空闲认知用户在认知无线电频谱检测中的应用
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摘要
随着通信技术的高速发展，频谱逐渐成为一种稀缺的资源。频谱利用率低的问题严重制约着无线通信的应用。认知无线电技术通过动态地利用空闲频谱资源进行传输，大幅提升频谱利用率，是未来无线通信系统中的关键技术之一。检测技术作为获取空闲频谱信息的手段，在认知无线电技术中起着重要的作用。在某一时刻，空闲频谱资源是由主要用户处于空闲状态形成的，与之相似，将处于空闲状态的认知用户用于检测可以提升检测的性能和效果。本文在考虑将空闲认知用户用于检测的情况下，重点从协作检测、联合检测以及对空闲认知用户的分配机制等方面研究了认知无线电网络检测优化问题。具体研究成果如下：
1.在overlay传输模式下提出了一种利用空闲认知用户的检测模型，通过分析得出认知网络的检测性能。由于利用空闲认知用户需要额外的消耗，同时考虑认知网络的吞吐量和使用效率，提出空闲认知用户在协作检测中的额外检测时长的优化问题。在公平性原则的要求下，允许空闲认知用户选择是否进行协作，提出了一种兼顾吞吐量和效率的优化算法。理论与仿真证明了加入空闲认知用户进行协作检测可以提升检测的性能。
2.针对主要用户网络存在网间干扰时，underlay传输模型下认知网络吞吐量较低的问题，提出了一种利用导频检测在underlay传输模式下切换发射功率以提升认知网络吞吐量的检测时长优化算法。首先考虑主要用户接收信干噪比满足的溢出概率，将对认知用户发射功率的优化问题转化成一个”检测-传输”的权衡问题。然后对权衡问题进行分析，得出使得吞吐量最大的检测时长优化算法。仿真结果表明，采用最优检测时长算法可以获得最大的认知网络吞吐量。
3.由于认知网络中主要用户状态的不确定性，随机检测策略虽然易于实现，但无法保证认知用户准确地寻找到可用信道。本文提出一种利用认知无线网络中空闲认知用户进行联合随机检测的策略。首先加入空闲认知用户进行检测，然后利用马尔科夫模型对认知基站获得的可用信道数进行描述，推导出此时认知网络的检测性能。理论分析和仿真结果表明，利用空闲认知用户可以减小服务时延，并且提高认知网络的吞吐量。在考虑认知用户汇报检测信息所占用的时长后，通过优化算法，可以得出最优的参与联合检测的空闲认知用户数。
4.在认知无线网络中，针对分配式联合检测中的最优检测顺序问题，本文提出了一种利用空闲认知用户的检测策略以最大化认知网络的吞吐量。首先使用连续时间马尔科夫模型对主要用户的活动状况进行建模，然后考虑检测性能对认知网络吞吐量的影响，得出此时认知网络吞吐量的表达式。并以此为目标函数，提出最大化认知网络吞吐量的检测顺序优化算法。由于上下行链路的差异性，在下行链路提出一种最优的检测策略；在上行链路提出一种次优的但是复杂度较低的检测策略。仿真证明了提出的检测顺序优化算法与随机检测相比拥有更好的吞吐量，并能获得更高的频谱利用率，同时降低了认知用户的等待时延。在考虑空闲认知用户的汇报时长后，得出最大化认知网络吞吐量的参与检测的空闲认知用户数。
5.每一个活跃认知用户都希望尽可能多的获得信道状态信息。为了解决认知网络中空闲认知用户的所属权问题，本文提出一种利用拍卖算法对空闲认知用户进行分配的方案。研究了在第二价格的拍卖场景下，认知用户在传输量拍卖和满意度拍卖两种模式下所能获得的收益。同时提出了一种存在预留价格、预算受限以及公平性限制等条件下的拍卖算法。仿真结果表明，同其他算法相比，基于拍卖的空闲认知用户分配算法可以使认知网络获得较好的性能。
With the rapid development of communication technology, spectrum becomes avery scarce resource. The application of the wireless communication is restricted byspectrum utilization. Cognitive radio is widely regarded as one of the key technolo-gies, which can improve the spectrum utilization by using the available spectrum moreefficiently through opportunistic spectrum usage. Spectrum sensing plays an impor-tant role in cognitive radio networks. Available spectrum resources will appear whenthe channels allocated to primary users are idle. Similarly, the sensing performanceis improved by utilizing the inactive secondary users. This dissertation deals with thesensing policies in cognitive radio networks, such as cooperative sensing, joint sens-ing and the allocation of the inactive secondary users. The main achievements of thisdissertation are listed as follows:
1. A sensing model is proposed by using the inactive secondary users in theoverlay transmission mode. Combining the additional cost with the throughput of cog-nitive radio network, a length of sensing period optimization issue is proposed basedon inactive secondary users in cognitive radio network. Under the fairness constraints,an optimization issue is proposed by allowing the inactive secondary users to coop-erate or not, the proposed optimization issue can improve both the throughput andthe efficiency. Both the mathematical analysis and simulations show that the inactivesecondary users can improve the sensing performance.
