Capacity Research Of Cognitive Radio Based On Spectrum Sharing System

With the continuous growth of the application areas of wireless communications,existing fixed spectrum allocation policy becomes more and more incapable of handlingthe challenge to meet the increasing demands of wireless communications services.Cognitive radio, as a promising approach to solve the scarcity of wireless spectrumresources, has attracted many researchers’ attentions in the world. In cognitive radio,power control and system capacity evaluation are among the key problems in theresearch field, whose findings are of significance in the directions of networking andconfiguration in cognitive radio systems. Based on the cognitive radio spectrum sharingsystem model, this dissertation studied the achievable channel capacity domains andoptimal power allocation schemes in different cognitive radio spectrum sharing systemswith relay communications, multi-user diversity and opportunistic communications,respectively. The contributions of this dissertation were mainly carried out in thefollowing aspects:First, in cognitive radio spectrum sharing networks, the channels of secondaryusers may experience severe channel fading, which prevents direct communication linksbetween secondary transmitters and receivers. To solve this issue, a method wasproposed to deploy multiple relays between the secondary transmitters and its receivers,and choose the best one to forward the information for secondary transmitters byadopting the multi-hop decode-forward schemes. Under the constraint of peakinterference power, closed-form expressions of both ergodic and outage capacities werederived over Rayleigh fading channels for the proposed spectrum sharing system withmultiple relays. Numerical simulation results were provided to show that the achievablechannel capacities can be improved with increasing the number of relays.Second, we considered a sharing spectrum network with multi-user diversity,which consisted of multiple secondary transmitters and one secondary base station asthe secondary receiver. The effective channel capacity of the up-link cognitivetransmission was evaluated over independent identical Rayleigh fading channels. Ourfindings showed that the maximum effective channel capacity can be improved as the number of secondary transmitters increased, which implied the existence of thecognitive multi-user diversity gain. Besides, a new spectrum sharing scheme withmulti-user diversity was proposed based on the diversity selection of multiple antennas.The cumulative distribution function and probability density function were derived forthe signal-to-noise ratio at the secondary receiver, and the relation between the channelergodic capacity and the number of secondary users was analyzed for the secondarysystem. For the case of not limiting the transmit power of secondary users, theclosed-form expression of the ergodic capacity was derived. Compared with traditionalmulti-user spectrum sharing methods, the proposed scheme further improved thechannel ergodic capacity due to the diversity selection of multiple antennas at thesecondary receiver.Third, we considered a cognitive radio sharing spectrum network with a secondarybase station as the secondary transmitter, and multiple secondary users as the secondaryreceivers. The channel between secondary base station and primary receiver is modeledas Nakagami-m fading, and the channels between the secondary base station andsecondary receivers experience independent identical Rayleigh fading. In each time slot,an opportunistic scheduling scheme is adopted that the secondary transmitter only sendsto the secondary receiver with the most favorable channel quality. The ergodic andoutage capacity were inverstigated for the down-link cognitive transmission withopportunistic scheduling over the asymmetric fading channels. Also, a closed-formexpression of the ergodic capacity was derived. It was shown that the maximum ergodiccapacity can be promoted as the number of secondary receivers increased, and theNakagami fading channel parameter became smallerFinally, we studied the power allocation and the corresponding effective channelcapacity maximization problems under the constraint of non-ideal channel stateinformation. Compared to the case of ideal channel state information, the analytical andnumerical results were presented to show that there was a decline in the maximumeffective capacity with non-ideal channels state information, which was more adhere topractical in cognitive radio networks. We showed that, given the same condition, bettereffective channel capacity was achievable under the constraint of average interferencepower imposed on the secondary users than that under the constraint of peakinterference power.