How to Learn 5G 6G RAN Development Using C and Python: Complete Beginner to Advanced Guide (2026)
- Kumar Rajdeep
- 2 hours ago
- 13 min read
Introduction How to Learn 5G 6G RAN Development Using C and Python
The global telecommunications industry is undergoing its most radical transformation in decades. Closed, vendor-locked hardware boxes are now obsolete. In their place, cloud-native software-defined networks, Open RAN (O-RAN), and disaggregated architectures dominate modern mobile infrastructure. For software developers, systems programmers, and engineering graduates, understanding How to Learn 5G 6G RAN Development Using C and Python is the single most valuable engineering investment you can make in 2026.
As operators across the globe accelerate their 5G-Advanced deployments and construct early 6G testbeds, the demand for developers who understand real-time systems programming alongside cloud orchestration has skyrocketed. High-speed cellular processing requires a dual-language paradigm: C and C++ power the microsecond, real-time data path, while Python manages control plane orchestration, AI/ML intelligent controllers (RIC), and protocol automation. This comprehensive guide walks you step-by-step from beginner fundamentals to advanced implementation, explaining protocol stacks, edge architectures, exposure engines, and the exact career roadmap needed to excel in this thriving field.
Table of Contents
The Core Engineering Stack: Why C and Python Drive 5G/6G Networks
Mastering 3GPP Protocol Stack Layers (PHY, MAC, RLC, PDCP, RRC, NAS)
What is MEC in 5G?
Role of NEF in 5G Core
Benefits of Edge Computing
MEC Architecture
NEF APIs and Exposure Functions
MEC vs Cloud Computing
Real-Time 5G Applications
AI and Edge Computing
5G Private Networks
Future of MEC and NEF in 2026
Telecom Industry Career Opportunities
Why Apeksha Telecom and Bikas Kumar Singh Are Important for a Career in the Telecom Industry
Frequently Asked Questions (FAQs)
Conclusion & Practical Action Plan
The Core Engineering Stack: Why C and Python Drive 5G/6G Networks
In modern software-defined cellular networks, baseband unit processing is split into containerized Cloud-Native Network Functions (CNFs). Building these disaggregated systems requires balancing zero-latency packet execution with rapid policy automation.
+-----------------------------------------------------------------------------------+
| 5G/6G TELECOM SOFTWARE DUAL-LANGUAGE PIPELINE |
| |
| FAST-PATH DATA PLANE (C / C++) |
| [ PHY Layer ] ---> [ MAC Scheduler ] ---> [ RLC / PDCP ] |
| * Sub-millisecond slot loops (125 µs) |
| * Zero-copy memory handling (DPDK, SIMD, CFFI) |
| |
| SLOW-PATH CONTROL & ANALYTICS PLANE (PYTHON) |
| [ Near-RT RIC xApps ] ---> [ NEF REST APIs ] ---> [ Pytest Automation ] |
| * Control loops (10 ms – 1000 ms) |
| * AI/ML model execution & PCAP forensic parsing |
+-----------------------------------------------------------------------------------+
Low-Level C and C++ for the Data Plane
Cellular slots run on sub-millisecond schedules (down to $125\ \mu\text{s}$ depending on 5G NR numerology). The data plane must calculate error check codes, execute channel estimation, and dynamically allocate physical resource blocks (PRBs) in real time.
Engineers rely on low-level C and C++ because they provide:
Direct Kernel Bypass: Interfacing with SmartNICs through the Data Plane Development Kit (DPDK) to process millions of packets per second without OS interrupt delays.
Deterministic Timing: Direct memory allocation that avoids unpredictable runtime garbage collection pauses.
Hardware Acceleration: Native compilation optimized with Single Instruction Multiple Data (SIMD) vector units for fast digital signal processing.
Python for Orchestration, Automation, and RIC Development
While C handles the raw high-speed bitstream, Python controls policy execution, testing automation, and cloud management:
RIC xApps and rApps: Near-Real-Time and Non-Real-Time Radio Intelligent Controllers process E2 interface telemetry in Python to execute AI-based beam steering and traffic steering.
Log Decoding & Forensics: Python scripts parse complex Wireshark traces, PCAP/PCAPNG files, and QXDM diagnostic logs to automate network issue detection.
Restful Service Interfaces: Python Web frameworks connect seamlessly to 5G Core RESTful endpoints using lightweight JSON payloads.
