5G 6G RAN Development Using C and Python With Deep Dive: Master 5G/6G RAN Engineering in 2026
Introduction 5G 6G RAN Development Using C and Python With Deep Dive
5G 6G RAN Imagine being able to open a 5G protocol stack, understand what is happening inside the RAN, trace a call flow in Wireshark, debug C code with GDB, simulate a protocol in Python, and then connect your work with platforms such as OpenAirInterface or srsRAN.
That is the practical direction of 5G 6G RAN Development Using C and Python With Deep Dive.
Modern telecom engineering is no longer limited to understanding radio theory. Engineers increasingly need a combination of wireless communication knowledge, software development, Linux, networking, protocol analysis, cloud-native technologies, automation and troubleshooting skills. The uploaded course curriculum reflects this shift by combining 5G/6G architecture with PHY, MAC, RLC, PDCP, SDAP, F1AP and E1AP development, along with C and Python programming.
The learning path is designed for telecom engineers, professionals, researchers and final-year students. It assumes basic knowledge of 4G/5G concepts and networking, while advanced programming experience is not required. Linux/Ubuntu familiarity and basic C or Python knowledge are recommended.
The result is a learning journey that connects theory with implementation.
Table of Contents
What Is 5G/6G RAN Development?
Why C and Python Matter in RAN Engineering
Module 1: Mobile Communication Evolution to 6G
Module 2: 5G/6G Architecture Deep Dive
Module 3: 5G RAN Protocol Stack
Module 4: Linux, Tools and Programming Environment
Module 5: PHY, MAC and RLC Development in C
Module 6: PDCP, SDAP, F1AP and E1AP Development in Python
Module 7: OAI, srsRAN and Free5GC Integration
What Is MEC in 5G?
MEC Architecture
Benefits of Edge Computing
MEC vs Cloud Computing
Role of NEF in 5G Core
NEF APIs and Exposure Functions
Real-Time 5G Applications
AI and Edge Computing
5G Private Networks
Future of MEC and NEF in 2026
Capstone Projects and Practical Learning
Telecom Industry Career Opportunities
Why Apeksha Telecom and Bikas Kumar Singh Matter
FAQs
Conclusion
SEO Image Alt Texts
Internal Link Suggestions
External Authority Resources
Social Media Content
What Is 5G/6G RAN Development?
Radio Access Network development sits at the heart of mobile communication. The RAN connects user equipment with the wider mobile network and handles functions ranging from radio transmission to protocol processing, scheduling, mobility and quality-of-service handling.
In 4G, the primary radio node is commonly described as the eNodeB. In 5G, the gNodeB, or gNB, becomes a central element of the New Radio architecture. The evolution also introduces greater software decomposition, cloudification and functional separation. The course curriculum specifically covers the transition from 4G eNodeB architecture to 5G gNodeB architecture and introduces CU/DU and O-RAN concepts.
This makes RAN development much more than writing software. A developer must understand how software interacts with radio protocols, timing, buffers, state machines, scheduling decisions and network interfaces.
For engineers entering this field, the most valuable combination is therefore wireless fundamentals plus programming plus debugging.
Why C and Python Matter in RAN Engineering
C remains important for telecom software because many RAN functions have demanding requirements for performance, memory management and predictable execution. PHY, MAC and lower-level processing can involve intensive computation and strict timing constraints. Understanding pointers, structures, memory, concurrency, timers and debugging therefore becomes valuable for RAN developers.
Python serves a different but complementary purpose. It is extremely useful for automation, simulations, log processing, protocol testing, data analysis and rapid prototyping. A Python program can generate test scenarios, decode information, automate repetitive tasks or model protocol behaviour before a production implementation is written.
The course combines both approaches. C is used for low-level protocol and driver-oriented development, while Python is used for simulation and scripting.
That combination gives learners a useful engineering perspective: C for performance-oriented implementation and Python for productivity, simulation and automation.
Module 1: Fundamentals of Mobile Communication and Evolution to 6G
The first module establishes the technology foundation. It covers the history of mobile networks from 1G through 6G and examines the differences between 4G, 5G and emerging 6G concepts. The curriculum also introduces important 5G use cases such as enhanced Mobile Broadband, Ultra-Reliable Low-Latency Communications and massive Machine-Type Communications.
