As the tech world converged once again at Mobile World Congress (MWC) 2024 recently, it’s an opportune moment to reflect on the myriad benefits this renowned event offers to businesses, both large-scale companies and SMEs alike. Whether exhibiting or simply attending, the advantages are vast and diverse, shaping the future landscape of innovation and connectivity.
For large-scale companies, exhibiting at MWC presented a golden opportunity to showcase cutting-edge technologies, solutions, and features, forge strategic partnerships, and amplify brand visibility on a global stage. From unveiling flagship products to engaging with industry leaders, the exhibition floor served as a dynamic marketplace for networking and business expansion.
Similarly, for SMEs (Small & medium enterprises), MWC offered a platform for accelerated growth, a real live marketing space, a huge media podium, and a magic way to enlarge market penetration.
It provided a level playing field to compete alongside industry giants, enabling startups, small and medium enterprises, and emerging businesses to show their capabilities and innovations, secure vital investor interest, secure partnerships with big players and clients, and garner invaluable feedback from a diverse audience. Moreover, participating in MWC allowed SMEs to gain insights into the competition’s landscape, analyze existing solutions, and identify opportunities for differentiation and innovation.
Even for those not exhibiting, attending MWC held immense value. It served as a hub for knowledge exchange, where attendees could gain insights into emerging trends, industry best practices, and future technologies through keynote speeches, panel discussions, and interactive sessions. Moreover, attendees had the opportunity to witness firsthand the future of connectivity, exploring ground-breaking innovations in 5G, IoT, AI, and beyond. Additionally, MWC provided unparalleled networking opportunities, allowing attendees to connect with industry peers, potential collaborators, and thought leaders from around the globe. From informal discussions on the exhibition floor to structured networking events, MWC fostered meaningful connections that could lead to valuable partnerships, business opportunities, and collaborations.
4YFN was not just a separate event but an integral part of MWC, focusing specifically on innovative ideas and new technologies. This dedicated exhibition hall within MWC provided Startups with a platform to showcase their products and ideas, connect with investors, and explore collaboration opportunities. By participating in 4YFN, Startups could gain exposure to a global audience, validate their concepts, and secure essential funding to fuel their growth trajectory.
In conclusion, Mobile World Congress 2024 stood as a beacon of opportunity for businesses of all sizes. Whether exhibiting or attending, the benefits extended far beyond the event itself, shaping the trajectory of innovation and connectivity for years to come.
We are thrilled to announce the launch of a groundbreaking feature on our product KATANA IPM (Intelligent Performance Management): Superior Complaints Handling. This innovative addition is designed to revolutionize the way you manage and address complaints, providing you with unparalleled insights and capabilities to enhance your overall customer experience.
Key Features:
1. Simplified GUI: Our user-friendly interface ensures ease of use, allowing for seamless navigation and efficient complaint management. 2. Multiple Location Input: Easily input data from various locations to gain a comprehensive understanding of performance across your network. 3. AI Prediction for CC Heat Map: Leveraging artificial intelligence, our system predicts and visualizes complaint hotspots, empowering proactive decision-making. 4. Integration Between Multiple Systems: Seamlessly integrate with Drive Testing, Configuration Management, and Fault Management systems for a holistic view of network performance.
Key Benefits:
• Proactive View on Vulnerable Areas: Identify and address potential issues before they escalate, improving network performance and customer satisfaction. • Enhanced Mean Time to Detect and Resolve: Streamline complaint handling processes to minimize downtime and optimize resource allocation. • Improved Customer Experience: Swiftly addressing complaints and optimizing network performance can significantly enhance the overall customer experience. • Enhanced Churn and Revenue KPIs: Retain more customers and increase revenue through improved service quality and customer satisfaction.
We believe that the Superior Complaints Handling feature on KATANA IPM will empower you to achieve new heights in performance management and customer satisfaction. We are excited about this feature’s possibilities and look forward to supporting you in leveraging its full potential.
5G technology promises blazing-fast data speeds and brings revolutionary enhancements to voice communication. In the realm of 5G, Voice over LTE (VoLTE) serves as a cornerstone, enabling high-quality voice calls over LTE networks.
However, as the transition to standalone 5G advances, the landscape for voice options expands, introducing innovative ways to manage voice traffic.
