Sarah Yost, Senior Solutions Marketer, Advanced Wireless Research, National Instruments
In today’s world, concepts that were once considered science fiction have begun to make their way into mainstream society as a result of engineering efforts and technology. While new technologies such as 5G are powering innovative solutions today, the core of “science fiction” technology still remains artificial intelligence (AI). While personal robots are still firmly in the future, 5G and AI are helping speed up the pace. Not only do they enable each other, but their fates are somewhat intertwined.
However, it must be noted that while 5G technology has consistently evolved over time, the basic algorithms used by machine learning to create AI have relatively unchanged for the last 30 years. This concept, called backpropagation, is fairly simple. Data sets and the expected outcomes associated with them are input into a processor, and it outputs a pattern. The more datasets and outputs that are used as inputs in the processor, the more accurate the resulting pattern will be. Machine learning thrives on massive amounts of data, a requirement that 5G is all set to meet in the coming future.
Reducing latency within 5G networks
One of the defining characteristics of 5G as opposed to previous standards is its built-in specifications for latency, the target for which is to reach 1 millisecond. The latency requirements differ based on the application used. While augmented reality requires very deterministic and low latency, phone calls and video streaming provide more leeway in terms of latency. Proper priority of network trafficking is a key element in the process of providing truly low latency and high reliability communications. The idea of network slicing, using a single shared physical network with multiple fully virtualised networks running on top of it, is a popular solution to this. This would allow a factory, for example, to pay for a slice with a guaranteed latency and reliability to connect smart machines and factory equipment. They could then have a separate slice for employee communications like cell phones and tablets. Or a 5G-connected car could have a slice for autonomous driving and other mission-critical functions and a separate slice for infotainment.
Tests have already begun in India to implement this solution, with Airtel and Huawei coming together in February 2018 to conduct the country’s first 5G network trial. Nokia and Ericsson have also expressed interest in conducting 5G field trials in India, thereby supporting the government’s plan to deploy 5G technology commercially by 2020.
The provision of this service, however, entails certain challenges, primarily in terms of the current need for the manual configuration of each slice. The impetus provided by 5G networks will concurrently increase the amount of configuration needed for slices. AI has shown, however, that it is perfectly suited for this task.
5G and AI: The advantage
Along with telecom advantages, AI has the potential to collaborate with 5G in other sectors too. Currently, voice-activated assistants like Siri, Alexa and Google Assistant already use AI to process our requests and return their best guess at an answer. Similar to the other cases mentioned, by having access to more data and having that access at significantly faster speeds than are available with today’s LTE networks, devices will have a better ability to understand their surroundings.
As the world becomes more connected, more data will become available on human patterns. AI can combine with IoT to take advantage of this data in many ways. For example, wearable smart monitors can help track patients’ medical status by collecting statistics that can be geotagged, time-stamped, and sent to the cloud to be aggregated and processed. On a simpler scale, AI and health-related IoT devices could be used to monitor patients and make recommendations for the treatment of disease much earlier than if a patient waits for symptoms to become overwhelming before visiting a doctor. A recent partnership between Microsoft and Apollo Hospitals to use AI to predict patient risk of heart disease and to assist doctors on treatment plans represents one example of the work being done to further research in this domain in India.
While the use of AI in other sectors may still be in the pipeline, its integration into the telecom sector is guaranteed to take place. Recent concerns, however, have been raised relating to the issue of data privacy in the post-GDPR world. There is a certain amount of distrust in society of corporations collecting personal data. The recent Srikrishna Committee report in India seeks to address these concerns and has even created a draft Data Protection Bill that is currently pending approval in Parliament. Finding ways to better secure personal data or new business models that allow it to be collected without exploitation are also important challenges that must be solved to make 5G successful.