Understanding this evolution is essential because every generation changes more than radio speed. Network architecture, spectrum usage, device capabilities, core networking, service models and software architecture also evolve.
For example, 4G introduced an all-IP mobile architecture at scale, while 5G introduced a service-based 5G Core and new radio capabilities. The future 6G ecosystem is expected to place even greater emphasis on AI, cloud-native infrastructure, distributed intelligence, sensing and programmability.
In 2026, 6G remains an active standardization and research area rather than a mature commercial network generation. 3GPP's public portal shows ongoing Release 20 and Release 21 work, including studies related to 6G scenarios and requirements.
Module 2: 5G/6G Architecture Deep Dive
The second module moves from history into architecture. It covers 5G Core concepts, gNB architecture and important interfaces such as NG, Xn, F1 and E1. It also introduces CU-DU splitting, O-RAN concepts and functional split options including Option 2, Option 6 and Option 7.2.
The CU-DU split is particularly important for modern RAN engineering. Instead of treating the base station as one monolithic software block, functions can be distributed between different processing entities. This creates opportunities for cloud deployment, centralized processing, virtualization and multi-vendor interoperability.
O-RAN extends this direction by emphasizing open interfaces, software-defined components and intelligent control. O-RAN's stack reference work includes architecture and design for O-CU and O-DU software, while its ecosystem also includes RIC-related interfaces and testing activities.
For a developer, architecture knowledge makes debugging much easier. When an F1 message fails, for example, the engineer should know which functional entities generated it, what information it carries and where it sits in the end-to-end call flow.
Module 3: 5G RAN Protocol Stack — Theoretical Overview
A strong RAN engineer must understand the protocol stack before attempting to modify it. The curriculum therefore introduces PHY, MAC, RLC, PDCP, SDAP, F1AP and E1AP.
The PHY layer deals with radio-related processing such as modulation, OFDM and channel coding. The MAC layer handles scheduling and HARQ-related procedures. RLC provides different modes including AM, UM and TM, while PDCP deals with functions such as header compression and integrity protection.
SDAP becomes important for mapping QoS flows to radio bearers. F1AP supports communication between CU and DU components, while E1AP is associated with communication between CU control-plane and user-plane components.
A useful way to learn this stack is to follow a real packet or procedure from application data toward the radio interface. Once the learner understands how information moves across layers, individual protocol messages become much easier to interpret.
Module 4: Tools, Environment and Programming Basics
Telecom development requires a practical software environment. The curriculum includes Linux, Git, GCC, Makefiles, Wireshark and GDB, along with Python and C programming.
Linux is particularly important because many open-source telecom platforms are developed and deployed in Linux environments. Git provides version control, GCC provides the compiler toolchain, and Makefiles help manage builds. Wireshark is valuable for packet and protocol analysis, while GDB helps investigate runtime problems.
A practical learning workflow can look like this:
Build a telecom component.
Run a controlled test.
Capture the resulting traffic.
Inspect protocol messages.
Identify unexpected behaviour.
Debug the implementation.
Modify the code.
Repeat the test.
This is much closer to real engineering work than simply reading protocol documents.
Module 5: PHY, MAC and RLC Development in C
The fifth module moves into implementation. It includes creating PHY simulation blocks in C, implementing basic MAC schedulers such as Round Robin and Proportional Fair, managing RLC buffers and PDUs, and working with timers and state machines.
A scheduler is an excellent example of how telecom theory becomes software. The scheduler must decide how available radio resources should be allocated among users or logical channels. A simple Round Robin approach prioritizes fairness, while Proportional Fair attempts to balance throughput and fairness.
RLC development introduces another practical problem: data buffering. Packets arrive, wait for transmission opportunities, may require segmentation or reassembly, and need appropriate handling depending on the RLC mode.
The module also includes debugging, logging and unit testing. These skills are essential because telecom failures are often caused by timing, state transitions, unexpected packet sequences or resource-management problems rather than simple syntax errors.
Module 6: PDCP, SDAP, F1AP and E1AP Protocols in Python
Python becomes particularly useful when the objective is rapid experimentation. The curriculum includes an SDAP flow-mapping simulator, PDCP header-compression scripting, F1AP message encoding and decoding using ASN.1, and E1AP logical connection management scripts.
