Human intelligence is rooted in sensing the environment, learning from the environment and processing the information from the environment. AI system which includes simulation of human senses (sight, hearing, smell, taste, and touch), simulation of learning and processing (deep learning, machine learning algorithms) and simulations of human responses (through robotics), is uniquely termed as Cognitive Technology.

Before we embark on development of Cognitive Technology, we must take into account peculiar traits of human beings for emulation by machine i.e.

• Humans are Active and Embodied agents.
• Humans are social being, at the same time are individuals.
• Humans are life-long learners and keen observers and behave like a dynamic system.

A Cognitive Technology has to keep such traits in design consideration to enable a machine to have a behavior as human.

Figure 1 shows design of a general-purpose Cognitive system which can provide more accurate results (based on predictive and prescriptive analytics, not bounded by pre-trained architecture) by taking into consideration conflicting and changing information that fits contextually into the situation.

Figure 1: Generic Cognitive System

Cognitive Computing is built on Artificial Intelligence and includes the individual technologies that perform specific tasks that facilitate human intelligence. These are smart decision support systems that simply use better data, better algorithms to come up with a better analysis of vast stores of information.

The Cognitive Engine can be implemented by using a combination of Characteristic principles (eg Ordered version space, hill climbing principle, competitive principle etc.) and Aided principles (e.g., score function etc.). This would automatically discover and learn the required regularities or patterns in images.

Further, the Cognitive engine can be designed to self-diagnose its decisions (Refer figure 2). The incorporated Artificial Intelligence (AI) system would respond well to unforeseen conditions and events, introspect itself (i.e., examine its own decision-making processes) and update its control laws in real time.

Figure 2: Self-diagnostic feature of Cognitive Engine

Cognitive Radio: Infusion of artificial intelligence into space communications networks

In Space communication, various link attributes may be desired, such as optimized data throughput, reduced power consumption, or guaranteeing that critical data is transmitted. But the most essential thing for a deep-space probe is to maintain contact with Earth. Otherwise, the entire mission could be doomed. Thus, the communication system should maintain a communication link by adjusting its radio settings autonomously. Maintaining a high data rate or a robust signal are lower priorities. Also, the communications system must consistently adapt its operations to the surrounding environment.

But there are number of factors that can hamper radio communications between a satellite and a ground station such as:

• Cosmic noise
• Varying characteristics of Earth’s Ionosphere
• Deformation of antenna material due to heating and cooling

A better alternative is to have the radios use neural networks to adjust their settings in real time. Neural networks maintain and optimize a radio’s ability to keep in contact, even under extreme alien space environmental conditions. Rather than waiting for a person on Earth to advise the radio how to change its systems, which may take days or weeks, a radio with a neural network can do it on the run.

A Cognitive Radio is an example of such a device. Its neural network detects changes in its surroundings automatically, adjusts its settings accordingly, and, most importantly, learns from the experience. That means a cognitive radio can experiment with different configurations in different situations, making it more resilient in unfamiliar environments than a standard radio. Thus, cognitive radios are suitable for space communications, particularly beyond Earth orbit, where the surroundings are unknown, human involvement is difficult, and preserving connectivity is critical.

A software-defined radio is a wireless technology that a cognitive radio utilizes to regulate its basic parameters. In a software-defined radio, major functions such as filtering, amplifying, and detecting signals that are performed with hardware in a traditional radio are performed with software. For a cognitive radio, this kind of adaptability is crucial. Adaptive radio software could help scientists and explorers get more data by avoiding the effects of space weather.

Alternate data pathways to the ground could potentially be suggested by a Cognitive Radio network. To avoid interference, these systems might prioritize and route data through numerous pathways at the same time. Artificial intelligence in the cognitive radio might potentially allot ground station downlinks just hours in advance, rather than weeks, allowing for more efficient scheduling.

Additionally, Cognitive Radio has the potential to improve communications network efficiency by reducing the requirement for human involvement. Intelligent radios could adapt to changing electromagnetic landscapes without the need for human intervention and predict typical operational parameters for many contexts, automating traditionally time-consuming tasks.

Engineers and researchers can use the Space Communications and Navigation (SCaN) Testbed aboard the International Space Station to test Cognitive Radio in space. Three software-defined radios, broadcasting in the S-band (2 to 4 gigahertz) and Ka-band (26.5 to 40 GHz) and receiving in the L-band (1 to 2 GHz), as well as a range of antennas and equipment, that can be configured from the ground or from another spacecraft, are housed in the testbed. Experiments with the SCaN test bed have showed that Cognitive Radios have a place in future deep-space communications.

Figure 3: The SCaN Testbed payload aboard the space station. In April 2013, it began conducting experiments after completing its checkout and commissioning operations.    Credits: NASA

As mankind reconsiders its exploration of the moon, Mars, and beyond, ensuring stable connectivity between planets has gained utmost importance, which can be realized through Cognitive Radio technology.

Military+Aerospace Electronics, Image Source: Military Embedded Sytems, NASA