Learning how to combine C performance with Python agility is the core foundation when exploring How to Learn 5G 6G RAN Development Using C and Python effectively.
Mastering 3GPP Protocol Stack Layers (PHY, MAC, RLC, PDCP, RRC, NAS)
A crucial milestone in telecom software engineering is mastering the 3GPP protocol stack architecture.
+-----------------------------------------------------------------------------------+
| 3GPP 5G NR PROTOCOL LAYER ARCHITECTURE |
+-----------------------------------------------------------------------------------+
| Non-Access Stratum (NAS): Mobility, Authentication & Core Session Control |
+-----------------------------------------------------------------------------------+
| Radio Resource Control (RRC): System Information, Connection & Handover Management|
+-----------------------------------------------------------------------------------+
| SDAP: QoS Flow Mapping | PDCP: Header Compression (ROHC) & Encryption |
| RLC: Segmentation & ARQ | MAC: Real-Time HARQ Scheduling & Multiplexing |
+-----------------------------------------------------------------------------------+
| Physical Layer (PHY): OFDM Numerology, LDPC/Polar Coding, Massive MIMO |
+-----------------------------------------------------------------------------------+
Layer 1: Physical Layer (PHY)
Handles radio frequency modulation (QPSK to 256QAM) and digital signal generation.
Uses LDPC coding for data payload channels and Polar coding for control channels.
Manages digital beamforming and spatial multiplexing across Massive MIMO arrays.
Layer 2: Data Link Sublayers
Medium Access Control (MAC): Runs dynamic slot-by-slot link scheduling, HARQ retransmissions, and logical-to-transport channel multiplexing.
Radio Link Control (RLC): Oversees packet segmentation, reassembly, and Automatic Repeat Request (ARQ) error correction.
Packet Data Convergence Protocol (PDCP): Handles sequence numbering, IP header compression (ROHC), and AES cryptographic encryption.
Service Data Adaptation Protocol (SDAP): Maps Quality of Service (QoS) flows directly to Data Radio Bearers (DRBs).
Layer 3: Signaling & Control
Radio Resource Control (RRC): Manages connection state transitions (RRC_IDLE, RRC_INACTIVE, RRC_CONNECTED), system information broadcast messages, and active cell handovers.
Non-Access Stratum (NAS): Manages subscriber authentication, registration state, and core network session setups between the device and the Access and Mobility Management Function (AMF).
What is MEC in 5G?
Multi-access Edge Computing (MEC) is an ETSI-standardized platform framework that brings cloud computing, storage, and application management directly inside the Radio Access Network.
+-----------------------------------------------------------------------------------+
| 5G LOCAL BREAKOUT (LBO) TRAFFIC FLOW |
| |
| [ UE Device ] ---> [ gNodeB Antenna ] ---> [ Local UPF Router Node ] |
| | |
| (Local Breakout) |
| | |
| v |
| [ On-Premise MEC Host ] |
| (Latency < 5 ms) |
+-----------------------------------------------------------------------------------+
In traditional 4G LTE topologies, all user plane traffic was backhauled to a centralized Packet Gateway (PGW) located far away in regional data centers, creating packet delays of 50ms to 150ms.
MEC changes this by placing compute hardware right at local cell sites or regional aggregation hubs. Utilizing the 5G User Plane Function (UPF) Local Breakout (LBO) capability, target data streams bypass long transport networks entirely. This drops round-trip latency below 10 milliseconds, making ultra-reliable, real-time applications possible.
Role of NEF in 5G Core
The Network Exposure Function (NEF) acts as a centralized, secure API gateway for the 5G Core Service-Based Architecture (SBA).
+-----------------------------------------------------------------------------------+
| 5G CORE NEF API GATEWAY SYSTEM |
| |
| +------------------------+ RESTful JSON +--------------------------+ |
| | Third-Party App / | <---------------------> | Network Exposure | |
| | Enterprise MEC Server | APIs (HTTPS) | Function (NEF) | |
| +------------------------+ +--------------------------+ |
| ^ |
| | SBI |
| v |
| +--------------------------+ |
| | Internal 5G Core NFs | |
| | (AMF / SMF / PCF) | |
| +--------------------------+ |
+-----------------------------------------------------------------------------------+
Before 5G, cellular networks operated as closed, opaque infrastructure. External software systems could not easily monitor network states or alter connectivity parameters on demand.
