Research On The Spectrum Resource Allocation And Sharing In Cognitive Radio Systems

With the development of wireless communication technology, the demand for wirelessspectrum has been growing tremendously, and leads to increasing scarcity in wirelessspectrum resource. Although the advanced wireless communication techniques are applied,such as the link adaptation and multi-antenna technology, which can improve the spectrumefficiency to some extent, the increasing demand of wireless spectrum resource requirementsstill can’t be satisfied. However, according to the research results, the spectrum resource in theexisting static spectrum sharing is not fully utilized. The cognitive radio technology hasattracted tremendous attention, and becomes an effective technique to alleviate thecontradiction between the scarcity and low efficiency of the existing static spectrum sharingscheme.This paper focuses on spectrum allocation and sharing of the cognitive radio networks, itmainly includes:Firstly, the spectrum sharing problem of the cognitive radio communication system isanalyzed. The list coloring algorithm is applied to discuss the spectrum allocation problem inthe overlay cognitive radio networks. In order to avoid the recalculation of the spectrumallocation with the mobility of the cognitive users, an improved list coloring based spectrumallocation algorithm is proposed. On the basis of previous spectrum allocation, it reduces theimpact of secondary users’ mobility to the spectrum allocation by releasing correspondingconflicted channels and searching for available channels. In addition, the spectrum allocationbased on intelligent algorithm is further analyzed, and the constraint templates based geneticspectrum assignment model for cognitive radio networks is proposed. The noninterferenceconstraint templates are calculated aiming at maximizing the system utility, and thechromosome in the proposed algorithm is composed of the indexes of the constraint templates.Thus the combination of the constraint templates with high fitness is obtained through theevolution of genetic operators, and the corresponding feasible spectrum assignment strategywithout interference can be achieved. The performance of the spectrum assignmentalgorithms for cognitive radio networks are compared and evaluated by simulation results.Secondly, the power distribution in the cognitive radio networks based on underlay spectrum sharing model is analyzed, and a step power distribution algorithm based on gametheory is proposed. The power distribution of the cognitive radio networks can be divided into the calculation of target signal to noise ratio and the calculation of power distribution. Itcan achieve the similar throughput performance with lower consumed power levels.Meanwhile, in order to control the impact of secondary transmission on the communicationquality of licensed users, the spectrum sharing model based on the feedback controlinformation is analyzed, and an improve power distribution algorithm based on feedbackcontrol information from the primary user is proposed. It combines the optimization theoryand feedback control information, and can obtain the power distribution strategies with lessiteration than the conventional algorithm. It can also get better outage probabilityperformance of the primary users.Thirdly, the spectrum sharing problem based on spectrum leasing mechanism incognitive radio networks is analyzed, the spectrum sharing models based on competitive pricegame and auction mechanism are discussed. The spectrum sharing problem with restrictedspectrum resource from the primary users is further analyzed, the optimization model basedon Lagrange multiplier is established, and a fast iteration algorithm to obtain shared spectrumprice of the primary users based on gradient iteration algorithm is proposed. It can avoid thepredefinition of adjustment factor according to the communication parameters in theconventional linear iterative algorithm, and obtain the shared spectrum price that satisfies theconstraints quickly. Besides, an improved spectrum leasing algorithm with the considerationof user requirements is proposed. It combines the competitive price game and the auctionmechanism, and can be applied in the spectrum sharing of multiple primary users andmultiple secondary users.Finally, the spectrum access in cognitive radio networks with the consideration ofspectrum sensing revenue and the spectrum sensing overhead is analyzed. A spectrum accessalgorithm based on the spare probability of licensed spectrum bands is proposed. Based on thespare probability of different spectrum bands, with the adequate selection of collaborativecognitive users in spectrum sensing, the licensed spectrum bands with higher spareprobability is sensed with priority, and the transmission performance of the secondary users isalso taken into account. The improved spectrum access algorithm can reduce the spectrumsensing overhead and achieve better spectrum sensing revenue, and it can improve the spectrum access opportunity in cognitive radio networks efficiently.