Centralized Channel Allocation Strategy In Cognitive Radio Network And Performance Analysis

With the high-speed development of wireless mobile communication, the limitedchannel becomes scarce resource. Compared with the traditional fixed channel allocationwith great waste, the cognitive radio network makes channel resource be utilized fully byenabling secondary users to utilize temporarily unused licensed channels by primary usersopportunistically. Therefore, new to design a reasonable channel allocation strategybecomes one of the key issues for improving the channel utility. A centralized channelallocation strategy is offered, the performance analysis and parameter optimization of thestrategy are brought out based on the single channel and multiple channels, respectively.Firstly, in order to decrease the system load caused by channel competition andchannel searching, at the same time, to improve the uniformity of channel utility, a novelbased on Hash algorithm and centralized channel allocation (HCCA) strategy is offered.Secondly, in order to reduce the data loss rate of secondary users, and to enhance theresponse performance of primary users ultimately, a limited cache K (K>0) is set for thesecondary users, no cache is set for the primary users. Moreover, secondary users areregarded as class I customers, primary users are regarded as class II customers, andlicensed channels are regarded as servers. At the same time, considering the exclusivelyright of primary users to licensed channels, a discrete time queuing model with two classesof customers is built, where the class II customer has preemptive priority.Thirdly, taking into account the single channel and multiple channels, the data arrivalinterval and service time are assumed to follow the Bernoulli processes. The system modelis analyzed for steady-state with the method of two-dimensional Markov chain, thequeuing measures are derived. The corresponding formulas for the performance measuresin terms of data loss rate, system throughput, average response time of secondary users,channel utility and average searching times are presented, respectively.Finally, combining the theory analysis and the working mechanism of HCCA strategy,numerical experiments and system simulation are performed. The influence of theparameters of the cache capacity of secondary users and the total number of channels onthe system performance is characterized. Taking into account different performance measures, two cost functions are constructed to optimize the cache capacity of secondaryusers and the total number of channels, respectively.