Handling Voice in 5G NSA deployment
In the initial stages of deploying 5G, Non-Standalone (NSA) architecture integrates 5G technology with existing LTE infrastructure. NSA 5G relies on VoLTE for voice services as the primary option, ensuring a smooth transition from 4G to 5G. This configuration maintains voice continuity and quality, utilizing the robustness of VoLTE even in the early phases of 5G deployment.
If VoLTE (Voice over LTE) is unavailable, especially in areas with limited or absent LTE coverage or for other reasons, the network activates traditional circuit-switched fallback mechanisms. In the absence of VoLTE, the network reverts to legacy 2G or 3G technologies for voice calls, resulting in a negative impact on data services and degradation in voice quality.
As 5G deployment advances, network coverage and support for VoLTE are anticipated to increase. This growth aims to minimize situations where VoLTE is unavailable, ultimately improving the quality and reliability of voice calls.
In essence, VoLTE provides superior voice quality and supports simultaneous voice and data sessions over LTE & 5G NSA. However, the absence of VoLTE support prompts a fallback to older 2G/3G networks for voice calls, ensuring continuous voice communication but potentially compromising quality and data performance. As telecom infrastructure evolves, prioritizing the expansion of VoLTE coverage remains crucial to delivering enhanced voice services across broader areas.
Handling Voice in 5G SA deployment
As the industry transitions to Standalone (SA) 5G networks, Voice over New Radio (VoNR) emerges as the dedicated voice solution for standalone architecture. VoNR, a significant evolution from VoLTE, is optimized specifically for 5G networks, offering superior voice quality, lower latency, and enhanced support for new features enabled by 5G technology.
The transition from VoLTE to VoNR in SA 5G networks will occur gradually, allowing for a coexistence period where both technologies jointly handle voice services. This hybrid approach ensures backward compatibility and smooth migration, maintaining the integrity of voice services while capitalizing on the enhanced capabilities of VoNR.
In cases where 5G coverage is lacking or weak, alternative solutions may be needed to handle voice services despite the presence of VoNR.
To prevent bad call quality or call drops, especially for UEs making Voice over New Radio (VoNR) calls from the 5G cell edge, the UE is directed during the voice call setup towards the 5G core network (5GC). This forces a switch to an LTE/EPS connection where the radio conditions are better for the voice service, a procedure known as “EPS Fallback,” defined by 3GPP. This process also occurs when the UE is served by a 5G cell not configured or optimized for VoNR calls or when the UE lacks necessary VoNR capabilities.
Actually, we have 2 options to implement EPS fallback could be described as below
In 5G release with redirection to LTE (Option A), the 5G radio connection is released after setup and redirected to LTE. Following the 5G RRC Release, the UE is instructed to reselect a 4G cell, initiating a new radio connection for the VoLTE call. During this process, the UE context is transferred from the AMF to the MME over the N26 interface.
In 5G-4G Inter-RAT Handover (Option B), signaling and traffic are tunneled between SMF/UPF and MME/SGW.
SRVCC (Single Radio Voice Connection Continuity) is a feature in mobile networks ensuring seamless transitions between different technologies during voice calls, facilitating handover from LTE (4G) or NR (5G) to legacy 2G or 3G networks when moving out of coverage.
Both VoLTE and VoNR require an IMS system. Establishing a solid, robust, and well-tested IMS network is a challenging task, demanding considerable effort and continuous improvement.
For more information about Digis Squared VoLTE and IMS Services please check out the Managed Services page.
The emergence of Low Earth Orbit (LEO) satellites marks a significant advancement in the realm of non-terrestrial networks, particularly in their integration with mobile devices. LEO satellites operate closer to Earth, reducing latency and enabling faster data transmission. Their use in providing global internet coverage directly to mobile devices heralds a new era in connectivity.
With companies like SpaceX, OneWeb, and Amazon’s Project Kuiper launching constellations of LEO satellites, mobile devices stand to benefit from expanded coverage and improved bandwidth.
The prospect of integrating LEO band support into mobile devices opens doors for seamless, high-speed internet access, revolutionizing how individuals experience connectivity on the go.
As LEO satellite constellations become more established, the integration of their capabilities into mobile technology could redefine the standards for mobile connectivity, promising faster, more reliable access for users worldwide.
But now the question is “are Non-Terrestrial Networks (NTN) a threat or an opportunity for Mobile Network Operators (MNOs) and the telecom industry?”
