ID 原文 译文
20055 针对传统单通道异步直接序列码分多址(DS-CDMA)信号信息序列及伪码序列(PN)难以估计的问题，该文提出一种基于平行因子(PARAFAC)的多通道盲估计方法。 For the problem of Direct Sequence-Code Division Multiple Access (DS-CDMA) signal in traditionalasynchronous single-channel, including blind estimation of the Pseudo-Noise (PN) sequence and informationsequence, a method using multi-channel synchronous and asynchronous based on PARAllel FACtor(PARAFAC) is proposed.
20056 该方法首先将信号建模为多通道接收模型，然后将观测数据矩阵等效为平行因子模型， Firstly, the signal is modeled as a multi-channel receiving model, then the observeddata matrix is equivalent to a factor model.
20057 最后使用迭代最小二乘算法对平行因子进行低秩分解，进一步完成对DS-CDMA信号各用户的信息序列及伪码序列进行估计。 Finally, the iterative least squares algorithm is applied todecomposing the parallel factor, and the information sequence and PN sequences of DS-CDMA signals arefurther estimated.
20058 仿真实验表明，该方法不仅能有效地对同步、异步短码DS-CDMA信号的伪码序列及信息序列进行估计，而且能在通道数为6、信噪比(SNR)为–10 dB的条件下，实现10个用户伪码序列的有效估计。 The simulation results show that the proposed method can effectively estimate the PNsequence and information sequence of the short code DS-CDMA signal, and the estimation of 6 user PNsequences can be realized under the condition that the number of channels is 10 and the Signal-to-Noise Ratio(SNR) is –10 dB.
20059 针对现有研究中缺乏云无线接入网络(C-RAN)场景下对网络切片高效的动态资源分配方案的问题，该文提出一种虚拟化C-RAN网络下的网络切片虚拟资源分配算法。 To solve the problem of lacking efficient and dynamic resource allocation schemes for 5G Network Slicing (NS) in Cloud Radio Access Network (C-RAN) scenario in the existing researches, a virtual resource allocation algorithm for NS in virtualized C-RAN is proposed.
20060 首先基于受限马尔可夫决策过程(CMDP)理论建立了一个虚拟化C-RAN场景下的随机优化模型，该模型以最大化平均切片和速率为目标，同时受限于各切片平均时延约束以及网络平均回传链路带宽消耗约束。 Firstly, a stochastic optimization model invirtualized C-RAN network is established based on the Constrained Markov Decision Process (CMDP) theory,which maximizes the average sum rates of all slices as its objective, and is subject to the average delayconstraint for each slice as well as the average network backhaul link bandwidth consumption constraint in themeantime.
20061 其次，为了克服CMDP优化问题中难以准确掌握系统状态转移概率的问题，引入决策后状态(PDS)的概念，将其作为一种“中间状态”描述系统在已知动态发生后，但在未知动态发生前所处的状态，其包含了所有与系统状态转移有关的已知信息。 Secondly, in order to overcome the issue of having difficulties in acquiring the accurate transition probabilities of the system states in the proposed CMDP optimization problem, the concept of Post-DecisionState (PDS) as an “intermediate state” is introduced, which is used to describe the state of the system after the known dynamics, but before the unknown dynamics occur, and it incorporates all of the known information about the system state transition.
20062 最后，提出一种基于在线学习的网络切片虚拟资源分配算法，其在每个离散的资源调度时隙内会根据当前系统状态为每个网络切片分配合适的资源块数量以及缓存资源。 Finally, an online learning based virtual resource allocation algorithm ispresented for NS in virtualized C-RAN, where in each discrete resource scheduling slot, it will allocateappropriate Resource Blocks (RBs) and caching resource for each network slice according to the observedcurrent system state.
20063 仿真结果表明，该算法能有效地满足各切片的服务质量(QoS)需求，降低网络回传链路带宽消耗的压力并同时提升系统吞吐量。 The simulation results reveal that the proposed algorithm can effectively satisfy the Quality of Service (QoS) demand of each individual network slice, reduce the pressure of backhaul link onbandwidth consumption and improve the system throughput.
20064 该文给出了一般的2次多项式混沌系统与Tent映射拓扑共轭的充分条件，并依据该条件，给出了一类2次多项式混沌系统及其概率密度函数；进一步得到了能够将这类系统均匀化的变换函数； A sufficient condition for general quadratic polynomial systems to be topologically conjugate with Tent map is proposed. Base on this condition, the probability density function of a class of quadratic polynomial systems is provided and transformations function which can homogenize this class of chaotic systems is further obtained.