Study On Energy Saving Strategy And System Optimization Of Base Station In Cognitive Radio Networks With LTE-A Structure

The vigorous development of intelligent communication equipment makes the spectrum-scarcity crisis more worse.Traditional fixed-spectrum allocation strategy has been unable to meet the market demand.Cognitive radio network(CRN)with LTE-A structure using dynamic spectrum allocation technology,that effectively alleviate the spectrum scarcity.We study energy-saving strategy for base station in green cognitive radio network,and analysis the system performance.First,according to the transmission characteristics of the two kinds of users and the base station side,and in order to improve the utilization rate of the spectrum and realize the green communication,we propose an energy saving strategy with non-periodic sleeping mechanism(NPSM-ESS)in CRN with LTE-A structure for the base station.By establishing a type of two-dimensional discrete time Markov queuing model with a single vacation mechanism,we capture the stochastic behavior of the proposed strategy and derive the performance measures in terms of the average latency of secondary user packets and the energy-saving degree of base stations.Secondly,in view of the phenomenon that the secondary user will impatience when the queue is too long,and for the strong real-time business needs,our aim is to improve the response performance of secondary users,we propose an energy saving strategy with non-periodic semi-sleeping mechanism(NPSSM-ESS)in the base station side.Accordingly,we establish a two-dimensional discrete time Markov queuing model with single working vacation mechanism.Using the method of a matrix geometric solution,the system performance of the energy saving strategy is evaluated in terms of energy saving rate,channel utilization,average delay of secondary users and interruption of secondary users.The theoretical analysis results and the simulation results verify the effectiveness of the energy saving strategy.Finally,because the steady-state distribution of the system can not be given in a closed-form,a intelligent optimization algorithm is adopted to optimize the two energy saving strategies.From the perspective of economics,we construct profit function of the NPSM-ESS and NPSSM-ESS and investigate the Nash equilibrium and the socially optimal behavior of the secondary user packets,then,we formulate a pricing policy of licensed spectrum for secondary users.In view of different system parameters,the system experiment is carried out to validate the rationality of the pricing policy.