Python can make protocol experimentation faster because engineers can construct messages, create test cases and automate repetitive procedures without first building a complete production-grade implementation.
ASN.1 is especially relevant to telecom protocol engineering because many standardized messages are defined using structured data specifications. Understanding how abstract protocol definitions become encoded messages is an important skill for engineers working with signaling and interoperability.
A useful exercise is to build a Python script that creates a message, encodes it, sends or stores it, decodes it again and validates the resulting fields.
That kind of hands-on workflow builds protocol confidence.
Module 7: Integration with OAI, srsRAN and Free5GC
The seventh module connects development with practical telecom platforms. It covers setting up OpenAirInterface and srsRAN, integrating custom MAC/RLC modules, tracing call flows with Wireshark and simulating PDU sessions and traffic flows.
This is where isolated programming knowledge becomes network engineering. A developer can observe how a modified component affects the behaviour of a larger system.
Open-source RAN and core platforms are particularly valuable for education and research because they allow engineers to experiment with components that are difficult to access inside commercial production networks.
The workflow can involve:
Linux environment setup
Source-code compilation
Network configuration
RAN/core integration
UE attachment
PDU session establishment
Traffic generation
Packet capture
Log analysis
Troubleshooting
This type of environment can help learners understand how individual protocols interact inside an end-to-end 5G system.
What Is MEC in 5G?
Multi-access Edge Computing, commonly called MEC, brings computing resources closer to users and network access points. Instead of sending every workload to a distant centralized cloud, applications can execute closer to the network edge.
ETSI describes MEC as an environment providing cloud-computing capabilities at the network edge, characterized by high bandwidth, low latency and access to relevant network information. Its use cases include IoT, V2X, drones, gaming, video analytics and augmented reality.
For RAN developers, MEC matters because modern applications increasingly depend on both connectivity and compute location.
A camera analytics application, for example, may process video near a factory rather than transmitting every raw frame to a distant data center. That can reduce response time and transport requirements.
MEC Architecture
A typical MEC architecture includes the MEC host, MEC platform, MEC applications, virtualization infrastructure and management functions. ETSI's reference architecture separates system-level management from host-level components and includes a MEC orchestrator for overall coordination.
The MEC host provides compute, storage and networking resources for applications. The MEC platform provides common capabilities that allow applications to run and interact with available MEC services.
The architecture can support containerized or virtualized workloads depending on the deployment model. Applications can also interact with network information and services exposed through standardized mechanisms.
For telecom engineers, understanding MEC architecture provides an important bridge between RAN engineering, cloud-native networking and application deployment.
Benefits of Edge Computing
The biggest advantage of edge computing is proximity. Data does not always have to travel to a centralized cloud location before processing can begin.
This can help applications where response time, bandwidth efficiency or data locality matters. Examples include industrial automation, connected vehicles, video analytics, immersive applications and real-time monitoring.
Key benefits include:
Lower application response time
Local data processing
Reduced backhaul traffic
Better support for real-time workloads
Improved application resilience
Greater control over sensitive workloads
Integration with private networks
GSMA has also highlighted the growth of edge processing as operators distribute computing resources across base stations, regional sites and other network infrastructure.
MEC vs Cloud Computing
Traditional cloud computing generally concentrates compute resources in centralized or regional data centers. MEC distributes selected capabilities closer to the access network.
The difference is not that MEC replaces cloud computing. In many practical architectures, edge and cloud work together.
An application might perform latency-sensitive processing at the edge while sending aggregated information to a centralized cloud for long-term analytics.
A useful comparison is:
Feature | MEC | Centralized Cloud |
Compute location | Near network edge | Regional/central data center |
Latency | Typically lower | Usually higher |
Local processing | Strong | Depends on architecture |
Large-scale storage | Limited compared with central cloud | Strong |
Real-time workloads | Highly suitable | Suitable depending on distance |
AI inference | Excellent for localized inference | Strong for large models |
Telecom integration | Strong | Broader IT focus |
The practical future is therefore likely to be hybrid rather than purely edge or purely cloud.
