ID 原文 译文
21475 通过理论分析，提出了保证算法收敛的充分条件，并计算出表征滤波性能的稳态额外均方误差(EMSE)。 A sufficient condition for guaranteeing convergence of the proposed q-APA is also presented, and its steady-state Excess Mean Square Error (EMSE) of q-APA is obtained theoretically to evaluate the filtering performance.
21476 除此之外，为了进一步提高算法的滤波性能，提出一个变q的APA(V-q-APA)。 In addition, the Variable q-APA (V-q-APA) is developed to improve further the filtering performance.
21477 在高斯噪声环境下，将q-APA和V-q-APA应用于系统辨识中。仿真结果表明：与传统的APA和变q的最小化均方(V-q-LMS)算法相比，q-APA和V-q-APA均具有更好的滤波性能。 Simulations in the context of system identification demonstrate the superior filtering performance of the proposed algorithms compared with APA and Variable q-Least Mean Square (V-q-LMS) algorithm in the presence of Gaussian noise.
21478 基于消息传递算法(MPA)进行多用户检测的稀疏码多址接入(SCMA)技术是一种面向5G的非正交多址技术(NOMA)。 Sparse Code Multiple Access (SCMA), based on Message Passing Algorithm (MPA) for multiuser detection, is a Non-Orthogonal Multiple Access (NOMA) scheme proposed to meet the demands of the future 5G communication.
21479 针对MPA复杂度较高的问题，该文首先分析接收信号概率密度函数值在不同信噪比(SNR)下的统计结果，并根据SCMA的非正交特性，综合考虑资源节点和用户节点之间的数据映射关系，提出基于概率密度函数值门限判决的部分码字搜索(PCS)MPA多用户检测算法(PCS-MPA)。 For the problem that the MPA has the characteristics of high algorithm complexity, some statistical results for the Probability Density Function (PDF) of received signal at various Signal to Noise Ratio(SNR) are first derived. Then, data mapping relationship between resources node and users node is fully considered based on the non-orthogonal property of SCMA, therefore a Partial Codewords Searching of MPA (PCS-MPA) is proposed with threshold decision scheme of PDF.
21480 仿真结果表明，在门限值合理的条件下，PCS-MPA在几乎不改变系统误比特率(BER)的条件下，降低了MPA的复杂度，尤其在高SNR条件下效果更好。 Simulations results show that the proposed PCS-MPA can reduce the complexity without changing the Bit Error Ratio (BER), especially at the case of high SNR.
21481 传统的合作频谱感知一般将感知环境建模为单级信道，且次用户一般都以相同的发射功率向数据融合中心报告感知数据，难以体现并利用不同次用户感知数据之间的空间分集差异。 In conventional cooperative spectrum sensing, the signal model is usually simplified as a single-stage channel environment where the Secondary Users (SUs) collect their spectrum data and report to the Fusion Center (FC) with the same transmit power. This hampers the FC from efficiently exploiting the space diversity gain beneath the data of different users.
21482 为解决此问题并有效地设置次用户在感知数据上报阶段的发射功率，该文提出了3种最优功率控制方案，以获得相应设计准则下参与合作感知的次用户最优发射功率。 In order to solve this problem and control the user transmit power in reporting their data, three Optimal Power Control (OPC) schemes are proposed.
21483 在融合中心理想具备感知信道和报告信道的统计特性时，通过理论推导获得了基于信道统计特性的功率控制闭式解方案；当信道统计特性难以现实具备时，分别获得了基于联合信道统计特性估计的最大特征功率矢量及盲加权多特征功率矢量方案。 When the Channel Statistic(CS) of the sensing channel and the reporting channel are perfectly known at the FC, a CS Aided Optimal Power Control (CSA-OPC) scheme is derived in closed-form, whereas when the CS is practically unavailable, Principal Eigen Vector aided OPC (PEV-OPC) and Blindly Weighted Multiple-Eigen Vector aided OPC (BWMEV-OPC) schemes are developed.
21484 理论分析和仿真实验表明，在不同的先验信息条件下，3种方案的性能皆远优于缺少功率控制的合作感知方案。 Theoretical analysis and computer simulation verify that the propose OPC schemes greatly ameliorate the spectrum sensing performance, compared to the non-OPC aided cooperative spectrum sensing schemes.