ID 原文 译文
17385 利用蜂窝认知无线电网络(CCRN)中的次级用户设备(SUE)所能提供的大量频谱观测数据，该文提出了一种基于主用户(PU)传输模式分类的频谱感知方案。 Based on the large amount of spectrumobservations captured by the Secondary User Equipment (SUE) in the Cellular Cognitive Radio Network(CCRN), this paper proposes a spectrum sensing scheme based on the Primary User (PU) transmission modeclassification.
17386 首先，基于多种典型的ML算法，对于网络中的多个主用户发射机(PUT)的传输模式进行分类辨识，在网络整体层面上确定所有PUT的联合工作状态。 Firstly, based on a variety of typical ML classification algorithms, the proposed scheme classifiesthe transmission mode of multiple Primary User Transmitters (PUTs) in the CCRN, and determines the jointoperating state of all the PUTs in the CCRN.
17387 然后，网络中的SUE根据其所处地理位置或者频谱观测数据，判断其在当前已判定的PUT发射模式下接入授权频谱的可能性。 Subsequently, the SUE evaluates the possibility of accessing thelicensed spectrum in the currently determined PUT transmission mode according to its geographical location orspectrum observation data.
17388 由于PUT在网络中的实际位置可能事先已知或者无法提前确定，该文给出了3种不同的处理方法。 Since the actual locations of the PUTs in the network may be readily known inadvance or unaware of at all, the proposed scheme solves the problem in three different methods.
17389 理论推导与实验结果表明，所提方案与传统的能量检测方案相比，不仅改善了频谱感知性能，还增加了蜂窝认知网络对于授权频谱的动态访问机会。 Theoreticalderivation and experimental results show that compared with the traditional energy detection scheme, theproposed scheme not only remarkably improves the spectrum sensing performance, but also significantlyincreases the opportunities of dynamic accessing to the licensed spectrum for the SUEs.
17390 该方案可以作为蜂窝认知无线电网络中的一种高效实用的频谱感知解决方案。 The proposed schemecan be used as an efficient and practical spectrum sensing solution in the CCRN.
17391 在多载波差分混沌键控(MC-DCSK)系统中，经由无线信道传输在接收端进行检测时，参考混沌信号的传输差错将降低承载信息的检测性能，降低传输可靠性。 In Multi-Carrier Differential Chaos Shift Keying (MC-DCSK) systems, after transmitted over wirelesschannels, the transmission errors in the reference chaotic signal will degrade the detection performances of theinformation-bearing signals at the receiver.
17392 为了提高可靠性，该文基于承载信息的调制信号因共享参考混沌信号的低秩特性，提出了一种基于矩阵低秩估计(LRAM)的MC-DCSK接收机，增强系统可靠性。 In order to address this issue, in this paper, a Low RankApproximation of Matrices (LRAM) aided MC-DCSK receiver is proposed based on the low rank characteristicsof the information-bearing chaotic modulated signals sharing the same reference chaotic signal, with the aim toenhance the reliability performances.
17393 该接收机将接收信号矩阵表示为秩1矩阵和噪声矩阵之和，然后对接收信号矩阵进行低秩估计，以得到参考信号的最优估计，并进而将其用于承载信息的调制信号的检测和解调，从而提升系统传输可靠性。 In the design, the received signal matrix is evaluated by the sum of a rankone matrix and a Gaussian noise matrix, and then the LRAM method is applied to derive the estimates ofreceived signals to attain the optimal estimate of the reference chaotic sequence, which is subsequently used torecover the user data, thereby improving the reliability performances of MC-DCSK systems.
17394 继而，该文证明了LRAM检测可等效于最大似然估计检测，并对信息泄露率理论安全性能进行了分析，分析结果表明所提方案安全性与基准MC-DCSK系统一致。 Subsequently, the proposed LRAM detection is proved that is equivalent to the maximum likelihood estimation detection, then the theoretical security performances in terms of the information leakage is analyzed. The analysis shows that the security performances of the proposed system keep the same as those of the benchmark MC-DCSK systems.