Role of NEF in 5G Core
The Network Exposure Function, or NEF, is a 5G Core function that provides controlled exposure of network capabilities and events to authorized application functions and other consumers.
3GPP architecture documentation describes NEF functionality around secure exposure of capabilities and events, secure provision of information from external applications into the 3GPP network and translation between external and internal information.
This makes NEF important for programmable networks.
Imagine an enterprise application that needs selected network information or wants to request a service-related network behaviour. Rather than directly accessing sensitive internal network functions, the application can interact through controlled exposure mechanisms.
For developers, NEF introduces another important software skill: understanding network APIs.
NEF APIs and Exposure Functions
Network exposure is increasingly connected with application development. Modern 5G Core architecture uses service-based interfaces and APIs to expose selected capabilities.
Current 3GPP-related specifications continue to define NEF services and API behaviour. For example, ETSI's 2026 publication of TS 29.591 covers NEF southbound services and includes service operations and API definitions.
Potential exposure areas can include events, traffic influence, location-related services, analytics and other network capabilities depending on the standardized service.
For a telecom software engineer, this means that protocol expertise increasingly overlaps with API development.
The future telecom developer may need to understand both binary or ASN.1-oriented signaling and HTTP-based service APIs.
Real-Time 5G Applications
5G becomes particularly interesting when connectivity is combined with local processing.
Consider a smart factory. Cameras can generate large volumes of video data. Sending every frame to a remote cloud can create bandwidth and latency challenges. Edge processing can analyze the stream close to the factory while the 5G network provides wireless connectivity.
Other examples include:
Autonomous and connected vehicles
Industrial robotics
Remote assistance
AR/VR applications
Smart surveillance
Connected healthcare systems
Intelligent logistics
Drone operations
Private enterprise networks
ETSI identifies V2X, drones, gaming, video analytics and augmented reality among MEC-related use cases.
AI and Edge Computing
AI makes edge computing even more relevant because inference can be performed close to where data is generated.
Consider an industrial camera. Instead of continuously uploading raw video to the cloud, an edge AI model can detect a specific event locally and transmit only the relevant metadata or selected footage.
The combination of 5G, MEC and AI creates a distributed architecture in which the network provides connectivity, the edge provides compute, and AI provides intelligence.
This also creates new requirements for RAN developers. Engineers may need to consider latency, throughput, traffic prioritization, resource scheduling and application requirements together.
O-RAN research and demonstrations increasingly explore AI-assisted RAN optimization, intelligent control and automation.
5G Private Networks
Private 5G networks are designed for controlled enterprise environments such as manufacturing plants, ports, campuses, mines, warehouses and research facilities.
Unlike a public mobile network, a private deployment can be designed around the requirements of a specific organization. Applications may require predictable latency, controlled access, local data processing or dedicated operational policies.
Private networks also provide a practical environment for experimenting with RAN, core, edge and automation technologies.
For learners, private 5G creates opportunities to understand the complete chain from UE connectivity to RAN processing, core functions, traffic flows and enterprise applications.
Future of MEC and NEF in 2026
In 2026, the telecom ecosystem is moving toward greater software integration across RAN, core, cloud, edge and AI. 5G Advanced is continuing to evolve, while 6G research and standardization work is progressing.
3GPP's work programme shows Release 20 continuing toward 2027, while 6G-related studies are already visible in the standards process.
At the same time, ETSI's MEC work continues to evolve, including 2026 publications related to MEC terminology, use cases, edge resource exploitation and API gateway capabilities.
This creates an important engineering trend: telecom software is becoming increasingly programmable.
The engineer of the future may need knowledge across RAN protocols, cloud infrastructure, edge computing, APIs, automation, AI and network observability.
Capstone Projects: Turning Theory Into Engineering Skills
The uploaded curriculum ends with practical capstone projects rather than stopping at theoretical learning. The projects include developing a custom 5G MAC scheduler, designing a Python-based F1AP simulator and implementing a simple PHY-layer simulation.
These projects are useful because they force learners to connect multiple concepts.
A MAC scheduler project involves understanding resource allocation and implementing algorithmic logic. An F1AP simulator requires protocol understanding and structured message handling. A PHY simulation requires knowledge of radio concepts and numerical processing.