In 5G Core architectures, internal functions communicate over HTTP/2 service interfaces. The NEF acts as the border control gateway:
Authentication: Validates external enterprise third-party platforms before allowing network interactions.
Translation: Transforms 3GPP binary configurations into developer-friendly REST/JSON payloads.
Security & Isolation: Exposes network status, dynamic bandwidth adjustment, and mobility triggers without exposing internal core infrastructure.
Benefits of Edge Computing
Shifting processing tasks from central mega-clouds to distributed edge nodes unlocks substantial architectural benefits:
System Metric | Centralized Cloud Framework | 5G/6G Multi-access Edge Computing |
Transport Latency | 50 ms – 150 ms | 1 ms – 10 ms |
Backhaul Traffic Cost | High (All raw data streams to core) | Low (Filtered locally) |
Data Privacy & Compliance | Data travels across public networks | Retained within enterprise perimeter |
Radio Awareness | No awareness of RF conditions | Direct access to real-time RNIS metrics |
System Reliability | Depends on wide-area connectivity | Remains operational during main backhaul outages |
1. Low Delay Responses
Executing software locally eliminates transport hops, keeping processing loops predictable and well within single-digit millisecond limits.
2. Reduced Backhaul Congestion
Local processing filters out high-volume raw video streams and sensor logs on site, sending only actionable alert logs across the main backhaul transport network.
3. High Data Security and Compliance
Enterprises handling sensitive industrial telemetry can maintain full data privacy by keeping operational traffic contained entirely within their physical boundaries.
MEC Architecture
The ETSI MEC standard defines a modular architecture designed to host virtualized microservices right at the network edge.
+-----------------------------------------------------------------------------------+
| ETSI MEC SYSTEM ARCHITECTURE |
| |
| +-----------------------------------------------------------------------------+ |
| | System Level: MEC Application Orchestrator (MEO) | |
| +-----------------------------------------------------------------------------+ |
| | |
| v |
| +-----------------------------------------------------------------------------+ |
| | Host Level: MEC Platform Manager (MEPM) | |
| +-----------------------------------------------------------------------------+ |
| | |
| v |
| +-----------------------------------------------------------------------------+ |
| | MEC Host | |
| | +-----------------------------------------------------------------------+ | |
| | | Container Runtime (Docker Containers / Kubernetes Pods) | | |
| | +-----------------------------------------------------------------------+ | |
| | | MEC Platform Services: RNIS, Location API, Bandwidth Allocation | | |
| | +-----------------------------------------------------------------------+ | |
| | | Edge Apps: C Vision Models, V2X Services, Industry 4.0 Engines | | |
| | +-----------------------------------------------------------------------+ | |
| +-----------------------------------------------------------------------------+ |
+-----------------------------------------------------------------------------------+
Core Architectural Layers
MEC Application Orchestrator (MEO): Oversees application deployments across multi-site edge topology based on capacity and service needs.
MEC Platform Manager (MEPM): Manages container lifecycles, service registrations, and local packet routing rules.
MEC Host Architecture:
Container Virtualization Engine: Hosts microservices in lightweight Docker containers managed by Kubernetes.
Platform Services (MEP): Provides essential platform utilities such as the Radio Network Information Service (RNIS) and Location Services.
Hardware Accelerators: Leverages NPUs, SmartNICs, and GPUs for accelerated AI and protocol processing tasks.
NEF APIs and Exposure Functions
Standardized 3GPP NEF APIs allow external applications to control cellular behavior using standard Web protocols:
+-----------------------------------------------------------------------------------+
| NEF RESTFUL API EXPOSURE ENGINE |
| |
| +---------------------------------------------------------------------------+ |
| | NEF API GATEWAY SYSTEM | |
| +---------------------------------------------------------------------------+ |
| | | | |
| v v v |
| +------------+ +------------+ +------------+ |
| | Nnef_Event | | Nnef_QoS | | Nnef_AF | |
| | Exposure | | Management | | SessionWith| |
| | API | | API | | QoS API | |
| +------------+ +------------+ +------------+ |
+-----------------------------------------------------------------------------------+
Essential Exposure APIs
Nnef_EventExposure API: Delivers automated callbacks regarding mobile connection states, cell transitions, and roaming events.