Examining this question uncovers various facets of this emerging technology.
Challenges that will Face MNOs with NTN growth:
Competition: NTN, like satellite networks or high-altitude balloons, competes with MNOs by offering connectivity in areas where traditional networks struggle to reach.
Infrastructure Costs: Adapting or investing in new infrastructure to match NTN capabilities can be financially burdensome for MNOs.
In summary, Non-Terrestrial Networks pose both challenges and opportunities for MNOs and the industry. Strategic adaptation and collaboration within this evolving network landscape will determine the outcome.
Now, exploring the limitations of NTN:
Coverage Constraints: NTN technologies have limitations in serving densely populated or geographically challenging areas.
Latency Issues: Satellite-based systems suffer from delays, impacting real-time applications.
High Costs: Deployment and maintenance expenses lead to less affordability, especially in developing regions.
Spectrum Management Challenges: Multiple systems operating in similar frequencies can cause interference.
Chipset Readiness: Despite the numerous claims made by chipset vendors regarding their support for LEO bands, the reality remains that only a handful of mobile devices currently possess the necessary reception capabilities to utilize these bands effectively.
Weather Dependence: Weather conditions affect certain NTN systems, causing service disruptions.
Capacity Limits: Constraints on simultaneous users and bandwidth affect service quality during peak times.
Security Vulnerabilities: Cybersecurity threats and data transmission security are critical concerns.
Reliability Challenges: Maintaining reliability, especially in space, faces technical and environmental hurdles.
In conclusion, while NTN offers global connectivity and remote access advantages, addressing these limitations is crucial for its viability in telecom.
NTN Applications across Industries:
Satellite Internet: Connects remote areas lacking terrestrial internet access.
Disaster Management: Vital in coordinating rescue efforts during crises.
Agriculture: Provides real-time data for precision farming.
Maritime and Aviation: Ensures continuous connectivity during travel.
Energy and Environmental Monitoring: Aids in monitoring remote facilities and environmental research.
Education and Rural Connectivity: Bridges the digital divide in remote education.
Industries like Mining, Oil & Gas, Tourism, and Defense: Facilitates communication and operations in remote locations.
These diverse use cases showcase how NTN technologies address connectivity challenges, improving safety, efficiency, and quality of life, becoming an extension of terrestrial connections.
In the realm of mobile network testing, accurate location data plays a crucial role in analyzing network performance and ensuring optimal coverage. However, relying solely on GPS accuracy for pinpointing locations can sometimes be challenging, especially in urban environments where tall buildings and signal obstructions can affect GPS signals. To overcome this hurdle, the innovative product known as iNOS (Intelligent Network Optimization System) introduces a groundbreaking feature called “AI Location Enhancement.” This feature leverages artificial intelligence to adjust sample locations, even when GPS accuracy is compromised, effectively placing all samples at the center of the street, enhancing their visual representation.
The Challenge of GPS Accuracy:
Mobile network testing involves collecting a vast amount of data points, including signal strength, data throughput, latency, and more. To accurately represent network performance, these data points need to be associated with their respective geographical locations. Conventionally, GPS technology is employed to track and map these locations. However, GPS signals can be susceptible to errors caused by factors like multi-path interference, urban canyons, or dense foliage. Consequently, the accuracy of GPS positioning may be compromised, leading to inaccurate mapping and misrepresentation of network performance.
Introducing AI Location Enhancement:
To address the limitations of GPS accuracy, iNOS integrates AI Location Enhancement as a groundbreaking feature. This feature utilizes advanced machine learning algorithms to analyze the available data and make intelligent adjustments to sample locations. By doing so, it significantly enhances the visual representation of samples, ensuring they are placed at the center of the street for a more accurate depiction of network performance.
How AI Location Enhancement Works:
1. Data Analysis: iNOS collects a vast amount of network performance data, including signal strength measurements, latency values, and throughput statistics, along with their corresponding GPS coordinates.
2. AI Algorithms: Advanced machine learning algorithms are applied to the collected data, taking into account various parameters and factors that affect GPS accuracy.
3. Sample Location Adjustment: Using the analyzed data, iNOS intelligently adjusts the sample locations to compensate for GPS inaccuracies. It identifies the center of the street or road segment to ensure that the samples are represented accurately, regardless of the GPS readings.