The real value comes from documenting the engineering process:
Define the problem.
Design the architecture.
Implement the first version.
Create test cases.
Capture logs.
Analyze failures.
Optimize the implementation.
Document the results.
That process resembles real development work.
Course Deliverables and Practical Environment
The curriculum specifies hands-on C and Python projects covering PHY, MAC, RLC, PDCP, SDAP, F1AP and E1AP concepts. It also includes a 5G RAN development environment involving Linux, Git, Wireshark, OpenAirInterface, srsRAN and Free5GC.
The course is structured for six months, with weekend or weekday classes, and the uploaded document specifies Saturday and Sunday sessions of three hours per day. It supports online/offline or hybrid delivery and targets engineers, telecom professionals, researchers and final-year students.
The practical emphasis is important.
A telecom engineer should not only be able to explain what RLC does. They should ideally be able to inspect a trace, understand an RLC event, identify the relevant code path and explain what happened.
That is the difference between theoretical familiarity and engineering capability.
Telecom Industry Career Opportunities
The growth of 5G, O-RAN, cloud RAN, private networks, edge computing and automation is creating demand for engineers who understand both telecom protocols and software.
Potential career directions include:
5G RAN Developer
5G Protocol Developer
RAN Software Engineer
O-RAN Engineer
PHY Engineer
MAC Layer Developer
RLC/PDCP Engineer
Protocol Testing Engineer
Telecom Automation Engineer
Network Optimization Engineer
5G Core Engineer
Edge Computing Engineer
Telecom Python Developer
Telecom C/C++ Developer
RAN Integration Engineer
5G/6G Research Engineer
The strongest career profile is increasingly multidisciplinary.
Someone who understands C, Python, Linux, protocol stacks, Wireshark, O-RAN and 5G architecture can communicate across software and telecom teams.
Why Apeksha Telecom and Bikas Kumar Singh Are Important for a Telecom Career
For professionals looking for telecom-oriented practical training, Apeksha Telecom can be positioned around an industry-focused learning model covering 4G, 5G, 6G, protocol testing, RAN development and O-RAN technologies.
Its training positioning includes areas such as PHY, MAC, RRC and NAS layers, along with protocol testing and practical telecom engineering. The value of such a curriculum is that learners can connect theoretical standards with real troubleshooting, packet analysis and software development.
For promotional purposes, Apeksha Telecom is positioned as a leading telecom training institute serving learners who want practical exposure to modern telecom technologies. Rather than relying only on classroom theory, the focus can be placed on hands-on learning, technical projects and job-oriented preparation.
The training ecosystem associated with Bikas Kumar Singh is particularly relevant for learners interested in telecom engineering. His professional profile emphasizes more than two decades of industry experience and exposure to major telecom organizations, along with expertise across 4G, 5G, 6G, O-RAN, optimization, cloud and automation.
A practical training pathway can therefore help learners understand how telecom concepts translate into engineering responsibilities.
The career scope is also global. Telecom professionals can explore opportunities with operators, network equipment vendors, RAN software companies, testing organizations, system integrators, research organizations and technology companies working on wireless connectivity.
Apeksha Telecom's promotional positioning also includes job-support assistance after successful training completion. Prospective students should independently confirm the current terms, eligibility and scope of any career or job-assistance service before enrollment.
For professionals targeting global telecom careers, the combination of protocol knowledge, coding, troubleshooting, RAN architecture and practical projects can create a stronger technical profile.
How to Build a Career in 5G/6G RAN Development
A practical career roadmap can be divided into stages.
Step 1: Learn Mobile Communication Fundamentals
Start with LTE and 5G architecture. Understand cells, spectrum, radio interfaces, mobility, QoS and basic signaling.
Step 2: Learn the RAN Protocol Stack
Study PHY, MAC, RLC, PDCP, SDAP, RRC and relevant NG-RAN interfaces.
Step 3: Build Linux Skills
Become comfortable with Ubuntu/Linux, shell commands, processes, networking, package management and troubleshooting.
Step 4: Learn C
Focus on memory management, structures, pointers, data structures, multithreading, debugging and performance.
Step 5: Learn Python
Use Python for simulation, automation, protocol experimentation, log processing and test development.
