Fuzzy Logic Based Decision System for Context Aware Cognitive Waveform Generation

Abstract

Cognitive radio is an intelligent radio which will run the cognitive cycle of observing, understand, create knowledge, make a decision and modifies the radio parameters for the given objective. Cognitive radio designed with single purpose may not be suitable for the next generation of heterogeneous network, where there are multiple QoS requirements on application/user side, experiences a different kind of channel condition and must support different frequency band of transmission. So, there is a need for cognitive radio that will meet the multi-scenario requirements or context aware cognitive radio communication system for the heterogeneous network. This work presents five transmission mode cognitive waveforms for handle five different contexts. The five transmission waveforms are (1) Energy efficient QoS CR waveform using Genetic algorithm. (2) Low data rate FBMC based subcarrier level interleave CR waveform. (3) Emergency communication support underlay spatial coder waveform. (4) Hardware impairment handling waveform using prewhitened precoding. (5) Imperfect channel state handling adaptive training sequence design based interleave CR waveform. Optimal decision making based on observed values and receiver feedback relies on the accuracy level of observed values which is not a precise one. The fuzzy logic is tolerant of such impreciseness of data. So a cognitive engine deigns with fuzzy based decision system to select optimal waveform for the given context is presented. The system is designed to take input from spectrum hole from detecting unit and database, inputs from receiver feedback like BER, data rate, channel gain, channel imperfection, SINR from PR receiver, input from the transmitter about hardware impairment and finally input from user application about the QoS requirement.