Nnef_AFSessionWithQoS API: Allows external control software to request guaranteed bit rates and low-latency profiles for active data streams dynamically.
Nnef_TrafficInfluence API: Instructs cellular UPFs to re-route active user traffic to specific local MEC servers dynamically.
MEC vs Cloud Computing
+-----------------------------------------------------------------------------------+
| MEC VS CENTRAL CLOUD ARCHITECTURE |
+----------------------------------+------------------------------------------------+
| Feature | Multi-access Edge Computing (MEC) |
+----------------------------------+------------------------------------------------+
| Deployment Location | Edge sites, base stations, regional hubs |
| End-to-End Latency | 1 ms – 10 ms |
| Data Processing Routing | Localized via UPF Local Breakout |
| Real-Time Radio Insights | Integrated RNIS and Location APIs |
| Primary Application Types | Autonomous mobility, industrial robotics |
+----------------------------------+------------------------------------------------+
| Feature | Centralized Cloud Architecture |
+----------------------------------+------------------------------------------------+
| Deployment Location | Concentrated mega data centers |
| End-to-End Latency | 50 ms – 200 ms |
| Data Processing Routing | Requires full backhaul transport |
| Real-Time Radio Insights | Unavailable |
| Primary Application Types | Web platforms, e-commerce, deep analytics |
+----------------------------------+------------------------------------------------+
Real-Time 5G Applications
Combining edge computing with modular Open RAN design enables breakthrough real-time services across key industries:
+-----------------------------------------------------------------------------------+
| REAL-TIME 5G APPLICATION DOMAINS |
| |
| [ Industry 4.0 Factories ] [ Connected Transportation ] [ Telemedicine ] |
| Robotic Synchronization V2X Collision Avoidance Remote Surgery |
| Target Latency: < 5ms Target Latency: < 10ms Target Latency: < 5ms|
+-----------------------------------------------------------------------------------+
1. Smart Factories & Industry 4.0
Non-public 5G installations power autonomous mobile robots (AMRs), synchronized assembly machinery, and real-time vision inspection. Real-time C schedulers deliver deterministic slot allocations, while Python AI services analyze multi-angle visual inspection feeds.
2. Cellular Vehicle-to-Everything (C-V2X)
Roadside units process position and velocity vectors shared by connected vehicles. Edge software predicts dangerous trajectories, broadcasting warning alerts within microsecond execution budgets.
3. Telemedicine and Remote Robotic Surgery
Surgical assistance systems require ultra-reliable low-latency communication (URLLC). Edge slicing controls guarantee sub-5ms delay bounds, ensuring precise, uninterrupted haptic feedback during sensitive remote operations.
Understanding these enterprise deployments illustrates why mastering How to Learn 5G 6G RAN Development Using C and Python is so valuable for systems engineers.
AI and Edge Computing
Modern Open RAN architectures incorporate machine learning directly into radio signal control loops. Standards defined in 3GPP Release 18 and Release 19 make AI a native layer of network execution.
+-----------------------------------------------------------------------------------+
| AI & EDGE COMPUTING IN O-RAN |
| |
| +-------------------------------------------------------------------------------+ |
| | Non-Real-Time RIC | |
| | - Trains AI/ML models on historical network data | |
| | - Deploys policy guidelines via Python rApps | |
| +-------------------------------------------------------------------------------+ |
| | |
| v Policy Updates |
| +-------------------------------------------------------------------------------+ |
| | Near-Real-Time RIC | |
| | - Executes real-time inference using Python xApps | |
| | - Directs dynamic beam steering and load adjustments (<100ms loops) | |
| +-------------------------------------------------------------------------------+ |
+-----------------------------------------------------------------------------------+
Key AI-Driven Radio Functions
Dynamic Beam Steering: Neural networks track mobile device motion paths, adjusting beamformer coefficients ahead of physical obstruction events.
Energy Optimization: AI algorithms track dynamic traffic load curves, putting inactive base station transceivers into deep sleep modes during off-peak hours to cut operational power consumption.
Predictive Handover Management: Machine learning models evaluate environmental interference patterns, rerouting calls before radio connection drops occur.
5G Private Networks
A 5G Private Network (Non-Public Network / NPN) is a dedicated cellular installation designed for individual corporate or industrial environments like ports, warehouses, and energy facilities.