4. Visual Enhancement: The adjusted sample locations are visually represented on a map or within a network performance report, offering a clear and concise view of the network’s performance characteristics. This enhanced visual representation helps network engineers and operators make informed decisions and optimizations.
Benefits of AI Location Enhancement:
1. Accurate Network Performance Analysis: By adjusting sample locations to the center of the street, AI Location Enhancement ensures that the network performance analysis is based on accurate and representative data.
2. Improved Data Visualization: The enhanced visual representation of sample locations allows network engineers and operators to quickly identify network performance patterns and make informed decisions for optimization.
3. Efficient Optimization Strategies: With more accurate data at hand, network operators can devise targeted optimization strategies to enhance coverage, reduce latency, and improve overall user experience.
4. Time and Cost Savings: By leveraging AI to adjust sample locations, iNOS reduces the need for manual data correction and eliminates the associated time and cost overheads.
Conclusion:
AI Location Enhancement is a revolutionary feature in iNOS, designed to overcome the limitations of GPS accuracy in mobile network testing. By leveraging advanced machine learning algorithms, this feature adjusts sample locations to the center of the street, enhancing the visual representation of data. With accurate network performance analysis, improved data visualization, and efficient optimization strategies, iNOS equipped with AI Location Enhancement empowers network engineers and operators to make data-driven decisions for enhancing mobile network performance and delivering an exceptional user experience.
In the ever-evolving landscape of telecommunications, Digis Squared stands as a trailblazer in delivering large-scale managed service projects across multiple Network Operator domains. With an extensive portfolio covering Field, RAN, Transport, IPBB, Core, VAS, and BSS domains, the company boasts profound experience and a robust foundation in managing Mobile Network Operator (MNO) networks. Leveraging multi-vendor expertise and diverse technological proficiency, Digis Squared ensures optimal operations for its Open RAN networks.
The emergence of Open RAN technologies has introduced a paradigm shift in network operations, presenting complexities attributed to an increased number of vendors, multiple integration points and interfaces as well as third parties solutions that are seamlessly integrated with MNOs network. In response, Digis Squared has ingeniously crafted its proprietary Managed Service Operations model. This model, aligned with the ITIL operational framework, the ITU FCAPS model, and SMO Standard guidelines provided by the ORAN Alliance, serves as a guiding structure for the company’s operational strategies across all Open RAN knowledge domains.
Within this model, Digis Squared meticulously covers a wide array of activities integral to Open RAN network management:
Radio Planning and Optimization activities including various types of RIC Operations
Field Activities
Field maintenance
Corrective Maintenance
Preventive Maintenance
E2ETesting Activities
Drive Testing
Network function testing
Network Operations Center (NOC) activities
Front Office Operations
Performance Monitoring
Service Desk Operations
Helpdesk
Change Management
Incident Management
Problem Management
Risk Management
Reporting
Back Office Operations
Integration activities that include third parties’ management and Operations.
Customer Experience Governance activities.
The encompassing nature of Digis Squared’s model extends its coverage across various essential components:
Radio
Site Hardware
RAN Software
Transport
Cloud Infrastructure
CaaS and O-cloud
The company’s expertise spans a broad spectrum of vendors, encompassing but not limited to VMWare, RedHat, Robin io, NEC, Mavenit, Altio-Star, Juniper, Dell, and HP. This expansive vendor landscape ensures a comprehensive understanding of diverse technological infrastructures, enabling Digis Squared to offer unparalleled solutions and support within the Open RAN ecosystem.
Digis Squared’s commitment to excellence and innovation in managed services within Open RAN networks continues to redefine industry standards. By blending extensive experience, a robust operational model, and a diverse vendor portfolio, the company stands at the forefront of delivering top-tier services in the realm of telecommunications.
As the telecommunications industry continues to evolve, Digis Squared remains dedicated to pioneering advancements, ensuring seamless operations and exceptional service delivery in the dynamic landscape of Open RAN networks.
Embarking on the journey of SOC (Service Operations Center) transformation prompts a pivotal inquiry: does a Call Drop Rate of 0.5% represent a good or bad metric? Applying Schrodinger’s cat theory to this value unravels the multiplicity of its implications. From a network perspective, this rate may signify a positive standing. However, in the context of impacting strategic corporate accounts situated within buildings, it could potentially evoke frustration among CEOs and senior staff, thereby rendering the 0.5% rate unfavorable. This duality underscores the necessity for a broader vision that extends beyond network quality alone, focusing on service quality—a vision materialized through the SOC.
