ID 原文 译文
633 仿真和数值结果表明,SBS下行链路覆盖概率会随着小小区下行链路功率共享系数的增加而减小; Simulation and numerical results show that the SBS downlink coverage probability decreases as the downlink power sharing coefficient of the small cell increases.
634 此外,通过对比 NOMA 和正交多址接入(Or-thogonal Multiple Access,OMA)以及 FD 和半双工(Half-Duplex,HD)对下行链路覆盖性能的影响,本文提出的方案能显著提升网络性能。 In addition, by comparing the effects of NOMA and orthogonal multiple access (OMA), FD and half-duplex (HD)on downlink coverage performance, network performance of the proposed scheme is significantly improved.
635 研究多入多出(Multiple Input Multiple Output,MIMO)同时同频全双工双向通信系统中,合法节点在接收信息的同时向对方发送保密信息,并发送零空间人工噪声干扰窃听节点的物理层安全方案的优化问题。 The optimization of physical layer security scheme in the multiple input multiple output(MIMO)fulldu-plex two-way communication system is studied, where legitimate nodes send confidential information and null space artificialnoise while receiving information.
636 针对窃听信道状态信息仅统计分布已知,且存在残余自干扰的情况,首先推导出系统平均保密和速率的闭合表达式,进一步给出其下界。 For the case where the eavesdropping' s channel state information is only statistically known and there is residual self-interference, the closed-form expression of the average achievable secrecy sum rate is first derived, then its lower bound is further given.
637 在此基础上,以最大化系统该下界为目标,对两节点的信息信号与人工噪声的功率分配因子、信息信号的功率分配矩阵进行联合优化。 Aiming at maximizing the lower bound, the power allocation factors of the ar-tificial noise and the information signal, along with the power allocation matrices of the information signal are jointly opti-mized.
638 采用迭代的方法进行优化,每轮迭代中,先固定前者,优化后者,再固定后者,优化前者。 An iterative method is used. In each iteration, we first fix the former and optimize the latter, then fix the latter and op-timize the former.
639 使用DC(Difference of Concave/Convex,DC)规划优化信息信号功率分配矩阵,使用遗传算法优化信息信号与人工噪声的功率分配因子。 The DC (Difference of Concave/Convex, DC)programming and the genetic algorithm are used to opti-mize the information's power allocation matrices as well as the power allocation factors of the information signal and artifi-cial noise respectively.
640 对所提方案进行了仿真验证,证明理论推导正确,优化算法能有效地提高系统的平均保密和速率。 The simulation results prove that the theoretical derivation is correct, and the optimization algorithm can effectively improve the average secrecy sum rate.
641 对于雷达高分辨距离像的识别问题,传统深层网络通常忽略了 HRRP 自身的目标特性,不利于学习有效的分类特征,导致其识别性能受到限制。 Traditional deep networks used for radar High-Resolution Range Profile (HRRP)target recognition usuallyignore the inherent characteristics of the target, which results in the limited capability to learn effective features for classifica-tion task.
642 针对这一问题,本文提出了一种基于稳健变分自编码模型的目标识别算法。 To address this issue, a novel nonlinear feature learning method, called Robust Variational Auto-Encoder model(RVAE)is proposed.