To mitigate the impacts of non-line-of-sight（NLOS） errors on location accuracy, a non-parametric belief propagation（NBP）-based localization algorithm in the NLOS environment for wireless sensor networks is proposed.According to the amount of prior information known about the probabilities and distribution parameters of the NLOS error distribution, three different cases of the maximum a posterior（MAP） localization problems are introduced. The first case is the idealized case, i. e., the range measurements in the NLOS conditions and the corresponding distribution parameters of the NLOS errors are known. The probability of a communication of a pair of nodes in the NLOS conditions and the corresponding distribution parameters of the NLOS errors are known in the second case. The third case is the worst case, in which only knowledge about noise measurement power is obtained. The proposed algorithm is compared with the maximum likelihood-simulated annealing（ML-SA）-based localization algorithm. Simulation results demonstrate that the proposed algorithm provides good location accuracy and considerably outperforms the ML-SA-based localization algorithm for every case. The root mean square error（RMSE）of the location estimate of the NBP-based localization algorithm is reduced by about 1. 6 m in Case 1, 1. 8 m in Case 2 and 2. 3 m in Case 3 compared with the ML-SA-based localization algorithm. Therefore, in the NLOS environments,the localization algorithms can obtain the location estimates with high accuracy by using the NBP method.
In order to achieve higher spectrum efficiency in cognitive radio （CR） systems, a closed-form expression of the optimal decision threshold for soft decision cooperative spectrum sensing based on the minimum total error probability criterion is derived. With the analytical expression of the optimal decision threshold, the impact of different sensing parameters on the threshold value is studied. Theoretical analyses show that the optimal threshold achieves an efficient trade-off between the missed detection probability and the false alarm probability. Simulation results illustrate that the average signal-to-noise ratio （SNR） and the soft combination schemes have a great influence on the optimal threshold value, whereas the number of samples has a weak impact on the optimal threshold value. Furthermore, for the maximal ratio combing （MRC） and the modified deflection coefficient （MDC） schemes, the optimal decision threshold value increases and approaches a corresponding individual limit value while the number of CR users increases. But the number of CR users has a weak influence on the optimal decision threshold for the equal gain combining （EGC） scheme.
In order to improve the performance of the security-reliability tradeoff （SRT）, a joint jammer and user scheduling （JJUS） scheme is proposed. First, a user with the maximal instantaneous channel capacity is selected to transmit its signal to the base station （ BS） in the transmission time slot. Then, when the user transmits its signal to BS, the jammer is invoked for transmitting artificial noise in order to perturb the eavesdropper’s reception. Simulation results show that increasing the number of users can enhance the SRT performance of the proposed JJUS scheme. In addition, the SRT performance of the proposed JJUS scheme is better than that of the traditional round-robin scheduling and pure user scheduling schemes. The proposed JJUS scheme can guarantee the secure transmission even in low main-to-eavesdropper ratio（ MER） regions.
