This paper focuses on multi-channel Cooperative Spectrum Sensing (CSS) where Secondary Users (SUs) are assigned to cooperatively sense multiple channels simultaneously. A multi-channel CSS optimization problem of join...This paper focuses on multi-channel Cooperative Spectrum Sensing (CSS) where Secondary Users (SUs) are assigned to cooperatively sense multiple channels simultaneously. A multi-channel CSS optimization problem of joint spectrum sensing and SU assignment based on data fusion rule is formulated, which maximizes the total throughput of the Cognitive Radio Network (CRN) subject to the constraints of probabilities of detection and false alarm. To address the optimization problem, a Branch and Bound (BnB) algorithm and a greedy algorithm are proposed to obtain the optimal solutions. Simulation results are presented to demonstrate the effectiveness of our proposed algorithms and show that the throughput improvement is achieved through the joint design. It is also shown that the greedy algorithm with a low complexity achieves the comparable performance to the exhaustive algorithm.展开更多
In order to take advantage of the asynchronous sensing information, alleviate the sensing overhead of secondary users （SUs） and improve the detection performance, a sensor node-assisted asynchronous cooperative spec...In order to take advantage of the asynchronous sensing information, alleviate the sensing overhead of secondary users （SUs） and improve the detection performance, a sensor node-assisted asynchronous cooperative spectrum sensing （SN-ACSS） scheme for cognitive radio （CR） network （CRN） was proposed. In SN-ACSS, each SU is surrounded by sensor nodes （SNs）, which asynchronously make hard decisions and soft decisions based on the Bayesian fusion rule instead of the SU. The SU combines these soft decisions and makes the local soft decision. Finally, the fusion center （FC） fuses the local soft decisions transmitted from SUs with different weight coefficients to attain the final soft decision. Besides, the impact of the statistics of licensed band occupancy on detection performance and the fact that different SNs have different sensing contributions are also considered in SN-ACSS scheme. Numerical results show that compared with the conventional synchronous cooperative spectrum sensing （SCSS） and the existing ACSS schemes, SN-ACSS algorithm achieves a better detection performance and lower cost with the same number of SNs.展开更多
在协作频谱感知网络中,设备故障、信道阴影衰落和噪声等会导致频谱感知器(如手机、平板等)发送的信息不可靠,而恶意用户在协作频谱感知网络中,也会发送错误的感知信息以混淆视听,干扰诚实用户的判决结果。不可靠消息在邻居用户间的传递...在协作频谱感知网络中,设备故障、信道阴影衰落和噪声等会导致频谱感知器(如手机、平板等)发送的信息不可靠,而恶意用户在协作频谱感知网络中,也会发送错误的感知信息以混淆视听,干扰诚实用户的判决结果。不可靠消息在邻居用户间的传递必将导致感知结果产生偏差和错误,大大降低了协作频谱感知的效率。为解决上述问题,本文将置信传播算法和信誉模型相结合,提出一种基于次用户分组的频谱感知数据伪造(SSDF,Spectrum Sensing Data Falsification)攻击防御方案。该方案分两个阶段对不可靠信息进行过滤:首先,在频谱感知阶段,通过置信传播算法对次用户进行分组,过滤掉因设备故障等因素产生的不可靠用户,剩余用户则视为正常工作用户进行数据融合。然后,在数据融合阶段,根据以信誉值作为权重因子的置信传播算法来计算最终的判决值。本文所提方案分别在感知阶段和融合阶段采取了防御措施,可有效地过滤网络中的不可靠信息,减小恶劣的频谱环境对次用户感知结果的影响。仿真结果表明,本文所提方案迭代次数少、收敛快,有效地减弱了SSDF攻击带来的损害,提高了感知结果的准确性、增强了认知无线网络的安全性。展开更多
基金Supported by the National Natural Science Foundation of China (No. 61271169)National Basic Research Program (973 Program) of China (No. 2009CB320405)Nation Grand Special Science and Technology Project of China under Grant (No. 2010ZX03006-002, 2010ZX03002-008-03)
文摘This paper focuses on multi-channel Cooperative Spectrum Sensing (CSS) where Secondary Users (SUs) are assigned to cooperatively sense multiple channels simultaneously. A multi-channel CSS optimization problem of joint spectrum sensing and SU assignment based on data fusion rule is formulated, which maximizes the total throughput of the Cognitive Radio Network (CRN) subject to the constraints of probabilities of detection and false alarm. To address the optimization problem, a Branch and Bound (BnB) algorithm and a greedy algorithm are proposed to obtain the optimal solutions. Simulation results are presented to demonstrate the effectiveness of our proposed algorithms and show that the throughput improvement is achieved through the joint design. It is also shown that the greedy algorithm with a low complexity achieves the comparable performance to the exhaustive algorithm.
基金supported by the National Basic Research Program of China (2011CB302903)the National Natural Science Foundation of China (61201161, 61271335)the Postdoctoral Science Foundation of Jiangsu Province (1301002B)
文摘In order to take advantage of the asynchronous sensing information, alleviate the sensing overhead of secondary users （SUs） and improve the detection performance, a sensor node-assisted asynchronous cooperative spectrum sensing （SN-ACSS） scheme for cognitive radio （CR） network （CRN） was proposed. In SN-ACSS, each SU is surrounded by sensor nodes （SNs）, which asynchronously make hard decisions and soft decisions based on the Bayesian fusion rule instead of the SU. The SU combines these soft decisions and makes the local soft decision. Finally, the fusion center （FC） fuses the local soft decisions transmitted from SUs with different weight coefficients to attain the final soft decision. Besides, the impact of the statistics of licensed band occupancy on detection performance and the fact that different SNs have different sensing contributions are also considered in SN-ACSS scheme. Numerical results show that compared with the conventional synchronous cooperative spectrum sensing （SCSS） and the existing ACSS schemes, SN-ACSS algorithm achieves a better detection performance and lower cost with the same number of SNs.
文摘在协作频谱感知网络中,设备故障、信道阴影衰落和噪声等会导致频谱感知器(如手机、平板等)发送的信息不可靠,而恶意用户在协作频谱感知网络中,也会发送错误的感知信息以混淆视听,干扰诚实用户的判决结果。不可靠消息在邻居用户间的传递必将导致感知结果产生偏差和错误,大大降低了协作频谱感知的效率。为解决上述问题,本文将置信传播算法和信誉模型相结合,提出一种基于次用户分组的频谱感知数据伪造(SSDF,Spectrum Sensing Data Falsification)攻击防御方案。该方案分两个阶段对不可靠信息进行过滤:首先,在频谱感知阶段,通过置信传播算法对次用户进行分组,过滤掉因设备故障等因素产生的不可靠用户,剩余用户则视为正常工作用户进行数据融合。然后,在数据融合阶段,根据以信誉值作为权重因子的置信传播算法来计算最终的判决值。本文所提方案分别在感知阶段和融合阶段采取了防御措施,可有效地过滤网络中的不可靠信息,减小恶劣的频谱环境对次用户感知结果的影响。仿真结果表明,本文所提方案迭代次数少、收敛快,有效地减弱了SSDF攻击带来的损害,提高了感知结果的准确性、增强了认知无线网络的安全性。
