Verizon and AT&T’s C-band 5G upgrade: From airports to rollouts, the latest on what you need to know

A new swath of radio airwaves could give AT&T and Verizon 5G more speed and reach — so long as the FAA and airlines are satisfied that flights won’t be endangered.

If you’ve been paying attention to the spat pitting carriers AT&T and Verizon against the Federal Aviation Administration over safety issues tied to 5G, you may have heard the term C-band thrown around.

It’s more than just a wonky designation for a swath of radio airwaves. This additional spectrum could significantly change your 5G experience, which for many has been an incremental upgrade — if that — over 4G. C-band is expected to give both AT&T and Verizon 5G customers wider coverage and higher speeds, though it has run into issues from the FAA and aviation industry.

A Samsung Galaxy S21 5G connected to Verizon’s C-band test network in downtown Los Angeles, running a speed test inside an elevator. David Lumb / CNET

Let’s first explain what C-band is. It’s a set of radio airwaves operating at a frequency range between 3.7GHz and 3.98GHz. That frequency falls under what is known as midband spectrum.

While AT&T and Verizon (as well as T-Mobile) have had 5G networks for a couple of years now, the former two have largely been limited to deploying next-generation networks using what’s known as low-band spectrum or high-band millimeter wave.

Low-band has excellent coverage, but its speeds are often equivalent to those of 4G LTE. Most people on AT&T and Verizon are experiencing this kind of 5G, which is why the difference has been minimal for many.

Millimeter-wave has excellent performance, but its coverage is often limited to just a handful of blocks in certain cities or in parts of an arena, stadium or airport. Not everyone is going to show up to Times Square or SoFi Stadium for that kind of enhanced 5G.

With midband spectrum, a carrier can offer 5G that’s not only significantly faster but works in more places.

OK, but how fast are we talking about?

Verizon said that it expects peak download speeds on C-band to be 1 gigabit per second, or 10x faster than 4G LTE. That’s comparable to the fastest home internet service, although note the term “peak” as the best-case scenario for connectivity. The performance improvements are why carriers spent over $80 billion — with the bulk of that bidding coming from Verizon and AT&T — to acquire C-band spectrum when the Federal Communications Commission put it up for auction.

Read more: Our first look at Verizon’s C-band network

It’s also worth noting that while T-Mobile did purchase C-band for use starting at the end of 2023, it isn’t anywhere near as desperate to deploy that now thanks to the large amount of midband spectrum it acquired in its merger with Sprint. T-Mobile’s midband 5G network already reaches 200 million people, with the company previously targeting average download speeds of 400 Mbps.

Verizon and AT&T will use C-band to plug coverage gaps in their 5G networks that fall between millimeter-wave, which provides high speeds in small areas within cities, and low bands, which offer better range but aren’t always faster than 4G LTE.

What’s the difference between C-band and other forms of 5G?

Once C-band service starts going live Verizon and AT&T customers should see broader 5G service with higher speeds that fall between 4G and mmWave 5G. Because the new C-band service will be integrated into existing coverage, however, customers may not even realize they’re connecting to the new frequencies.

For Verizon users, when you’re connected to C-band you should see a “5G UW” or “5G UWB” indicator on your phone. AT&T users will see “5G+” branding.

Both indicators are similar to what each carrier already uses to denote their respective millimeter-wave connections.

Will I need special devices to connect to this?

Before you get excited about these incoming faster speeds, know that only a few phones have the hardware to connect to C-band. These are Apple’s iPhone 12 and iPhone 13 lines; Samsung’s Galaxy S21 line, Z Flip 3 and Z Fold 3; and Google’s Pixel 6 and 6 Pro. Verizon and AT&T have also confirmed that Apple’s 5G iPads (the iPad Pro and iPad Mini) will also work with their respective new services.

Some older phones and devices may get software updates, but exactly which devices and when those updates will roll out isn’t yet clear. New flagship phones sold by Verizon and AT&T in 2022 and beyond are expected to support the new flavor of 5G.

Will I need a special plan?

Depending on your carrier, you might. AT&T is offering C-band, which it’ll call 5G Plus, with most of its unlimited plans. This includes the Unlimited Starter, Extra and Elite offered today as well as a large number of its older unlimited plans from recent years.

Verizon, which will offer C-band under its Ultra Wideband (or UW) branding, will be limiting access just to a handful of its unlimited options. This includes the Do More, Play More or Get More plans sold today as well as the older Above and Beyond unlimited options from a few years ago.

If you don’t have one of these plans, you won’t be able to take advantage of the faster network even if you have a phone that supports it.

When is C-band being turned on?

Both Verizon and AT&T started to activate their C-band services on Jan. 19 after delays around concerns raised by the FAA and the airlines.

What is the issue for the FAA and airlines?