Understanding the SOC and its functionalities requires delving into the customer experience approach, especially as the telecom industry converges with rapidly advancing technology and heightened customer expectations. The advent of the Customer Experience Management (CEM) framework amplifies the significance of a dedicated customer experience team.
The primary goal of the CEM framework lies in augmenting customer satisfaction and fostering loyalty through the provision of effective technical support. This proactive approach not only contributes to sustained revenue growth but also serves as a linchpin for maintaining competitive differentiation in a dynamic market environment.
The SOC serves as the linchpin between network metrics and customer-centric service qualities. Its transformation represents a strategic shift towards a holistic perspective, acknowledging that network performance metrics, while vital, might not encapsulate the entirety of customer satisfaction. Integrating the SOC within the operational framework enables a more comprehensive
By amalgamating network-centric data with a nuanced understanding of customer needs, the SOC transformation aims to strike a delicate balance. It doesn’t dismiss the importance of network performance but rather complements it by incorporating the customer’s perception of service quality into the evaluation metrics.
In essence, the evolution of the SOC signifies a paradigm shift—a departure from a myopic focus on network metrics to a more encompassing approach that places customer experience at its core. Embracing this transformation not only elevates service delivery but also aligns telecommunications companies with the evolving landscape of customer-centricity, fostering enduring relationships and sustained growth in a fiercely competitive market.
The fundamental ethos of the SOC revolves around fostering a Customer-Centric network and operations, aligning every operational facet towards optimizing customer satisfaction.
Outlined below are the core functions that delineate the landscape of the SOC:
Service Surveillance:
This function entails the continuous monitoring and management of service performance and quality. From fault detection to real-time response mechanisms, its aim is to minimize service disruptions while upholding stringent quality standards and Service Level Agreements (SLAs). Collaboration with network operations and customer support teams is crucial to gauge customer impact accurately. Robust reporting and documentation further drive ongoing improvements, ensuring high service reliability and customer satisfaction.
Service Analysis:
Delving deeper into customer usage patterns, service reliability, and network efficiency, this function identifies areas for enhancement or expansion. By assessing customer satisfaction levels, it informs future service development and enhancement strategies, paving the way for proactive service improvements.
Supporting CSI Initiatives:
The SOC actively participates in developing and executing action plans aimed at addressing identified gaps. Monitoring the impact of these changes is pivotal, as it supports continual service evolution, ensuring sustained high levels of customer satisfaction.
Reporting:
Systematic collection, analysis, and presentation of data and insights form the backbone of this function. Accurate and regular reports are indispensable for monitoring progress, identifying improvement areas, and supporting organizational success on a holistic level.
SOC teams have the below interaction map could be described as below.
As an integral component of the SOC transformation, Mobile Network Operators (MNOs) must integrate additional tools to facilitate and fortify this evolution. Some of these crucial tools encompass:
Network Probing tools
OSS data Access
Trouble ticketing Tools.
The collaborative efforts between SOC (Service Operations Center) and CEM (Customer Experience Management) teams play a pivotal role in crafting Service Key Performance Indicators (KPIs) and Key Quality Indicators (KQIs). The creation of these metrics involves a strategic alignment between operational excellence and customer-centricity, focusing on various aspects that directly impact service delivery and customer satisfaction.
SOC SKPIs centers around the following.
Handsets Performance
Customer Segment Performance
HotSpots performance
OTTs performance
…. Etc
SOC use cases, We at Digis Squared have more than 70 ready use cases with insights and expected outputs, but use case generation is a continuous task and it shall be endless
Customers flip-flopping between radio technologies.
Customers with 4G handsets locked onto 3G.
Heavy data users with 3G handsets, we offer 4G handsets.
VoLTE performance variance across different handsets
Geolocation for data streaming activities
VIP and enterprise dashboards and proactive monitoring
Happy voice and data customers
CSFB analysis and delay investigations
…
Let’s explore a significant use case featuring our product, INOS, specifically the SOC – Active Probing scenario. In this scenario, we implement our INOS Watcher Kits in various high-traffic locations such as hotspots, VIP customer areas, corporate settings, shops, stations, or any other locations designated by the MNO. Subsequently, we establish continuously running scripts across these watchers, enabling these kits to instantly upload testing logs.
