ID 原文 译文
47136 针对非合作接收的加扰信号，提出 2 种基于软信息的扰码盲识别方法。 Two scrambler blind recognition methods based on soft information were proposed for received signal innon-cooperative ways.
47137 方法 1 利用软信息建立了扰码系数的代价函数，采用实数域的优化理论进行正向求解， The first method established a cost function of the scrambler coefficients by using the soft infor-mation, and adopted the optimization theory of real number field for positive solution.
47138 不再需要对多项式测试闭集进行遍历； So it didn’t need to traverse theclosed set of test polynomial any more.
47139 方法 2 利用软信息建立了符合度的概念，以每个测试扰码多项式符合度的大小作为判别的标准， The second method built conformity degree concept with the soft information,and used the size of conformity of each test scrambler polynomial as the discriminant criteria.
47140 相比硬判决识别算法，其对接收信息得到了更充分的利用。 So it made more full use ofthe received information compared to the hard sentence recognition algorithm.
47141 仿真结果表明，方法 1 相比 Cluzeau 提出的遍历方法，其自同步扰码多项式的识别时间可从 5 min 18 s 缩短为 8 s；方法 2 与现有硬判决算法相比，达到较高正确率时，具有约 2 dB 的信噪比增益。 Simulation results show that the first me-thod can shorten the recognition time of a synchronous scrambler polynomial from 5 min 18 s to 8 s compared with thetraversal method put forward by Cluzeau, and the second method has 2 dB SNR gain when to achieve the relatively highaccuracy compared with the hard sentence recognition algorithm.
47142 在未来异构无线网络中，授权用户（PU）与认知用户（SU）间无法进行协作定时，导致授权用户发射机和认知用户接收机之间存在感知时间差。 In the future heterogeneous wireless networks, since primary user (PU) and cognitive secondary user (SU) arenot coordinated to be synchronous, it will result in sense timing difference between PU’s transmitter and SU’s receiver.
47143 针对这一异步感知场景，基于贝叶斯统计估计理论提出一种全新的异步感知算法。 For this asynchronous sense case, a new asynchronous sensing algorithm based on Bayesian estimation theory was pro-posed.
47144 首先，提出一种统一的动态状态空间模型，来描述可观测能量与动态授权用户状态以及未知时间差之间的关系； A unified dynamic state space model was first proposed to describe the observable energy relationship with dy-namic PU state and unknown timing difference.
47145 然后，利用随机有限集并基于最大后验概率准则设计一种迭代式估计方案； Then, an iterative estimation scheme was designed using stochastic finiteset and the rules of maximum posterior probability.