A cooperative model of multiple primary and secondary users coexisting cognitive network is presented. In this model, the control center is aware of all the users＇ locations in order to allocate the nearest secondary user to the primary user. The control center is aware of the information of the unused spectral resources in terms of the feedback of the sensing results from the secondary users. It allocates idle frequency bands among the secondary users. The primary user accesses the base station （BS） in orthogonal subchannels, and it cooperatively transmits packets with the secondary user and exploits the free band assigned by the control center to amplify-and-forward what it receives immediately. Under this scenario, the outage probability of the cooperative transmission pair of the primary and secondary transmitters is derived. The numerical simulation of the outage probabilities as a function of primary transmission probability ps, power allocation ratio ξ between the primary and secondary users, and the numbers of the primary and secondary users are given respectively. The results show that the optimal system performance is achieved under the conditions of ξ=0.5 and the numbers of the primary and the secondary users being equal.
基于射频识别技术(Radio frequency identification technology,RFID)和近距离无线组网通讯技术(ZigBee:紫蜂)这两大物联网关键技术,设计以ZigBee协议作为传输协议的物联网主从节点以及RFID读写模块,得到了物联网实验系统的总体方案,并实现了一套完整的物联网实验系统硬件平台。测试结果验证了该实验系统完全满足设计要求,可以应用于教学实验,也可作为其他物联网应用系统的开发。
In order to improve network connectivity in clustered wireless sensor networks,a node cooperative algorithm based on virtual antenna arrays is proposed.All the nodes in the network are assumed to be clustered via Poisson Voronoi tessellation（PVT）.The activation of the node cooperative algorithm is determined by the cluster heads（CHs） according to communication links.When the cooperative algorithm is activated,the CH selects cooperative nodes（CNs） from its members to form a virtual antenna array.With the cooperation,nodes can extend the inter-cluster communication range to directly contact with further nodes after a coverage hole is detected,or compensate for channel gains while inter-cluster transmission fails due to deep channel fading.Simulation results show that the proposed algorithm achieves better network connectivity and energy efficiency.It can reduce outage probability,sustain network connectivity and maintain operations as long as possible,which prolongs network operation time.
According to the fact that the secondary users＇ delay requirements for data transmission are not unitary in cognitive radio networks, the secondary users are divided into two classes, denoted by SU1 and SU2, respectively. It is assumed that SU1 has a higher priority to occupy the primary users＇ unutilized channels than SU2. A preemptive resume priority M/G/1 queuing network is used to model the multiple spectrum handoffs processing. By using a state transition probability matrix and a cost matrix, the average cumulative delays of SU1 and SU2 are calculated, respectively. Numerical results show that the more the primary user＇s traffic load, the more rapidly the SU2＇s cumulative handoff delay grows. Compared with the networks where secondary users are unitary, the lower the SUI＇s arrival rate, the more obviously both SUI＇s and SU2＇s handoff delays decrease. The admission access regions limited by the maximum tolerable delay can also facilitate the design of admission control rules for graded secondary users.
Due to the fact that the conventional spectrum sensing algorithm is susceptible to noise, an adaptive double-threshold energy detection algorithm for a cognitive radio is proposed. Based on double-threshold energy detection, the algorithm can adaptively switch between one-round sensing and two-round sensing by comparing the observations with the pre-fixed thresholds. Mathematical expressions for the probability of detection, the probability of false alarm, and the sensing time are derived. The relationships including signal to noise ratio （SNR） vs. the probability of detection and SNR vs. the sensing time are plotted using Monte Carlo simulation and the algorithm is verified in a real cognitive system based on GNU Radio and universal software radio peripheral （USRP）. Simulation and experimental results show that, compared with the existing spectrum sensing method, the proposed algorithm can achieve a higher probability of detection within a reasonable sensing time.
