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Adaptive Systems: The Next Big Thing in RF?

Adaptive systems have moved from the realm of science fiction novels to real-world applications. Also known as self-adjusting systems, adaptive systems react to changes by adopting new behaviors or functions as needed. With the rise of artificial intelligence and related technologies, such as large language models (LLMs), natural language processing (NLP), and neural networks, it seems the era of adaptive systems is finally upon us.

You can find examples of adaptive systems in expected places like robotics but also in fields as diverse as weather forecasting and aviation. Given that many of these domains rely on radio frequency (RF) communication systems, one has to wonder if adaptive systems are the next big thing in RF. All signs point to the RF industry undergoing rapid change thanks to the power of adaptive systems.

What Is an Adaptive System?

Scientists and academics have been discussing adaptive systems for decades. As a theoretical concept, adaptive systems are the natural evolution of the machines that powered the Industrial Revolution in the late 19th century. Early researchers said that any device — or later, computer algorithm — that could change its behavior based on environmental clues would qualify as an adaptive system.

Over time, the development of artificial intelligence created exciting new possibilities for adaptive systems. As a subset of AI, machine learning is focused on processing data and making real-time decisions, all to perform a task faster and more accurately. It only seems natural that the study of robotics also absorbed the developments in machine learning and adaptive systems. Today, you can find robots in all manufacturing environments, warehouses, and the supply chain. When you receive a package or food delivery from a robot, you see the convergence of adaptive systems, robotics, and machine learning.

Adaptive Systems Today

Even tiny robotic vacuum cleaners found in many of today’s homes show the self-adjusting traits and artificial intelligence of adaptive systems. Once the robot runs into a wall or gets stuck rounding a corner, it learns and adapts to its environment. We now see adaptive systems in much more complex and wide-ranging applications, such as self-driving cars and automated stock trading apps.

As machinery evolved from the time of the Industrial Revolution to today, so did RF and radio communications. The late 19th century was the earliest days of telegraphs and Morse code transmissions; today, we have global cellular and data networks. Still, radio communication systems are typically designed with fixed parameters: each device continuously operates on the same frequencies, always attempting to send and receive signals regardless of environmental factors.

So, what would it look like if adaptive systems could incorporate adaptive systems? Instead of fixed parameters, what would dynamic configuration changes do for radio communications? As it turns out, adaptive systems could revolutionize the entire RF industry.

RF Applications of Adaptive Systems

One of the key concepts in adaptive systems is the feedback loop. Adaptive systems continuously incorporate feedback from their operating environments so as to adjust to changing conditions. RF devices are prone to interference and noise from changing environmental conditions. Typically,  RF filters are employed to reduce interference on specific frequencies.  Imagine radio communications devices that can incorporate a feedback loop and self-adjust for optimal performance.

That would mean WiFi and 5G networks that could reduce interference and optimize signal coverage on the fly. Satellite communication systems could dynamically adjust due to changing weather and other environmental conditions that degrade performance. Military and public safety communications would see drastic improvements in reliability as people in those fields often head into unknown or rapidly changing environments.

Adaptive Systems in Radio Communications Today

While those are some examples that seem sure to come over the next few years, especially as AI and machine learning are rapidly evolving, you can already see RF applications of adaptive systems today.

IoT devices are becoming commonplace in manufacturing environments, transforming traditional production environments into smart facilities. At their core, IoT applications are a sensor and an RF device. When they’re deployed on production equipment or other machinery, they continuously collect data on operating conditions, including fixed data like the time and temperature. They also capture data that requires some analysis to understand, such as how well the machinery is operating.

Using predictive analytics, IoT devices can alert humans when equipment may need repairs. They can even tell the equipment to adjust operations to avoid a complete breakdown before a maintenance window can be scheduled. If deviations from quality standards are detected, IoT systems effectively become adaption control systems. All communication between devices, equipment, and humans occurs wirelessly.

The feedback loop between RF-equipped IoT devices goes beyond the manufacturing floor. Robots can be told to pick up a completed product and take it to a warehouse. Adaptive systems optimize the supply chain using real-time inventory and transportation data. Inventory management systems thus adapt, calculating new reorder points and quantities.

Future RF Developments With Adaptive Systems

Radio communication makes the promise of IoT devices and smart manufacturing a reality. However, AI, machine learning, and adaptive systems will likely be further incorporated into most RF devices in the near future. This includes:

• Dynamic spectrum sharing: This emerging technology allows multiple RF systems to share the same frequencies efficiently. Adaptive systems will help allocate spectrum resources efficiently and effectively.
• Finding unused frequencies: Today, a “smart radio” is just a WiFi-equipped radio. The smart radios of the future will be able to dynamically adapt by finding unused spectrums and frequencies, minimizing the threat of noise and interference.
• Adaptive beamforming: Beamforming is the long-standing RF practice of directing signals toward specific devices or locations. Adaptive systems could adjust beamforming patterns based on the location of mobile users.

Choose an Industry Leader for the Latest RF Developments

The rapid adoption of AI has brought some highly technical concepts out of labs and college lecture halls and into our everyday lives. Whether you’re interacting with a friendly chatbot or working with financial systems powered by AI algorithms, you likely regularly use adaptive systems in some form. The RF industry is about to undergo a similar change thanks to these innovations.

To stay on top of the changes in the RF space, choose an industry leader for your radio communications needs. TX RX has been at the forefront of the RF industry since 1976, leading the way in technological advancements. Our team of RF engineers brings years of experience and knowledge to all of our products. To learn more or schedule a demo of TX RX products, contact us today.