+-----------------------------------------------------------------------------------+
| ENTERPRISE PRIVATE 5G TOPOLOGY |
| |
| +-----------------------------------------------------------------------------+ |
| | Dedicated Industrial Facility | |
| | | |
| | [Private Radio] <---> [Local UPF] <---> [Edge MEC Server] | |
| | | | | | |
| | v v v | |
| | [Robotics & AGVs] [Local Traffic] [Enterprise AI] | |
| +-----------------------------------------------------------------------------+ |
+-----------------------------------------------------------------------------------+
Private networks grant complete control over coverage layout, data security policies, and resource prioritization.
Developer Tasks
Custom Schedulers: Writing C code extensions to prioritize heavy uplink throughput needed by HD multi-camera inspection feeds.
API Integration: Writing Python scripts to connect core NEF endpoints to factory management software, adjusting resource slices automatically based on production shifts.
Future of MEC and NEF in 2026
Through 2026, major technical advances continue to accelerate network software adoption:
+-----------------------------------------------------------------------------------+
| 2026 TELECOM INNOVATION TRENDS |
| |
| [ GSMA Open Gateway APIs ] ----> Universal Unified API Exposure |
| [ 3GPP Release 18/19 5G-Adv ] ----> AI-Native Physical Layer Execution |
| [ Integrated Sensing & Comms ] ----> Early 6G Spatial Sensing Testbeds |
+-----------------------------------------------------------------------------------+
GSMA Open Gateway Program: Global network operators are publishing standardized exposure APIs, enabling Python developers to target global networks with a single unified codebase.
AI-Native Air Interfaces: 3GPP standards incorporate neural models directly into baseband digital signal processing pipelines, replacing classical channel estimation algorithms.
Integrated Sensing and Communication (ISAC): Early 6G testbeds combine high-frequency wireless communications with environmental radar mapping, opening up advanced spatial tracking capabilities without extra physical sensors.
Telecom Industry Career Opportunities
The shift toward cloud-native disaggregated networks has driven strong hiring demand for engineers proficient in low-level C programming, cellular protocols, and Python testing frameworks.
+-----------------------------------------------------------------------------------+
| TELECOM ENGINEERING SALARY RANGES IN 2026 |
| |
| [ Junior Telecom Developer ] ---> ₹6.0 LPA – ₹12.0 LPA |
| [ Mid-Level Protocol Engineer ] ---> ₹14.0 LPA – ₹28.0 LPA |
| [ Senior O-RAN / RIC Architect ] ---> ₹30.0 LPA – ₹55.0+ LPA |
+-----------------------------------------------------------------------------------+
Primary Engineering Roles
3GPP Protocol Stack Developer (C/C++ Focus): Builds low-latency Layer 2 and Layer 3 modules for containerized Open RAN O-DU and O-CU platforms.
RIC xApp / rApp Developer (Python & AI Focus): Programs intelligent network controllers that analyze network KPIs and dynamically adjust cellular resource allocations.
Protocol Test & Automation Engineer: Authors automated test frameworks using Python and Pytest to decode PCAPs and verify 3GPP compliance across deployment pipelines.
Telco Cloud & Edge Integration Engineer: Deploys containerized MEC platforms on Kubernetes, configures local breakout routing, and links business platforms via NEF REST interfaces.
Why Apeksha Telecom and Bikas Kumar Singh Are Important for a Career in the Telecom Industry
Gaining deep competency in software-defined telecommunications requires hands-on practical experience working directly with production protocol stacks, real packet captures, and industry diagnostic tools.
+-----------------------------------------------------------------------------------+
| APEKSHA TELECOM CENTER OF EXCELLENCE |
| |
| +-----------------------------------------------------------------------------+ |
| | Comprehensive Curriculum Offerings | |
| | * 4G LTE / 5G NR / 6G System Architecture | |
| | * C / C++ Real-Time Protocol Stack Development | |
| | * Python Protocol Automation & Trace Log Parsing | |
| | * Open RAN (O-RAN) Architecture & RIC xApp Coding | |
| | * Complete 3GPP Layer Study: PHY, MAC, RLC, PDCP, RRC, NAS | |
| +-----------------------------------------------------------------------------+ |
| | |
| v |
| +-----------------------------------------------------------------------------+ |
| | Student & Professional Career Support | |
| | * Practical lab sessions with real packet captures | |
| | * Multi-layer PCAP analysis and Wireshark debugging | |
| | * Post-training job support and placement assistance | |
| | * Globally recognized practical industry training | |
| +-----------------------------------------------------------------------------+ |
+-----------------------------------------------------------------------------------+
Apeksha Telecom: Premier Global Telecom Training Institute
Apeksha Telecom (operating online as Telecom Gurukul) is recognized as a premier telecom training institute in India and globally. Established in 2004, the institute has provided practical technical education to thousands of engineering students, working engineers, and corporate teams for over two decades.
