The promise of 5G has always been to bring the advantages of mobile technology to industries that stand to benefit from it. Just as consumers have realized the upsides of ubiquitous connectivity through smartphones, that kind of transformative power can be applied to businesses using a network of devices and machines.
Enterprise capabilities that 5G can offer include the ability to extend digital transformation to the network edge, where key performance indicators are tracked and value is delivered. Data captured at the network edge can also boost digital intelligence through machine learning and artificial intelligence (AI) inferencing.
When implementing this new intelligent network edge, an emerging class of 5G devices called NR-Light is set to help businesses looking for new, highly scalable and customizable mobile connectivity. In this article, we’ll discuss the foundational role 5G NR-Light could play in the development of a new mobile network where edge devices are tailored to wide-ranging industrial applications.
Benefits of 5G NR-Light
In a previous blog, we discussed NR-Light allowing the “right-sizing” of 5G air interface capabilities to fit the needs of a specific application. Current narrowband radio technologies used for 5G in the Internet of things (IoT) have a design bias toward longer battery operations and come with stringent limitations on data bandwidth. In addition, the full broadband capabilities of 5G on our smartphones provide more bandwidth than what’s needed for machine-to-machine communications, and at a higher cost than the business case can justify. This means we need a middle ground where engineers can balance mobile connectivity with complexity, cost and battery life to optimize designs for specific applications. This is the sweet spot of 5G connectivity that NR-Light has been created to fill.
By creating a new standard for machine-type communications, NR-Light offers the opportunity for 5G to cover novel IoT markets and industrial applications — particularly when paired with artificial intelligence (AI). The effects of interconnected devices and machines represent an untapped potential that wireless networks have yet to realize. This all means that NR-Light stands to become a very promising radio technology for 5G networks as it matures and expands beyond smartphones.
Network edge applications are varied and have differing connectivity requirements. For example, a motion sensor in a large security system needs very little bandwidth, which can be addressed with existing narrowband IoT connectivity at slow speeds. But devices like surveillance cameras have entirely different bandwidth requirements when deployed over 5G, potentially demanding speeds of tens of megabits per second. And ultimately, a cellular-connected 5G video camera can only be viable when the cost of both the device and connectivity becomes economically feasible.
The radio specifications of NR-Light provide a highly scalable data throughput when compared with existing high-throughput LTE Category 4 solutions. Improvements to air interface, including higher order modulation and multiple radio paths, allow the new standard to deliver higher data rates, lower network latency, long battery life and cost-effectiveness. In short, NR-Light brings with it a more flexible set of design rules to meet a range of IoT needs.
Enabling AI at the Network Edge
Staying with the 5G surveillance camera example, let’s take a look at another use for NR-Light coupled with the trend of AI migration to the network edge. NR-Light brings 5G capabilities that make it possible to embed AI capabilities on edge devices like our surveillance camera. Using machine learning data sets and inferencing, the AI-connected camera can perform localized surveillance services as opposed to simply sending video to the network, freeing up network resources and data costs. AI running on the camera can be tuned to detect activity, and once triggered it can send recorded images to the network.
This example of AI at the edge comes with several benefits. Firstly, it dramatically reduces the camera’s connectivity requirements because data is only transmitted when an event occurs. Secondly, the AI alleviates the need to run constant surveillance on the cloud, allowing for more efficient use of the centralized computing resource. Thirdly, the power savings realized by not switching on radio help lengthen the camera’s battery life. All combined, the cost savings generated by localized AI capabilities produce a convincing argument for investing in AI at the edge.
NR-Light Road Map
NR-Light specifications were added to 3GPP Release 17 from March 2022, and the tech’s expected to appear on modems and radios starting in 2023. Once these chipsets and radio designs are made available to the larger manufacturing space, new NR-Light edge devices will probably hit the market from 2024. Enterprises worldwide are also investing to digitally transform their business practices, and a central tenet of that is establishing an intelligent connected edge. These two trajectories are expected to intersect as 5G NR-Light devices imbue mobility and extend the reach and efficacy of these enterprise networks.
There are still barriers to NR-Light gaining traction at this middle stage of 5G. The necessary network of chipsets and devices has yet to be built, although many chipset suppliers are actively preparing for the tech’s roll-out. And enterprise investment in digital transformation will need to remain robust to bolster demand for NR-Light devices and services — something that remains a question mark in difficult macroeconomic conditions. NR-Light will have to overcome the pitfalls of the much-hyped IoT promises made in the 4G days and demonstrate real market value.
The promise of 5G rests in its potential, and in a future where industries take advantage of mobile systems created to advance business outcomes. NR-Light represents a vital technology that helps right-size 5G connectivity for intelligent edge applications, clearing the way for innovative devices and services that take advantage of the network. Fundamentally, it’s the underlying technology in establishing the connected edge and imbuing it with intelligence.
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