2. A length of sensing period optimization issue is proposed by considering theinter-cell interference in the underlay transmission mode. When the inter-cell interfer-ence is existed, a scheme which can change the transmission mode between overlayand underlay based on the pilot sensing was proposed. Considering the SINR of pri-mary user satisfies the outage probability, the optimization problem of transmit powerof secondary user was changed into a tradeoff problem between sensing and through-put. Then the maximum network throughput is formulated as an object function. Afteranalyzing the optimization problem, an effective algorithm of the length of sensingperiod for maximizing the throughput was found. Simulations results show that theproposed policy based on sensing period can improve the sensing performance.
3. Due to the uncertainty of primary users’ states, random sensing policy isconvenient to implement but cannot find vacant channels rapidly. A joint random sens-ing policy by using the inactive secondary users in cognitive networks was proposed. After utilizing inactive secondary users to detect, sensing performance of cognitivenetworks can be deduced by modeling the list of available channels stored in cog-nitive base station as markov model. Based on the fairness principle, an availablechannels allocation strategy was proposed for active secondary users. Both the theo-retical analysis and simulations results show that sensing with inactive cognitive userscan reduce the service overhead and improve the cognitive network throughput. Afterconsidering the report overhead of secondary users, the optimal number of inactiveusers was obtained which yields the highest throughput of cognitive network throughan optimization algorithm.
4. In cognitive radio networks, A novel scheme which utilizes inactive secondaryusers efficiently has been proposed to manage the problem caused by optimal sensingorder in joint allocated sensing policy. the primary The users’ traffic patterns wasmodeled as continuous-time Markov chains. Considering the influence of sensingperformance, the throughput of cognitive radio networks is formulated as an objectfunction, and an optimal sensing order is obtained. As the difference between up linkand down link, We get an optimal sensing strategy in up link mode and a suboptimalsensing strategy with low complexity in down link mode. The numerical simulationresults show that the proposed order based on spectrum sensing scheme can achievehigher throughput,larger channel utilization and lower sensing overhead as comparedwith the spectrum sensing scheme without using the optimal order sensing. Afterconsidering the report overhead of SUs, the optimal number of inactive SUs for themaximum throughput can be found.
5. In cognitive radio network，each active secondary user wants to get muchchannel information. An allocation algorithm based on the auction theory is proposedto solve the ownership of inactive secondary users. The payoffs of transmission vol-ume action and satisfaction degree action were studied under the second-price auc-tion mode. An auction algorithm based on reserve price, budget constraint and fair-ness limit was proposed. The numerical simulation results show that the schemebased on auction algorithm can achieve higher performance as compared with otherschemes.
1.在overlay传输模式下提出了一种利用空闲认知用户的检测模型，通过分析得出认知网络的检测性能。由于利用空闲认知用户需要额外的消耗，同时考虑认知网络的吞吐量和使用效率，提出空闲认知用户在协作检测中的额外检测时长的优化问题。在公平性原则的要求下，允许空闲认知用户选择是否进行协作，提出了一种兼顾吞吐量和效率的优化算法。理论与仿真证明了加入空闲认知用户进行协作检测可以提升检测的性能。
2.针对主要用户网络存在网间干扰时，underlay传输模型下认知网络吞吐量较低的问题，提出了一种利用导频检测在underlay传输模式下切换发射功率以提升认知网络吞吐量的检测时长优化算法。首先考虑主要用户接收信干噪比满足的溢出概率，将对认知用户发射功率的优化问题转化成一个”检测-传输”的权衡问题。然后对权衡问题进行分析，得出使得吞吐量最大的检测时长优化算法。仿真结果表明，采用最优检测时长算法可以获得最大的认知网络吞吐量。
3.由于认知网络中主要用户状态的不确定性，随机检测策略虽然易于实现，但无法保证认知用户准确地寻找到可用信道。本文提出一种利用认知无线网络中空闲认知用户进行联合随机检测的策略。首先加入空闲认知用户进行检测，然后利用马尔科夫模型对认知基站获得的可用信道数进行描述，推导出此时认知网络的检测性能。理论分析和仿真结果表明，利用空闲认知用户可以减小服务时延，并且提高认知网络的吞吐量。在考虑认知用户汇报检测信息所占用的时长后，通过优化算法，可以得出最优的参与联合检测的空闲认知用户数。
4.在认知无线网络中，针对分配式联合检测中的最优检测顺序问题，本文提出了一种利用空闲认知用户的检测策略以最大化认知网络的吞吐量。首先使用连续时间马尔科夫模型对主要用户的活动状况进行建模，然后考虑检测性能对认知网络吞吐量的影响，得出此时认知网络吞吐量的表达式。并以此为目标函数，提出最大化认知网络吞吐量的检测顺序优化算法。由于上下行链路的差异性，在下行链路提出一种最优的检测策略；在上行链路提出一种次优的但是复杂度较低的检测策略。仿真证明了提出的检测顺序优化算法与随机检测相比拥有更好的吞吐量，并能获得更高的频谱利用率，同时降低了认知用户的等待时延。在考虑空闲认知用户的汇报时长后，得出最大化认知网络吞吐量的参与检测的空闲认知用户数。
5.每一个活跃认知用户都希望尽可能多的获得信道状态信息。为了解决认知网络中空闲认知用户的所属权问题，本文提出一种利用拍卖算法对空闲认知用户进行分配的方案。研究了在第二价格的拍卖场景下，认知用户在传输量拍卖和满意度拍卖两种模式下所能获得的收益。同时提出了一种存在预留价格、预算受限以及公平性限制等条件下的拍卖算法。仿真结果表明，同其他算法相比，基于拍卖的空闲认知用户分配算法可以使认知网络获得较好的性能。
