Overview The 3GPP Spec Excerpt Finder is a browser tool for pulling exact passages out of 3GPP specifications. You give it a release (for example Rel-17), optionally a spec number such as 38.331, and a search type: RAN parameter, topic or procedure, feature explanation, or free text. It returns the matching clauses word for word, shown as dark text on a white background. Each excerpt carries a citation (3GPP TS 38.331 V17.5.0 (Rel-17), clause 5.3.5.1) and the surrounding para

In 4G LTE and 5G New Radio (NR), Orthogonal Frequency Division Multiplexing (OFDM) has been the undisputed king of physical layer multi-carrier waveforms. OFDM works exceptionally well in static or low-speed environments like homes, offices, and walking speeds. However, as we move toward 6G—where devices communicate on high-speed bullet trains (350+ km/h), in low-Earth orbit (LEO) satellites moving at 28,000 km/h, and in autonomous vehicle-to-everything (V2X) swarms—OFDM hits

Introduction The sixth generation (6G) of wireless communications is expected to fundamentally transform mobile networks from pure communication platforms into intelligent sensing and communication infrastructures. One of the most revolutionary technologies enabling this transformation is Integrated Sensing and Communications (ISAC). ISAC combines wireless communication and environmental sensing within a unified network infrastructure, allowing the same radio signals, spect

1. Introduction The exponential growth in mobile data traffic, driven by 4K/8K video, cloud gaming, AR/VR, industrial IoT, and private 5G networks, has forced wireless systems to evolve beyond traditional antenna systems. One of the most transformative technologies enabling 5G performance is Massive MIMO (Multiple Input Multiple Output). Unlike conventional MIMO (2x2, 4x4, 8x8), Massive MIMO scales antenna elements to tens or even hundreds at the base station, enabling spatia

1. Introduction Modern 5G radio access networks have reached a level of complexity where traditional automation approaches are no longer sufficient. While machine learning has been widely adopted in telecom analytics, most deployed solutions still behave as passive systems: they ingest data, run inference, and output a score, label, or alert. In practice, experienced RAN engineers do not work this way. They observe symptoms, form hypotheses, validate those hypotheses by check

1.Introduction Cloud and Network Function Virtualization (NFV) for 5G networks represent a fundamental shift in how telecommunication networks are designed and managed. NFV decouples network functions from specialized hardware, allowing them to run as software on standard cloud infrastructure. This virtualization enables 5G networks to be more flexible, scalable, and cost-efficient by leveraging cloud-native principles and automation. It allows operators to dynamically alloca

Case Study – Low throughput issue mitigation Introduction The complexity of today’s telecom networks—driven by 5G’s massive scale, distributed Radio Access Network (RAN) architectures, and virtualized infrastructure—makes operational reliability and proactive fault management both a necessity and a challenge. Static rules and threshold-based monitoring techniques, once the backbone of network assurance, are now insufficient as data velocity, volume, and variety continue to gr

Introduction Artificial Intelligence (AI) and Machine Learning (ML) are becoming integral to the evolution of 5G Radio Access Networks...

Introduction As the wireless industry looks beyond 5G, 6G networks are expected to revolutionize not only connectivity speeds but also...

Introduction As 6G research gathers momentum, the demand for higher data rates, massive connectivity, and extreme spectral efficiency is...

Introduction We’ve all seen how 5G has transformed the world — faster internet, low latency for gaming, support for smart cities, and...