These logs are then utilized to populate a customized SOC dashboard hosted on the cloud. This dashboard provides a comprehensive overview of all Service KPIs and KQIs categorized by device, area, location, and/or IMSI. This solution empowers us to monitor service levels in specific areas and proactively identify any potential service issues experienced by customers in those locations.
In the ever-evolving landscape of telecommunications, the advent of 5G stands as a monumental leap forward. Beyond just speed, 5G introduces a transformative architecture known as the 5G core (5GC), revolutionizing the way we integrate, connect, and communicate. Let’s delve deeper into this advanced infrastructure and the pivotal concepts that shape its functionality.
The 5G core represents a fundamental shift from its predecessors, embracing a software-defined network architecture, cloud-native virtual network functions, and service-based architecture as well as full separation between the user plane and control plane through the full implementation of CUPS. Within this core, network functions play a pivotal role. These functions, ranging from authentication and policy control to session management and database management, are decoupled and virtualized, allowing for flexibility and scalability previously unseen in telecommunications networks. The Service-Based Architecture (SBA) in 5G represents a paradigm shift in how telecommunications networks are structured and function. At its core, SBA redefines network architecture by organizing various functionalities into modular and reusable services. These services, such as network slicing, authentication, session management, and policy control, are designed to be independent and interact through well-defined interfaces. This modular approach enables flexibility, allowing service providers to dynamically compose and deploy services tailored to specific user needs and applications. SBA facilitates efficient resource utilization, scalability, and rapid innovation, enabling the seamless integration of diverse services and applications across the 5G network.
Its emphasis on standardized interfaces and service-based components fosters interoperability and encourages an ecosystem where new services can be rapidly developed, deployed, and managed in a more agile and cost-effective manner, ultimately driving the evolution of 5G networks to meet the demands of an increasingly connected world.
This cloud-service-based approach in the 5G core revolutionizes how telecommunications networks operate, offering a level of flexibility and scalability crucial for supporting a wide array of services and applications in the 5G era.
Network slicing, a defining feature of 5G, enables the creation of isolated, end-to-end virtual networks tailored to specific services or customer requirements.
By partitioning the network resources, 5G can allocate bandwidth, latency, and other parameters on demand. For instance, a slice designed for autonomous vehicles may prioritize ultra-low latency, ensuring real-time responsiveness, while another slice optimized for IoT devices might emphasize massive connectivity. This ability to customize network characteristics within slices is pivotal in meeting the diverse needs of various industries and applications.
As part of 3GPP release 16 the Service Communication Proxy (SCP) has been introduced as a non-mandatory but vital node to have strong SBA deployment in coordination with multi-access edge computing (MEC) and it serves as a pivotal component within the 5G network, facilitating service-based communication between various network functions. Acting as an intermediary, the SCP ensures seamless interaction and coordination between functions such as the policy control function (PCF), user plane function (UPF), and network exposure function (NEF). It enables efficient handling of service requests, ensuring that data and control flow smoothly across the network, ultimately contributing to a robust and responsive network infrastructure and reducing the load on NRF (Network Repository Function)
Digis Squared stands out as a pivotal force in the domain of 5G system integration, renowned for its extensive proficiency in deploying both standalone and non-standalone 5G networks. our expertise spans across the entire spectrum of 5G infrastructure, encompassing radio, transport, and core networks. Through a meticulous approach to integration, we at Digis Squared ensure a cohesive and harmonized ecosystem, emphasizing seamless interoperability and optimal performance across these network layers.
Their in-depth understanding of 5G architecture enables us to tailor solutions that precisely address the unique needs and challenges encountered across diverse industries. For instance, in industries like healthcare, manufacturing, automotive, and entertainment, we at Digis Squared customize the integration strategies to accommodate specific requirements, whether it’s ultra-reliable low-latency communication (URLLC) for critical applications or massive machine-type communication (mMTC) for IoT devices as well as for the application that needs the enhanced mobile broadband (eMBB).
Digis Squared’s contributions extend beyond mere integration; they actively shape the 5G landscape by pioneering innovative solutions and best practices. Their role in driving the transition toward a fully connected future is instrumental, as they continuously refine their methodologies to adapt to the evolving demands of the 5G ecosystem. This commitment to innovation positions Digis Squared as a key enabler of the transformative potential inherent in 5G technology, propelling industries, and societies toward a more connected and technologically advanced era.