With the rapid development of communication technology, spectrum becomes avery scarce resource. The application of the wireless communication is restricted byspectrum utilization. Cognitive radio is widely regarded as one of the key technolo-gies, which can improve the spectrum utilization by using the available spectrum moreefficiently through opportunistic spectrum usage. Spectrum sensing plays an impor-tant role in cognitive radio networks. Available spectrum resources will appear whenthe channels allocated to primary users are idle. Similarly, the sensing performanceis improved by utilizing the inactive secondary users. This dissertation deals with thesensing policies in cognitive radio networks, such as cooperative sensing, joint sens-ing and the allocation of the inactive secondary users. The main achievements of thisdissertation are listed as follows:
1. A sensing model is proposed by using the inactive secondary users in theoverlay transmission mode. Combining the additional cost with the throughput of cog-nitive radio network, a length of sensing period optimization issue is proposed basedon inactive secondary users in cognitive radio network. Under the fairness constraints,an optimization issue is proposed by allowing the inactive secondary users to coop-erate or not, the proposed optimization issue can improve both the throughput andthe efficiency. Both the mathematical analysis and simulations show that the inactivesecondary users can improve the sensing performance.
2. A length of sensing period optimization issue is proposed by considering theinter-cell interference in the underlay transmission mode. When the inter-cell interfer-ence is existed, a scheme which can change the transmission mode between overlayand underlay based on the pilot sensing was proposed. Considering the SINR of pri-mary user satisfies the outage probability, the optimization problem of transmit powerof secondary user was changed into a tradeoff problem between sensing and through-put. Then the maximum network throughput is formulated as an object function. Afteranalyzing the optimization problem, an effective algorithm of the length of sensingperiod for maximizing the throughput was found. Simulations results show that theproposed policy based on sensing period can improve the sensing performance.
3. Due to the uncertainty of primary users’ states, random sensing policy isconvenient to implement but cannot find vacant channels rapidly. A joint random sens-ing policy by using the inactive secondary users in cognitive networks was proposed. After utilizing inactive secondary users to detect, sensing performance of cognitivenetworks can be deduced by modeling the list of available channels stored in cog-nitive base station as markov model. Based on the fairness principle, an availablechannels allocation strategy was proposed for active secondary users. Both the theo-retical analysis and simulations results show that sensing with inactive cognitive userscan reduce the service overhead and improve the cognitive network throughput. Afterconsidering the report overhead of secondary users, the optimal number of inactiveusers was obtained which yields the highest throughput of cognitive network throughan optimization algorithm.
4. In cognitive radio networks, A novel scheme which utilizes inactive secondaryusers efficiently has been proposed to manage the problem caused by optimal sensingorder in joint allocated sensing policy. the primary The users’ traffic patterns wasmodeled as continuous-time Markov chains. Considering the influence of sensingperformance, the throughput of cognitive radio networks is formulated as an objectfunction, and an optimal sensing order is obtained. As the difference between up linkand down link, We get an optimal sensing strategy in up link mode and a suboptimalsensing strategy with low complexity in down link mode. The numerical simulationresults show that the proposed order based on spectrum sensing scheme can achievehigher throughput,larger channel utilization and lower sensing overhead as comparedwith the spectrum sensing scheme without using the optimal order sensing. Afterconsidering the report overhead of SUs, the optimal number of inactive SUs for themaximum throughput can be found.
5. In cognitive radio network，each active secondary user wants to get muchchannel information. An allocation algorithm based on the auction theory is proposedto solve the ownership of inactive secondary users. The payoffs of transmission vol-ume action and satisfaction degree action were studied under the second-price auc-tion mode. An auction algorithm based on reserve price, budget constraint and fair-ness limit was proposed. The numerical simulation results show that the schemebased on auction algorithm can achieve higher performance as compared with otherschemes.
引文
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