Airlines and aviation officials have argued that the frequencies covered by C-band have the potential to interfere with instruments used in aircraft and contend that deployments of 5G near airports could endanger takeoff and landing operations.

The carriers, the FCC and the FAA have disagreed on whether C-band 5G signals that use the 3.7GHz to 3.98GHz frequency range could interfere with instruments like altimeters that measure in the 4.2GHz to 4.4GHz spectrum. Wireless industry lobbying group CTIA argues that nearly 40 countries — including Australia, China, France, Japan, South Korea and the United Kingdom — already have 5G deployed over C-band with no issues involving aircraft.

After most recently planning to turn on C-band on Jan. 5, Verizon and AT&T conceded to a final two-week delay so that all parties could take necessary precautions, which includes exclusion zones that ban C-band service for a few miles around airports.

After airline executives warned of significant disruptions to flights if C-band launched as planned, on Jan. 18 the carriers each agreed to “voluntarily” defer or limit C-band launches around certain airports. For Verizon, these adjustments will affect 10% of its planned C-band rollout, with the carrier now aiming to cover 90 million people at launch as opposed to its original goal of 100 million.

So no 5G in airports?

Low-band and mmWave 5G service will still continue around airports, and Verizon will bolster its non-C-band coverage in those areas as part of its broader 5G rollout efforts this year. In short, your phone will still be able to work as it is today, you just won’t have the more consistent faster speeds in and around the airports that C-band would’ve delivered.

And T-Mobile?

Verizon and AT&T still lag behind T-Mobile, which announced in November that 80% of T-Mobile customers within its 200 million-person 5G coverage can access its midband 5G service (which it calls Ultra Capacity). T-Mobile’s midband network operates at a different frequency than C-band and isn’t a concern to the FAA or airlines.

In addition to coverage, the carrier competition will also come down to speed. T-Mobile says its midband 5G network targets average download speeds of 400Mbps. By comparison, our first Verizon C-band testing found speeds ranging from 400Mbps up to 1.4 gigabits per second right below the 5G emitter. Distance isn’t the only metric, as we still got over 400Mbps within elevators and nearly 100Mbps in underground parking structures. The test, however, was highly controlled using Verizon phones and a limited area.

Ultimately, C-band will fill a crucial gap in Verizon’s and AT&T’s respective networks, but the Jan. 19 launch day is just the beginning of a broader rollout. We’ll have to see how customers react to this supplemental service, which could fulfill the 5G promise to bring high speeds to consumers beyond major cities — or just be another small step in the slow network evolution after 4G.

First published on Jan. 6, 2022 at 5:00 a.m. PT.

L’Autorité de Régulation des Télécommunications/TIC de Côte d’Ivoire (ARTCI) a réalisé au titre de l’année 2020, une campagne d’audit de la qualité de service (QoS) fournie par les opérateurs de téléphonie mobile sur toute l’étendue du territoire national.

Voir les résultats de l’audit de la QoS

Voir le rapport détaillé de la campagne d’audit de la qualité de service (QoS) des réseaux de téléphonie mobile en Côte d’Ivoire (2020)

Breaking down artificial intelligence into its most common forms can help integrators understand the potential for the technology as well as its limitations.

 

For many integrators, the concept of artificial intelligence is well known, but the ways in which it can be applied to the residential, resimercial, and commercial markets remain relatively misunderstood. So, consider the following overview an attempt to break AI down into its basic parts and what it potentially means to us in real-world applications.

One basic definition of AI is that artificial intelligence is the science of training computer systems to emulate human tasks through learning and automation. The key elements here are that an AI system requires learning, and only once it has been taught can it automate or replicate what it has ingested.

At the core is the capability of a machine to learn how to apply logic and reason to gain an understanding from complex data. It is not stand alone; AI requires initial data that it receives to teach it. It can then apply the algorithms developed by the learning process to patterns and relationships found in other sets of data.

Fundamentally, an AI is a set of algorithms inside a computer that are fed a set of known data to “learn” from and guided on how to interpret this data. It can then take what it has learned and perform tasks, further learning from each data set. This is where the “garbage in and garbage out” factor comes into play.

AI is only as good as the quality of the data it learns from, but quality data is not enough. Think of data as the food that now must be digested. Depending upon the application massive amounts of data can be ingested but now comes the analysis phase, the extraction of key data points, and finally writing the code that can make the output processes automated in some way.

File all of this under the umbrella of still requiring humans to make it all work. Without data and the analytics of what to do with it, AI is just a couple of words that sound impressive. At a very high level, artificial intelligence can be split into two broad types: narrow AI and general AI.

