ID 原文 译文
39036 最后，利用高精度单频估计算法估计匹配相关后波形的残余频偏，提高频率估计精度。 Finally, the high-precision single frequency estimation algorithm is used to estimate the residual frequency deviation of the matched correlation waveform to improve the accuracy of frequency estimation.
39037 理论分析和仿真结果表明，所提算法在保证估计精度的同时大大提高了频率估计范围，更适用于非合作接收环境。 Theoretical analysis and simulation results show that the proposed algorithm improves the range of frequency estimation while ensuring the accuracy of estimation, and is more suitable for non-cooperation communication systems.
39038 针对第五代/后五代(The Fifth Generation/Beyond The Fifth Generation，5G/B5G)移动网络以用户为中心的小基站密集部署问题，构建了一个用户簇分布的三层异构网络模型。 In order to solve the problem of dense deployment of user-centric small base stations in fifth generation/beyond the fifth generation(5 G/B5 G) networks, a three-tier heterogeneous network model with user cluster distribution was constructed.
39039 该网络模型由宏基站(Macro Base Station， MBS)、微微基站(Pico Base Station， PBS)和毫微微基站(Femto Base Station， FBS)组成。 The network model consists of macro base stations(MBS), pico base stations(PBS) and femto base stations(FBS).
39040 采用随机几何理论对三层异构网络基站部署进行建模。 Stochastic geometry theory is used to model the deployment of base stations in the three-tier heterogeneous network.
39041 充分分析了毫微微基站层基于SSA干扰管理的网络干扰统计特性，考虑了有序FBS和无序FBS两种情况，给出了FBS下行链路的覆盖概率。 Fully analyzed the network interference statistical characteristics of the femto base station tier based on SSA interference management, considered the two cases of ordered FBS and Non-ordered FBS, and gave the coverage probability of FBS downlink.
39042 通过仿真，验证了理论结果的正确性，分析了覆盖半径、方差以及宏基站密度对覆盖概率的影响，得出有序FBS方案和无序FBS方案在覆盖概率方面的好坏性取决于系统参数。 Through simulation, the correctness of the theoretical results is verified, the influence of coverage radius, variance and macro base station density on coverage probability is analyzed, and it is concluded that the ordered FBS and the Non-ordered FBS scheme depend on the system parameters in terms of coverage probability.
39043 针对在卫星认知通信场景下传统频谱感知算法感知性能低、受通信时延影响大的问题，提出了一种基于长短期记忆(LSTM)神经网络的卫星频谱多门限感知算法。 A satellite spectrum multi-threshold sensing algorithm based on long short-term memory(LSTM) neural network is proposed in allusion to the problems of low sensing performance and high influence of communication delay in satellite cognitive communication.
39044 首先构建卫星认知通信模型，其次将仿真数据送入长短期记忆(LSTM)神经网络进行预测感知，采用动量随机梯度下降(SGDM)算法对网络进行更新，然后提出多门限算法对网络输出进行优化，最后与其他神经网络算法作性能对比。 Firstly, the satellite cognitive communication model is constructed, then the simulation data is sent to the LSTM neural network for prediction and sensing, and the network is updated by the stochastic gradient descent with momentum(SGDM) algorithm.
39045 该算法无需构建特征值，实验结果表明:在卫星信道条件下，当面对低接收信噪比及低网络迭代次数时，该算法频谱感知性能要优于其他神经网络算法。 Then the multi-threshold algorithm is proposed to optimize the output of LSTM neural network, and finally, the performance is compared with other neural network algorithms.The results show that under the condition of satellite channel, the spectrum sensing performance of the proposed algorithm is better than that of other neural network algorithms in low signal-to-noise ratio(SNR) and low neural network iterations.