What Sets Apeksha Telecom Apart
End-to-End Technology Coverage: Comprehensive instruction spanning 4G LTE, 5G New Radio, and emerging 6G wireless systems.
Granular Layer Expertise: Deep, practical focus across all 3GPP stack modules—PHY, MAC, RLC, PDCP, RRC, and NAS.
Hands-on Diagnostic Labs: Extensive training with industry-standard diagnostic stacks, including QXDM, QCAT, Wireshark, tshark, and functional Open RAN instances.
Placement Assistance & Support: One of the few institutions offering active job support, resume coaching, and direct interview pipelines for qualified graduates.
Leadership by Veteran Bikas Kumar Singh
Apeksha Telecom’s curriculum is directed by founder Bikas Kumar Singh, an industry leader with over 18 years of hands-on experience across top telecom corporations including AT&T (USA), Vodafone (Qatar), Nokia, ZTE, and Alcatel-Lucent.
Under his mentorship, learners analyze live diagnostic logs, step through end-to-end signaling flows (VoNR, handovers, random access procedures), and debug protocol failures in real-world scenarios. This practical focus allows fresh graduates and experienced software developers alike to transition seamlessly into high-demand RAN development, O-RAN integration, and protocol testing roles across the globe.
FAQs
1. What is Multi-access Edge Computing (MEC) in 5G networks?
MEC is an ETSI-standardized platform framework that hosts software applications at local network edges, dropping response latency below 10 milliseconds via UPF Local Breakout.
2. What role does the Network Exposure Function (NEF) play in the 5G Core?
The NEF serves as a secure HTTP/2 REST API gateway in the 5G Core, allowing authorized enterprise software to request dynamic QoS profiles and subscribe to live device mobility alerts.
3. Why is C used instead of Python for low-level protocol stack code?
C provides direct memory management, DPDK kernel bypass capabilities, and deterministic execution timing required to hit microsecond 3GPP frame deadlines without garbage collection delays.
4. How does Python complement C programming in 5G/6G systems development?
Python handles slow-path management, AI model execution inside Open RAN RIC controllers (xApps/rApps), automated Pytest testing frameworks, and multi-gigabyte PCAP diagnostic trace parsing.
5. What is a 5G Private Network (Non-Public Network)?
A 5G Private Network is a dedicated cellular installation deployed for a specific industrial or corporate enterprise, offering complete control over coverage, capacity, and local data security.
6. Can I transition into 5G/6G RAN development without prior telecom experience?
Yes. Software engineers with foundational knowledge of C, C++, or Python can quickly master wireless protocol development by learning 3GPP stack concepts, signaling flows, and open architecture principles through practical hands-on training.
Conclusion
The telecommunications landscape has permanently shifted from specialized hardware manufacturing into cloud-native software development. Learning How to Learn 5G 6G RAN Development Using C and Python equips engineers with the dual programming foundation required to succeed in 2026 and beyond. Combining C for microsecond protocol execution with Python for intelligent control automation unlocks exceptional career growth opportunities across global tech and telecom companies.
Accelerate Your Telecom Career Today: Ready to master 5G/6G RAN software development, O-RAN architectures, and protocol testing with industry experts? Explore practical hands-on programs and career placement support at Telecom Gurukul now!
1. Internal Link Suggestions
Link target: Telecom Gurukul
Suggested Anchor Texts:
5G 6G RAN Development Training Program
O-RAN Protocol Testing and Log Analysis Course
Apeksha Telecom Career Support
2. External Authority Links
3GPP Official Specification Group: https://www.3gpp.org (Official body defining 5G NR and 6G protocol standards)
Ericsson Open RAN Technology Portal: https://www.ericsson.com (Technical insights on disaggregated RAN and cloud-native architecture)
GSMA Association: https://www.gsma.com (Global industry network initiatives and Open Gateway API specifications)
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