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Cognitive Radio is expected to have the following capabilities:

  1. Sense the environment and collect information of the environment (e.g., spectrum, propagation conditions, network topology)

  2. Be aware of the external situation, the internal state and its own capabilities (e.g., currently used waveforms and settings, waveforms that the radio has)

  3. Automatically adapt its parameters and optimize multiple objectives (e.g., adjust its transmit power)

  4. Reason about communications situations, objectives and radio configurations (e.g., which parameters to change and by how much).

Limitation of Currently Used Technology:

  1. Local information is stored in a data model that does not have high expressivity and machine understandable semantics. For example, in SNMP (Simple Network Management Protocol) or CMIP (Common Management Information Protocol), the information that can be stored and retrieved is limited to scalar variables. It is not possible to exchange complicated information such as the structure of a component or description of a waveform.

  2. XML technology is integrated with the existing protocols to provide a means to express more complex information, however XML does not have computer-processable semantics and thus cannot be processed by the inference engine. Therefore, the radio cannot reason and adapt its behavior without human intervention.

  3. Control signaling is limited by the frame structure defined by the protocol, and therefore hinder  the ability to achieve the vertical and horizontal mobility among the communication networks.

Our CR Group is focusing on the capabilities of awareness and reasoning, especially combined with optimization. Awareness, including situation awareness and self-awareness, is the ability to interpret input information to achieve: the perception of elements in the surrounding environment, the comprehension of their meaning and the projection of their status in the near future (Endsley, 2000). Reasoning refers to the ability to infer implicit knowledge from the explicitly represented knowledge. Reasoning requires (1) a proper language to represent the knowledge and policies, and (2) a reasoning engine that can process the knowledge and policies.

Aligned with the above assessments, the mission of our research group includes:

  1. Development of cognitive radio ontology

  2. Investigation of language design, language expressiveness and computational complexity

  3. Design and implementation of ontology-based radio with policy-based control

Progress and Plans:

  1. In 2003 [1] we proposed the concept of Ontology-Based Radio (OBR). In the OBR approach, all the internal/external information and the signaling messages are represented in the Web Ontology Language (OWL). OWL is a formal language with high expressivity and computer processable semantics and therefore is capable of expressing complicated information and can be processed by the inference engine.

  2. We actively participate in the work of the Wireless Innovation Forum, Modeling Language for Mobility (MLM) Working Group, where we are leading an effort to develop a formal language, with computer understandable semantics, that could be used to describe all aspects of network operations and management. Some of the related papers are: [2,3,4,5].

  3. Papers [6] and [7] discuss the language issues that arose in the process of developing the ontology and policies for cognitive radio.

  4. In [8], we use a public safety use case to demonstrate how to combine ontology, policy and inference engine to control the radio behavior.

  5. We are also active in the IEEE P1900.5 working group in an effort to define requirements for a policy language for Dynamic Spectrum Access (DSA).

A really smart radio that would be self, RF- and User-aware, and that would include language technology and machine vision along with a lot of high-fidelity knowledge of the radio environment.

J. Mitola (2000)


Cognitive Radio