The RCR Wireless 6G Forum 2025 brought together leading voices from across the telecom ecosystem to discuss the technologies, challenges, and opportunities shaping the road to 6G. Held virtually and featuring contributions from operators, vendors, and research organisations, the forum focused on how early innovation and collaboration are defining the foundations of the next generation of connectivity.
Among the highlights was a talk by Nancy Friedrich, 6G Solutions Expert at Keysight Technologies, who explored how 6G research and early development are already advancing well ahead of formal standardisation. Her presentation, titled “From 0 to PHY – Innovating Ahead of the Standard”, offered a detailed look at the technologies and strategies being trialled to accelerate the path to 6G.
Nancy began by noting that 6G will not be a radical transformation but rather an evolution of 5G. It will expand on the most successful elements of 5G while integrating new capabilities such as integrated sensing, artificial intelligence, and machine learning. The aim is to simplify specifications, enhance cost efficiency, and address the pain points that limited 5G’s full potential.
A key difference will be that 6G is expected to be standalone from the start, unlike 5G, where most deployments relied on non-standalone architectures. By learning from 5G’s challenges, 6G aims to deliver improved performance and return on investment for operators and the wider ecosystem.
To achieve these goals, research efforts are focusing on both retaining valuable 5G features and introducing new ones. Early work at the physical layer has been exploring candidate technologies across several fronts: the upper mid-band spectrum known as FR3 (7–24.5 GHz), sub-terahertz communications, reconfigurable intelligent surfaces, non-terrestrial networks, and AI-driven enhancements to radio access.
Two main research approaches have emerged. One builds on the 5G New Radio baseline to test potential 6G features collaboratively. The other starts from a clean slate to experiment with simplified 6G concepts and achieve early proof of ideas. Both approaches are helping to refine 6G’s foundation, particularly at the physical and protocol layers.
Among the areas under evaluation are new waveforms, coding schemes, and modulation techniques aimed at improving uplink coverage, energy efficiency, and spectral utilisation. 3GPP has already begun assessing options for waveforms, channel coding, AI/ML integration, and energy efficiency. Enhancements to low-density parity check and polar coding are being considered to deliver better throughput and lower latency.
On the waveform side, 6G is expected to evolve from 5G’s OFDM baseline, with enhancements such as discrete Fourier transform spread OFDM and frequency-domain spectral shaping. Other candidate waveforms like orthogonal sequence division multiplexing and orthogonal time frequency space are being studied for their potential in high-mobility or high-delay environments, although real-world deployment challenges remain.
Modulation research is also advancing, with probabilistic and geometric constellation shaping seen as promising methods for increasing robustness and power efficiency. The aim is to balance higher data rates with reduced complexity for devices.
Massive MIMO will continue to play a central role in 6G, particularly as networks move into FR3 frequencies. The use of larger antenna arrays will offset propagation losses at higher frequencies and enable extremely focused pencil-beam transmissions. This evolution is expected to bring major gains in spectral efficiency and support for dense user environments.
Another important enabler will be Multi-Radio Access Technology Spectrum Sharing (MRSS), allowing 5G and 6G to coexist within the same frequency bands. By simplifying spectrum allocation and management, MRSS will make spectrum reforming more efficient and support dynamic spectrum sharing through AI-driven scheduling and resource allocation.
AI and machine learning are poised to transform every layer of the 6G architecture. At the physical layer, they will optimise channel state feedback, beam prediction, and positioning accuracy. Within the RAN, AI will drive smarter beam management, energy optimisation, and predictive maintenance. AI integration will also extend to devices, enabling adaptive modulation and improved channel estimation.
Digital twins and advanced simulation platforms are becoming vital tools in 6G research. They allow engineers to emulate realistic network conditions, generate synthetic data, and test AI algorithms at scale before real-world deployment. This accelerates development and builds confidence in AI-driven network models.
Finally, the industry is gradually shifting from fixed, hardware-centric implementations toward flexible, software-based approaches. This move will support faster iteration, scalable pricing, and easier integration of AI and ML across the 6G stack.
Nancy concluded by emphasising that innovation ahead of the standard is crucial to shaping a successful 6G future. Through simulation, testing, and early experimentation, the industry can identify viable technologies, refine their performance, and ensure smoother standardisation and deployment.
Her talk is embedded below:
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