Research On Spectrum Allocation Technology Of Cognitive Emergency Communication System

As a simple, effective and temporary means of communication, the demand and development of emergency communication system has becoming imminent when faced with earthquake, flood, tsunami and other temporary variable natural disasters and emergency tough city emergencies, At present, with the rise and development of the wireless industry, spectrum resources is becoming increasingly tense, which seriously restrict the development of emergency communication. The cognitive radio technology has a strong spectrum sensing capabilities and network reconfiguration ability, the using of cognitive radio technology can improve a better utilization efficiency of emergency communication cyber source and enhancement of intelligence of emergency communication system in various network conditions, which greatly alleviate the problem of serious lack of spectrum resources etc.This paper studies the efficient and rational use of the limited available spectrum in emergency scene, and introduces the application characteristics of cognitive radio emergency communications system. After the objective analysis of the disaster-affected areas and the emergency communication service demand, this paper proposes an emergency communication system scheme based on cognitive radio technology with the characteristics of cognitive radio and emergency communication system. Based on this design, its process of the system is given. Then a concrete analysis of the application scenario and a brief introduction of the application of system are made.In the cognitive emergency communication system, due to the disaster area irresistible environmental interference and rescue squads subsystem internal interference, this paper proposes the concept of spectrum demand classification based on interference temperature model. Then demand spectrum classification is applied to the graph coloring model and the algorithm of graph coloring model based on improved spectrum allocation is proposed. According to the spectrum of the subsystem requirements, this algorithm can meet the business Qo S and the maximum demand spectrum allocation without interference for each subsystem in the cognitive system. The simulation results show that the proposed algorithm can effectively allocated spectrum to adapt to the demand of spectrum of each subsystem ofbusiness needs and provides Qo S guarantee for business. Therefore, the improved graph-coloring-model in spectrum allocation can meet the demand of each subsystem in the cognitive system much better than the original CSGC algorithm.