• Narrow AI represents the vast majority of what we encounter. This is what we see all around us with computers containing intelligent systems that have been taught or have learned how to carry out specific tasks without being explicitly programmed how to do so. A good example might be one of the virtual assistants that so many of us rely on. Keep in mind though that unlike humans, these systems can only learn or be taught how to do defined tasks, which is why they are called narrow AI.
• General AI is very different and is the type of adaptable intellect found in humans. It is a flexible form of intelligence capable of learning how to carry out vastly different tasks based on the data from its accumulated experience. This is the sort of AI more commonly seen in sci-fi movies but doesn’t exist today and AI experts are fiercely divided over how soon it will become a reality.

Some say we will see Artificial General Intelligence (AGI) by 2050 and yet other prominent experts opine that it is much farther off than that and perhaps centuries away.

AI Related Terms Integrators Should Know

As noted, AI requires a lot of data and from the analysis learns the patterns or features of the data and applies it. While AI is the umbrella, there are subfields. Here are a few of the ones you most likely will encounter:

Machine Learning

Machine Learning is the technique that gives computers the potential to learn without being programmed and it is actively being used in daily life. Fundamentally, it is the science that enables machines to translate, execute and investigate data for solving real-world problems.

Neural Network

In simple terms, a neural network is a set of algorithms that are used to find the elemental relationships across the bunches of data via the process that imitates the human brain operating process. The bigger the neural network the close we get to the way we think as human beings. •

Expert Systems

This is a program that is designed to solve problems with requires human expertise and experience. A good example is medicine. A collection of data fed into expert systems can offer knowledge of similar cases or it can be used as a reference or a self-check tool.

Natural Language Processing

NLP is the part of computer science and AI that can help in communicating between computer and human by natural language. It is a technique of computational processing of human languages.

It enables a computer to read and understand data by mimicking human natural language. Of course, there are technologies that enable AI.

We live in the era of the internet of things (IoT) where appliances of all types are connected thus producing huge amounts of raw data.

Graphic processing units (GPUs) inside a computer can provide more than just the ability to render graphics, they have immense computer horsepower to help process data. Advanced algorithms are being developed in new ways to analyze the data.

APIs or application programming interfaces as one AI expert notes “are portable packages of code that make it possible to add AI functionality to existing products and software packages.

“They can add image recognition capabilities to home security systems and Q&A capabilities that describe data, create captions and headlines, or call out interesting patterns and insights in data.” Is AI a trend? Of course it is, but it is already ubiquitous today.

Click online in a search engine and it is used to recommend what you should buy next. It is used to understand what you say to virtual assistants, such as Amazon’s Alexa and Apple’s Siri, and even to spot spam, or detect credit card fraud. The list goes on and on.

Understanding the Limitations Of AI

As wonderful as AI is (opinions vary on this) and understanding that it is going to change every industry, we must understand its limits.

The principal limitation of AI is that it does require data to learn. It does not think on its own. As noted before this means any inaccuracies in the data will be reflected in the results. And any additional layers of prediction or analysis have to be added separately.

Today’s AI systems are narrow AI and trained to do a clearly defined task. One experts points out that “the system that plays poker cannot play solitaire or chess. The system that detects fraud cannot drive a car or give you legal advice. In fact, an AI system that detects health care fraud cannot accurately detect tax fraud or warranty claims fraud.”

 

AI will only get bigger and become of increasing importance in our personal and business lives.

In other words, these systems are very (I do mean very) specialized. They are focused on a single task and are far from behaving like humans. Likewise, self-learning systems are not autonomous systems.

The imagined AI technologies that you see in movies and TV are still science fiction. What is not science fiction are the advances in data collection, algorithms and analytics, and computers that can probe complex data to learn and perfect specific tasks. These are becoming quite common.

All the major cloud platforms – Amazon Web Services, Microsoft Azure and Google Cloud – provide access to GPU arrays for training and running machine-learning models. All the necessary associated infrastructure and services are available from the big three, the cloud-based data stores, capable of holding the vast amount of data needed to train machine-learning models, services to transform data to prepare it for analysis, visualization tools to display the results clearly, and software that simplifies the building of models.

AI will only get bigger and become of increasing importance in our personal and business lives. Machine-learning systems have helped computers recognize what people are saying with an accuracy of almost 95%.

In recent years, the accuracy of facial-recognition systems has leapt forward, to the point where it can match faces with 99% accuracy. In healthcare AI has helped in responding to the pandemic by aiding researchers in spotting genetic sequences related to diseases and identifying molecules that could lead to more effective drugs.

The point for us in AV is to think about how AI can benefit our clients. We won’t provide the AI per se, but we will provide many of the technologies that use AI to their best advantages.

As in all things AV it is our job to know, suggest, and assist our clients meet their objectives. Count on the fact that AI will be part of that.

https://www.cepro.com/business-support/understanding-artificial-intelligence-benefit-av-integration/