How do 5G and AI accelerate each other?

Together, 5G and artificial intelligence (AI) technologies have the power to improve an organization's digital agility and network speed. However, we must wait for the next generation of wireless connection technology to become further developed to benefit from these advantages.

5G and artificial intelligence can benefit institutions the most by enhancing each other's capabilities. While 5G speeds up wireless networks and makes them more responsive, artificial intelligence has the potential to assist in managing workloads and boosting device efficiency. But before the combination of 5G and artificial intelligence truly pays off, we'll need to wait for the new wireless technology to finish its years-long development process and start to mature.

From 4G to 5G

Allied Market Research predicts that the global 5G market value will increase to $797.8 billion by 2030.

Greater data volumes and quicker data collection made possible by 5G allow AI to produce models and forecasts that are more precise. The development of a fully connected and intelligent world will accelerate with the help of 5G and AI.

Although the promised speeds of 5G look like an amazing improvement over 4G, applications will develop to use the new opportunities. As usual with these matters, problems show up as you dig deeper. In reality, there are two separate 5G networks. 

mmWave, also known as 5G II, works at 100 MHz, delivers between 24 and 100 GHz (gigahertz), and offers incredibly low latency. However, its range is only 300 meters. In comparison, Sub-6 GHz, or 5G I, works at 50 MHz, has a range of 1.5 kilometers, provides between 3.5 and 7 GHz, but has lower latency than 5G II and is better than 4G. In other words, 5G II can handle more robust applications, but the limited range necessitates greater infrastructure investment. As a result, 5G I has seen the majority of 5G rollout thus far.

The role of artificial intelligence in 5G networks

Adopting 5G networks entails some challenges, and the industry is tackling those challenges by incorporating artificial intelligence into networks. Over 50% of the decision-makers surveyed by Ericsson from 132 global telecom operators are expected to integrate AI into their 5G networks by the end of 2020. Reducing capital costs, improving network performance, and creating new revenue streams are the main goals of AI integration. According to 55% of decision-makers, AI is already being utilized by enhancing network quality and providing personalized services to improve customer service and enhance the customer experience. According to 70% of respondents, AI in network planning is the greatest way to recuperate the costs associated with converting networks to 5G.

According to 64% of study participants, network performance management will be the primary emphasis of their AI initiatives. Managing SLAs, product life cycles, networks, and revenue are other areas where cellular decision-makers plan to concentrate AI expenditures. Of course, integrating AI into 5G networks is not without its difficulties. Creating efficient systems for gathering, organizing, and evaluating the massive amounts of data that AI generates is necessary. For this reason, once 5G networks connect, early AI adopters who can overcome these obstacles will unquestionably become leaders.

Why is 5G important for AI?

Despite their shrinking size, the fundamental algorithms that power our mobile devices have not changed since the 1990s. As a result, 5G systems use far more power than ideal and deliver lower data rates than anticipated. Deep learning AI will significantly reduce battery consumption and boost performance by replacing conventional wireless methods. This strategy will be more important overall than concentrating AI mainly on network management and scheduling.

Current cellular networks run on the radio spectrum, which uses bandwidth. Radio waves are electromagnetic waves with frequencies inside the radio spectrum. Along with several other contemporary technologies, radio waves are frequently utilized in communications. National laws strictly regulate interference between users of various radio frequencies, and the International Telecommunication Union (ITU) coordinates these rules. There is a worry that the number of wireless devices being used may cause the airwaves our devices utilize to communicate to become congested. Creating communication tools that don't always broadcast on the same frequency is one solution that has been suggested for this problem. Then, AI algorithms would be utilized to discover available frequencies by enabling intelligent awareness of RF activity that was not possible in the past.

Even though it can be up to 20 times faster than 4G, 5G delivers more than just better connection speeds. Due to its low latency, 5G speeds will enable programmers to use quicker response times by developing applications that include near real-time video transmission for security or sporting events. Additionally, increased access to real-time data from multiple solutions will be possible thanks to 5G connectivity. Internet of Things (IoT) sensors is used by 5G since they are long-lasting and use a lot less electricity to operate. This would make it possible to remotely detect changes in factory equipment conditions and irrigation levels. Patient data might be more simply and securely accessed by doctors. For each of these opportunities to be useful, AI will be used.

Why is AI important for 5G?

AI is necessary for a 5G network to be completely functional and effective. Using 5G networks will enable the integration of machine learning and AI at the network edge. The simultaneous connections to numerous IoT devices made possible by 5G produce enormous volumes of data that need to be handled using ML and AI.

4G networks currently in use rely on inefficient IP broadband access for transmission. To function, 5G networks must be proactive and predictive, which is only possible with ML and AI. Intelligent base stations will be able to decide for themselves thanks to the integration of ML into 5G technology, and mobile devices will be able to build dynamically flexible clusters based on learned data.

A case for edge computing

The idea behind edge computing is to process and analyze data on servers closer to the applications they support. Many have stated that introducing "connected" devices, such as coffee cups and pill dispensers, did not cause the market to soar as projected. However, it is becoming increasingly popular and providing new opportunities for telecom providers and other businesses. However, by fusing big data, IoT, and AI, recent technological advancements have started to transform sectors and the amount of value that all these connections can offer consumers.

This transformation is accelerated by 5G since AI processing is easily supported by the 5G network design. Artificial intelligence's future will shift due to the 5G network architecture. While AI will enable computers and systems to operate at levels of intelligence comparable to humans, 5G will improve the speed and integration of other technologies. Essentially, 5G accelerates cloud services while AI processes and learns from the same data more quickly.