Leveraging advanced analytics and AI engine, IPM predicts and prevents network performance issues before they happen, building Capacity growth models and forecasting user behaviour and traffic load on the network, giving proper recommendations that keep network performance on track with this growth and user behaviour changes.
IPM Analytics is the heart of KATANA IPM module, and it offers the below different uses cases.
Anomaly Detection:employs a machine-learning algorithm to understand the patterns of Key Performance Indicators (KPIs), making comparisons and autonomously recognizing deviations. The resulting scores are presented for each instance, facilitating straightforward identification of anomalies and their deviation from the typical cluster or common behavioral patterns within the network.
Forecasting Analysis: iPM encompasses various forecasting techniques within a unified interface, granting users the capability to analyze anticipated future trends in network usage for any counter and Key Performance Indicator (KPI).
Capacity Management: As networks expand and experience heightened traffic, there is often a decline in network performance. To prevent this deterioration, iPM Capacity management function becomes crucial to enhance performance and restore it to its initial levels. iPM is Addressing traffic shifts requires the strategic rebalancing of network traffic, ensuring even utilization across the network, thereby deferring capital expenditures on new equipment.
Worst Cell List: The Worst Cell List Report, an integral component of our iPM capabilities, is robustly supported by ranking conditions tied to specific periods for designated Key Performance Indicators (KPIs). This functionality empowers users to assess nodes with the poorest performance through detailed maps and charts.
Worst Degraded List:This module, seamlessly integrated into our iPM suite, efficiently troubleshoots and compiles a list of nodes with degraded performance over a specified period. It conducts in-depth analyses through maps and charts, facilitating immediate examination at the work area for detailed troubleshooting
Benchmark: After implementing an optimization action, users have the flexibility to initiate a benchmark across a set of Key Performance Indicators (KPIs). This benchmarking can be conducted on a Day-to-Day, Week-to-Week, or Month-to-Month basis, allowing for comprehensive performance evaluation over various timeframes.
Swap & Acceptance: In Swap Projects, users are required to compare Key Performance Indicators (KPIs) before and after the swap. iPM provides users with the convenient option to effortlessly compare the performance of vendors, facilitating a streamlined assessment of the impact of the swap on network performance.
In the world of mobile network testing, efficiency and accuracy are crucial for optimizing network performance. The “Eagle Eye” feature in INOS is a powerful tool that enables users to analyze large data sets in logfiles, extracting valuable insights through geofencing. This feature facilitates data-driven decision-making for network optimization.
Unveiling “Eagle Eye”
The “Eagle Eye” feature in INOS allows users to effortlessly search through logfiles containing millions of samples, making it a reality. Unlike the traditional method that required meticulous effort in recalling file names, dates, and locations, “Eagle Eye” offers an intuitive solution. Users can define their area of interest using geofencing, and the feature retrieves all relevant data within that area, saving both time and effort.
Optimizing Search Results
“Eagle Eye” offers various settings to streamline the search process, allowing users to optimize and narrow down their results efficiently. These settings include:
Time Aggregation: Users can pick time granularity (hourly, weekly, or monthly) to analyze data over specific periods, aiding trend identification.
Distance Aggregation: Users can set the desired distance aggregation for a detailed location-based network performance analysis.
Operator MNC/MCC: Users can filter their search results based on specific Mobile Network Code (MNC) and Mobile Country Code (MCC).
KPI Selection: Users can choose the Key Performance Indicators (KPIs) they wish to extract from the logfiles.
Date Range and Time Clustering: Users can set a date range and cluster data in time to better understand network performance changes in specific periods.
Interpreting the Results
Once the search parameters are set, “Eagle Eye” presents users with an interactive map accompanied by a timeline.
Figure-2
“Eagle Eye” offers a user-friendly visual representation for easy navigation, providing insights into network performance across locations and timeframes. It also includes benchmark tables and histogram charts for comparative analysis and trend identification.
Use Case Scenarios
The application of “Eagle Eye” in INOS extends to various use cases like;
Pre-action Network Assessment
Performance Benchmarking
Team Performance Assessment
Investment Impact analysis
Conclusion
“Eagle Eye” in INOS is a game-changer for mobile network testing, with geofencing, result optimization, and visual representations that empower efficient insights extraction. It enhances decision-making, network performance, and operational excellence in mobile network testing.
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