Cross-Layer Analysis in Cognitive Radio—Context Identification and Decision Making Aspects

This is the authors' abstract. We don't add key points for this paper.

Research on context-aware communications has recently led to the introduction of features and algorithms relying on the presence of rich, accurate context information, and requiring however, the introduction of cross-layer information exchanges. Cognitive radio (CR), in particular, is expected to benefit from context awareness, as the cognitive engine (CE) relies on the availability of multiple information sources to operate efficiently. In this context, this work delivers a detailed, yet concise classification and description of the information exchanged in a CR network between the layers of a generic protocol stack, and between each layer and the CE. For each layer, the key services provided and delivered are presented, followed by a catalogue of exchanged parameters. The analysis, supported by a set of use cases providing a quantitative assessment of the impact of crosslayer information exchanges in a CR framework, is the basis for the discussion of key implementation challenges and the identification of the most promising partition of functions and tasks between layers and CE.