UK Slowest as OpenSignal Tests Early 5G Mobile Broadband Speeds

Crowd-sourced analyst firm OpenSignal has today published the first results from their initial real-world benchmarks of 5G based mobile broadband networks across 8 countries (i.e. those that have launched the service). The highest maximum speeds were seen by 5G users in the USA (1815Mbps), while the UK scored the lowest (569Mbps).

On the surface this may seem like a poor outcome (assuming you think 569Mbps is slow) and we don’t yet know what the average speeds will become, although at the same time it’s also important not to read too much into these statistics and there are several reasons for that. Firstly, the only UK operator to have any kind of live commercial 5G service running during the testing window was EE (1st April to 30th June 2019).

Secondly, EE can only harness a 40MHz slice of the 3.4GHz spectrum band until Ofcom auctions off the next batch in 2020, while other countries (e.g. USA) have been able to harness several bands simultaneously (Carrier Aggregation). Some of those countries have also been able to use bigger frequency slices of 100MHz, which is somewhat of a sweet spot for 5G networks.

On top of that we mustn’t lose sight of the fact that none of the early 5G networks have many real-world customers (i.e. low network congestion – not very reflective of eventual take-up) and the initial hardware being deployed doesn’t always support all of 5G’s claimed capabilities. Suffice to say that 5G is in its infancy and when 4G first went live it wasn’t all that much faster than 3G but that did change.

On the upside the table gives some indication that even early 5G services can eventually become nearly 3x faster than 4G, once they get access to spectrum bands. In the USA they do make some use of higher frequency mmWave bands too, although we don’t expect to see UK operators harnessing those for awhile (most of the UK bands due for auction in 2020 are closer to those used by 4G).

As usual there are other caveats to this sort of crowd-sourced data. For example, app-based crowd-sourced data such as this could be impacted by any limitations of the devices being used, which at the same time removes the ability to adopt a common type of hardware in order to establish a solid baseline of performance.