ID 原文 译文
26175 最后，通过数学仿真验证了算法在估计精度和收敛性能上的优越性。 Finally, this algorithm was verified by mathematical simulation on the estimation precision and convergence performance of superiority.
26176 提出一种结合空时分组码(space-time block coding，STBC)与双层预编码的方法。 In this paper, a combined with space-time block codes (space - time block coding, STBC) and double precoding method.
26177 建立了基于STBC的双层预编码多输入多输出(multiple input multiple output，MIMO)系统模型，给出了预编码赋形权矢量的构造方法，利用预编码形成的两个虚拟子信道同时传输两个数据流，同时结合Alamouti STBC构成混合编码，带来分集增益； Set up double precoding based on STBC multiple input multiple output (multiple input multiple output, MIMO) system model, gives the precoding informs the structure of the weight vector method, the use of precoding formed by two virtual channel transmission at the same time data stream, at the same time combined with Alamouti STBC constitute a hybrid coding, bring diversity gain;
26178 针对STBC双层预编码系统设计了一种低复杂度的译码方法。 For STBC double precoding system designed a low complexity decoding method.
26179 理论和仿真结果表明，新系统可以同时带来分集增益和复用增益，有效提高系统信道容量，与通常的MIMO系统相比，误码性能得到明显改善。 Theory and simulation results show that the new system can bring the diversity gain and multiplexing gain at the same time, effectively improve the channel capacity, compared with usually MIMO system, the error performance is obviously improved.
26180 依据传感器网络面向应用的价值区分度特征，提出一种基于冗余价值滤波的传感器网络节能数据收集机制。 Based on sensor network application oriented value differentiation characteristics, puts forward a kind of sensor network energy saving based on redundancy value filter data collection mechanism.
26181 所提机制采用预测模型在线评估采样数据价值，并映射为相应的价值因子，进而根据强化学习理论将价值因子引入区分服务的退避机制设计，驱动媒体介质访问层层竞争窗尺寸的自适应优化调整，在满足数据收集服务质量的前提下，有效地抑制网内价值冗余负荷传输量，实现价值区分性滤波的节能效果。 The proposed mechanism for online prediction model is adopted to estimate the sampling data value, and mapped to the corresponding value factor, and then based on the theory of reinforcement learning value factor introduced to distinguish the service retreat mechanism design, the driving medium access layer upon layer media competition window size, the adaptive optimization and adjustment of the data collection service quality under the premise of effectively restrain redundant load transmission network value quantity, realize the energy saving of value to distinguish the filtering effect.
26182 仿真实验表明，所提机制能有效增加网络吞吐量和降低传输时延，且相对于一些传统的节能收集机制，能够从传感器网络数据内涵应用价值挖掘的角度，更有效地降低网络整体能耗。 The simulation results show that the proposed mechanism can effectively increase the network throughput and reduce the transmission delay, and compared with some traditional energy collection mechanism, can from the Angle of the sensor network data connotation and application value mining, more effectively reduce the network energy consumption as a whole.
26183 对于双基地多输入多输出(multiple input multiple output，MIMO)雷达，发射和接收阵列幅相误差耦合到一起，不易单独测量。 For double base multiple input multiple output (multiple input multiple output, MIMO) radar, transmit and receive array amplitude-phase error coupled together, is not easy to separate measurement.
26184 针对阵列存在小扰动幅相误差的MIMO雷达，分别推导了借助旋转不变信号参数估计技术(estimating signal parameter via rotational invariance techniques，ESPRIT)算法的到达角(direction of ar-rival，DOA)和离开角(direction of departure，DOD)的均方根误差(root mean square error，RMSE)与幅相误差关系表达式。 In view of the array of the MIMO radar is small disturbance amplitude phase error, respectively is deduced by means of rotation invariant signal parameter estimation technology (estimating signal parameter via rotational invariance techniques, ESPRIT) algorithm of arrival Angle (direction of ar - originallydescribed, DOA) and left Angle (DOD) direction of departure, root mean square error (root mean square error, RMSE) and amplitude phase error of relational expression.