ID 原文 译文
51397 文章结合单路径专有保护和带宽分割多路径专有保护提出了一种混合路径专有保护(HDPP)算法。 In this paper, a Hybrid Dedicated Path Protection(HDPP) routing spectrum allocation strategy is proposed by combining single-path dedicated protection and partitioning dedicated path protection.
51398 该算法利用路径的单位频谱效率和路径跳数计算了k条链路不相关候选路径， This strategy considers the distance adaptive modulation and the number of path hops pre-calculated k link disjoint candidate paths.
51399 并提出了一种考虑单位频隙最高频谱效率和路径跳数以及路径上最大可用频谱信息的多路径频谱分配(MPSA)算法， We also propose a Multiple Path Spectrum Assignment(MPSA) strategy that considers the highest spectrum efficiency per unit frequency slot with the number of path hops and the maximum available spectrum information on the path.
51400 最后，HDPP算法在多种生存性方案中选择出最佳方案。 HDPP selects the best scheme among multiple survivability routing spectrum allocation schemes.
51401 仿真结果表明，与对比算法相比，所提算法在阻塞率和频谱利用率方面都有较好的性能表现。 The simulation results show that the proposed algorithm has better performance in terms of blocking rate and spectrum utilization compared with other algorithms.
51402 由于海水的散射特性，光在水下传输时会产生码间串扰(ISI)问题，传输环境较差时尤为严重。 Due to seawater scattering characteristics, Inter-Symbol Interference(ISI) will occur in underwater transmission, especially in poor transmission environment.
51403 为解决该问题，文章将预均衡技术应用于基于直流偏置光正交频分复用(DCO-OFDM)调制的水下光通信系统中，并针对水下光的传输特性提出了一种基于先验信息的预均衡方法。 In order to solve this problem, pre-equalization technology is applied to underwater optical communication system based on Direct Current Offset Orthogonal Frequency Division Multiplexing(DCO-OFDM) modulation, and a pre-equalization method based on prior information is proposed.
51404 在浑浊海港海水环境下与传统均衡算法进行了性能对比。 The performance of Turbid Harbor seawater channel is compared with that of traditional equalization algorithm.
51405 仿真结果表明，在信噪比(SNR)较差的情况下，采用所提方法能够有效降低水下光通信系统的ISI，降低了误码可能性，提高了信道估计的可靠性。 The simulation results show that the ISI in underwater optical communication system can be effectively reduced, as well as the Bit Error Rate(BER). The reliability of channel estimation can be improved under the condition of poor Signal Noise Ratio(SNR).
51406 相比于最小二乘(LS)后均衡算法，误码率能下降约3. 56 dB，相比于LS预均衡算法，误码率能下降约3. 00 dB，相较于最小均方误差(MMSE)和最小均方(LMS)后均衡算法，误码率下降约1. 85 dB。 Compared with the Least Squares(LS) post-equalization, LS pre-equalization and Mini-mental State Examination(MMSE) algorithms, the BER can be reduced by ～3. 56, ～3. 00 and ～1. 85 dB, respectively.