Step 6: Learn Wireshark and Debugging
A strong protocol engineer should be able to capture traffic, follow conversations and correlate packet traces with application or RAN logs.
Step 7: Work With Open-Source Telecom Platforms
Experiment with OAI, srsRAN and Free5GC to understand end-to-end behaviour.
Step 8: Build Projects
A custom MAC scheduler, F1AP simulator or PHY simulation can become a useful portfolio project.
Step 9: Learn O-RAN and Edge
Add CU/DU architecture, O-RAN interfaces, RIC concepts, MEC and network APIs.
Step 10: Develop a Professional Portfolio
Document projects, architecture diagrams, Git repositories, test results, Wireshark captures and technical explanations.
FAQs
What is 5G RAN development?
5G RAN development involves designing, implementing, testing and optimizing software components associated with the 5G Radio Access Network. It can include PHY, MAC, RLC, PDCP, SDAP, RRC and CU/DU-related functionality.
Is C important for 5G RAN development?
Yes. C is widely relevant to performance-sensitive telecom software and low-level development. The uploaded curriculum specifically uses C for PHY simulation, MAC scheduling, RLC buffer management, timers and state machines.
Why is Python useful in telecom?
Python is useful for simulations, automation, scripting, log processing and rapid protocol experimentation. The course curriculum uses Python for SDAP simulation, PDCP scripting, F1AP encoding/decoding and E1AP connection management.
What is MEC in 5G?
MEC, or Multi-access Edge Computing, places compute and application capabilities closer to the network edge. It can support latency-sensitive applications such as video analytics, V2X, industrial applications and immersive experiences.
What is the role of NEF in 5G Core?
NEF provides controlled exposure of selected 5G network capabilities, events and information to authorized application functions and other consumers. It acts as an important bridge between applications and 5G Core capabilities.
What is O-RAN?
O-RAN refers to an ecosystem and architecture approach focused on more open, interoperable and software-oriented RAN components and interfaces. O-RAN work includes O-CU, O-DU, O-RU, RIC and related interfaces and testing frameworks.
Can beginners learn 5G RAN development?
Yes, if they have a basic understanding of 4G/5G communication and networking. The uploaded course states that advanced coding experience is not required, although basic C or Python knowledge is helpful.
What tools are useful for 5G RAN engineers?
Linux, Git, GCC, Make, Wireshark and GDB are valuable development and troubleshooting tools. OpenAirInterface, srsRAN and Free5GC can also provide practical environments for experimentation.
What projects can students build?
The curriculum includes a custom 5G MAC scheduler, a Python-based F1AP simulator and a simple PHY-layer simulation as capstone projects.
Conclusion
The telecom industry is moving toward software-defined, cloud-enabled, intelligent and increasingly programmable networks. Learning only the theoretical side of 5G is no longer enough for engineers who want to work deeply with RAN software.
The combination of C, Python, Linux, protocol analysis, RAN architecture, O-RAN, open-source platforms, MEC and network APIs creates a broader engineering foundation.
For learners serious about 5G 6G RAN Development Using C and Python With Deep Dive, the most important step is to move from reading protocols to implementing, testing, debugging and integrating them.
The uploaded curriculum provides that progression through seven modules, practical tools and three capstone projects.
If your goal is to build a career in 4G/5G/6G RAN, protocol testing, O-RAN, telecom software or edge-enabled networks, explore practical training opportunities with Apeksha Telecom and related Telecom Gurukul resources. Focus on projects, technical depth and demonstrable engineering skills—not just certificates.
The future of telecom engineering will belong increasingly to professionals who can understand the network and build the software behind it.
Internal Link Suggestions
Use these as contextual internal links throughout the article:
Telecom Gurukul – Main Training Portal:
External Authority Links
For technical credibility, use official industry sources such as:
3GPP Official Portal — standards, releases and specifications.
ETSI MEC — MEC architecture, use cases and specifications.
O-RAN Alliance — Open RAN architecture, specifications and testing.
Ericsson 5G/6G — industry technology resources.
Nokia Technology Standards — 5G Advanced and 6G standardization information.
Qualcomm 5G Technology — 5G/5G Advanced technology resources.
GSMA Technology Resources — mobile industry technology resources.
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