To assure reliability and performance, and avoid potential problems such as insertion loss (weakened signal), back reflection (signal is diverted back to its source), or a total system shutdown, it’s essential that all connections are perfectly clean. This is especially important with a 5G network because every milliwatt of power is necessary for optimum connectivity and peak performance.
5G means that, for the first time, last-mile latency will often be less than backbone latency. If your data center is a long way from lots of your customers, your quality of service will be poorer (i.e. noticeably slower) than competitors with physically closer data centers. The potential answer to this problem has been around for a while – edge and fog computing. These may finally come into their own as last-mile latency drops and the sheer volume of data from the IoT skyrockets.
This week, I read an article stating that 5G “gives developers the ability to scale up projects more easily because there’s no need to build extensive fiber-optic networks to keep data flowing.” This couldn’t be further from the truth. In fact, fiber is the essential backbone for all 5G networks to operate, for fronthaul, midhaul, backhaul, and the densification needed to network between small cells.
The rollouts for 5G will be expensive, but analytics and machine learning can help operators plan their 5G rollouts in the most effective and customer-centric ways. Here are three ways how: Troubleshooting 5G network performance; Scheduling beamforming in massive MIMO networks to maximize capacity and coverage investments; and improving the positioning of indoor base stations.
In a mere four years, more than one billion users will rely on 5G. The emerging fifth-generation broadband network promises speeds at least seven times faster than the average 4G LTE browsing experience. While the average 4G browsing speeds run at an average of 56 Mbps, 5G would bump speeds up to 490 Mbps. That increased speed and powerful connection means big things for businesses seeking to pull off competitive digital transformations. But a broader, faster network also brings greater risk. Cybercriminals are always on the lookout for new, sophisticated ways to attack, so they’ll naturally take advantage of 5G’s promise.
For the electrical contractor, the promise of IoT could be fully unleashed with 5G. The real game changer will be sensor density, potential installation transmitters and supportive technologies such as 5G distributed antenna systems (DAS). The construction site could also be enhanced when 5G hot spots emerge. Think of how low latency and high bandwidth could upgrade the performance of AR goggles, perhaps working with BIM on site and back at the office, and other wireless and mobile tech.
Hargray Fiber will provide the critical infrastructure at Curiosity Lab at Peachtree Corners, a 5G Smart City incubator. Throughout Curiosity Lab, Hargray’s fiber optic-cable will serve as the key infrastructure backbone, with all services using or connected to the lab’s network benefiting from Hargray’s efficient, seamless transfer of data.
Digital transformation is coming to a warehouse near you. In fact, it may already be in place. Consider this: there were 4,000 robotic warehouses in operation worldwide last year. By 2025, four million commercial robots will be at work in 50,000 warehouses across the globe, forecasts say. That’s a 12-fold increase in the span of just six years. The key to the success for a smart warehouse? Not the robots. Or the management systems. It’s connectivity that is making the industrial internet of things (IIoT) a reality on a massive scale. 4G LTE and 5G networks are up to the task.
In this interview with TIA’s Harry Smeenk, reviews how TIA has taken 5G and IoT, and network evolution and next-generation networking, and put them into use-case examples for edge data centers and smart buildings.
A growing number of operators recognize that the network efficiency brought about by automation is integral to their ability to manage the complexity of 5G. This is especially true with heterogeneous equipment meant to deliver end-to-end services. An early example is Vodafone, which increased its network optimization speeds by a staggering 45,000 percent by implementing AI-enabled augmented engineering.
