capturing packets and examining their characteristics. This process helps to pinpoint the root cause of the latency and take appropriate corrective measures to optimize network performance.AEGIS VR is equipped with sophisticated features for measuring delays and analyzing packets across various segments of the communication process, spanning from the end device to the wireless network and the core network. The solution enables independent measurement and analysis of latency in diverse devices such as mobile devices, VR equipment, and PCs, across different wireless network segments, including 4G, 5G, and WLAN, as well as wired network sections that traverse from the core network to the contents server. The advanced capabilities of AEGIS VR facilitate a comprehensive assessment of the end-to-end communication process, helping to detect and resolve latency-related issues with utmost precision and efficiency. Accuver\'s state-of-the-art solution, AEGIS VR, is a game-changer for customers seeking to verify the performance of their 5G systems. With AEGIS VR, you can meticulously evaluate the delay of your 5G system, section-by-section and overall, enabling early detection and remediation of issues that could impact 5G Ultra-Reliable Low-Latency Communications (URLLC). This cutting-edge technology empowers you to optimize your 5G network for maximum performance, ensuring seamless, uninterrupted connectivity and an exceptional user experience. Discover the transformative potential of 5G technology with Accuver\'s AEGIS VR.

Apr 16, 2023

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