The move towards 6G is often described in terms of higher data rates, lower latency and improved reliability. While these remain important, efficiency has become a central theme. Traditionally, the industry has measured efficiency through Spectral Efficiency (SE) and Energy Efficiency (EE). In a recent paper, Joseph Boccuzzi has proposed an additional metric that could be key to defining 6G: Radio Resource Utilisation Efficiency (RUE). He shared his work on LinkedIn where it sparked an engaging discussion among researchers, practitioners, and other industry players.
The idea behind RUE is straightforward but powerful. It measures how effectively the available radio resources, such as spectrum, time slots and data symbols, are being used to deliver services. When the author applied this to a commercial 5G configuration, the result was just 47%. In other words, more than half of the available resources are not directly contributing to useful throughput. This highlights that while 5G has made significant progress, there is still a great deal of untapped potential. For 6G, the paper proposes raising this figure to around 75%, which would represent a step change in overall efficiency.
The paper categorises the factors that impact spectral efficiency into three groups/categories: radio resources, wireless channel limitations, and implementation losses. Of these, the largest impact comes from the way radio resources are structured in 5G. Slot formats, pilot symbols, coding rates and cyclic prefix overheads all reduce the effective throughput before the channel or hardware is even considered. Wireless channel rank deficiencies, particularly in MIMO systems, further limit gains as the real-world environment often prevents all layers from being fully utilised. Implementation losses, such as channel estimation errors or frequency offseets, add another layer of degradation.
Boccuzzi’s analysis shows that the biggest opportunity for improvement lies in radio resource utilisation. If 6G can introduce approaches like full duplex (FD) operation, Pilot Symbol-Less communication, or AI/ML based receivers, then significant efficiency gains become achievable. Similarly, techniques such as Reconfigurable Intelligenent Surfaces (RIS) and Multi-User MIMO (MU-MIMO) could help address channel rank limitations. Machine Learning (ML) also has a role in reducing implementation losses, but the paper makes clear that these are the smallest contributor compared with the structural inefficiencies of radio resource use.
Another important aspect discussed in the paper is the impact of Transmission Bandwidth (BW). Moving from 100 MHz to 1.6 GHz can dramatically increase throughput, but only under certain conditions. Close to the cell centre, where signal strength is high, wider bandwidths deliver almost linear gains. At the cell edge, however, the benefits are far more limited. This has implications for scheduling and network design, ensuring that resources are allocated where they deliver the most benefit.
The study also compares traditional cellular deployments with Cell-Free Massive MIMO (CF-MaMIMO). The latter offers a far more uniform quality of service across the coverage area, particularly at the cell edge. In fact, the analysis shows that Cell-Free deployments can provide up to 3.8 times the spectral efficiency of typical cellular networks under certain conditions. This supports the growing view that distributed access points as well as antenna systems may play a central role in 6G.
What makes this work valuable is not just the detailed modelling but the introduction of a new way to measure performance. By focusing on RUE, the paper highlights the inefficiencies in today’s systems and provides a practical target for future networks. It shifts the discussion from peak spectral efficiency, which is often a theoretical number, to real-world utilisation that directly impacts user experience.
The LinkedIn post where this work was shared has already generated thoughtful debate, with many recognising that improving utilisation will yield bigger gains than chasing headline peak rates. Some have connected the metric to AI for RAN research, while others see it as a foundation for new architectural directions. By proposing RUE as a guiding measure, the paper provides the industry with a clear and quantifiable goal as it defines 6G.
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