Abstract: The emerging Cognitive Radio is combo of both the
technologies i.e. Radio dynamics and software technology. It involve
wireless system with efficient coding, designing, and making them
artificial intelligent to take the decision according to the surrounding
environment and adopt themselves accordingly, so as to deliver the
best QoS. This is the breakthrough from fixed hardware and fixed
utilization of the spectrum. This software-defined approach of
research is centralized at user-definition and application driven
model, various software method are used for the optimization of the
wireless communication. This paper focused on the Spectrum
allocation technique using genetic algorithm GA to evolve radio,
represented by chromosomes. The chromosomes gene represents the
adjustable parameters in given radio and by using GA, evolving over
the generations, the optimized set of parameters are evolved, as per
the requirement of user and availability of the spectrum, in our
prototype the gene consist of 6 different parameters, and the best set
of parameters are evolved according to the application need and
availability of the spectrum holes and thus maintaining best QoS for
user, simultaneously maintaining licensed user rights. The analyzing
tool Matlab is used for the performance of the prototype.
Abstract: Spectrum is a scarce commodity, and considering the spectrum scarcity faced by the wireless-based service providers led to high congestion levels. Technical inefficiencies from pooled, since all networks share a common pool of channels, exhausting the available channels will force networks to block the services. Researchers found that cognitive radio (CR) technology may resolve the spectrum scarcity. A CR is a self-configuring entity in a wireless networking that senses its environment, tracks changes, and frequently exchanges information with their networks. However, CRN facing challenges and condition become worst while tracks changes i.e. reallocation of another under-utilized channels while primary network user arrives. In this paper, channels or resource reallocation technique based on DNA-inspired computing algorithm for CRN has been proposed.