An Experiment of Adaptive PMD Compensation in 10 Gbit/s RZ Optical Communication System using PSO Algorithm

Zhang, Xiaoguang; Yu, Li; Zhou, Guorui; Shen, Yu; Yan, Zheng; Li, Chaoyang; Liu, Yumin; Chen, Lin; Xi, Lixia; Yang, Bojun

doi:10.1515/joc.2005.26.3.138

Cited by 4 publications

(8 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many reports, for the use of PSO in solving dynamic problem, are available in the literature on the application of different mechanism, i.e., reinitialization of particle positions [9][10], charged swarms [11] [12], limited memory [13], local search [14], split adaptive PSO [15], fine-grained PSO [16], hierarchical particle [17]. In the case of using mobile robots and multiple sensory modalities (e.g., odometry, anemometry, olfaction), we should carefully consider the feasibility of the hardware [18].…”

Section: Motivationmentioning

confidence: 99%

A Mobile Robots PSO-based for Odor Source Localization in Dynamic Advection-Diffusion Environment

Jatmiko

Sekiyama

Fukuda

2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

This paper presents a problem of odor source localization in a dynamic environment, which means the odor distribution is changing over time. Odor source localization is an interesting application in dynamic problems. Modified Particle Swarm Optimization is a well-known algorithm, which can continuously track a changing optimum over time. PSO can be improved or adapted by incorporating the change detection and responding mechanisms for solving dynamic problems. Charged PSO which is another extension of the PSO has also been applied to solve dynamic problems. We will adopt two types of modified concepts of PSO for a new algorithm in order to control autonomous vehicles in more realistic environment where a speed limitation of the robot behavior and collision avoidance mechanism should be taken into consideration as well as the effect of noise and threshold value for the odor sensor response, also positioning error of GPS sensor of robot. Simulations illustrate that the new approach can solve such dynamic problems in Advection-Diffusion odor model environment.

show abstract

Section: Motivationmentioning

confidence: 99%

A Mobile Robots PSO-based for Odor Source Localization in Dynamic Advection-Diffusion Environment

Jatmiko

Sekiyama

Fukuda

2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

show abstract

“…One is to observe the power level of specific tones in the received RF spectrum of base-band signal 1,5,6,7 . The other is to evaluate the DOP of optical signal in the fiber link 2,3,4,8,9,10 .…”

Section: The Experimental Setupmentioning

confidence: 99%

Adaptive PMD compensation up to second-order in 40Gb/s OTDM optical communication system using two-stage compensator

Zhang

et al. 2005

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

In this paper we report a successful experiment of adaptive polarization mode dispersion (PMD) compensation up to second-order in a 40Gb/s optical time-division multiplexed (OTDM) communication system by using two-stage compensator. In the experiment the PMD monitoring technique based on degree of polarization (DOP) was adopted. And the Particle Swarm Optimization (PSO) algorithm was introduced in adaptive PMD compensation, with the desirable features of fast convergence to the global optimum point for compensation without being trapped in local sub-optima and with good robustness to noise. The comparison was made to estimate the performance effectiveness between PSO algorithms with global neighborhood structure (GPSO) and with local neighborhood structure (LPSO). The LPSO algorithm is shown to be more effective to search global optimum for PMD compensation than GPSO algorithm. The ability of tracking changed PMD using PSO algorithm was also investigated. The two-stage PMD compensator is shown to be effective for both first-and second-order PMD, and the compensator is shown to be bit rate independent. The compensation time is within several hundreds of milliseconds. The response time for recovery from a sharp disturbance is about 11ms.

show abstract

“…PMD compensation has become one of hot topics in recent years [1][2][3][4][5][6][7][8][9] . An ordinary automatic PMD compensator can be divided into three important subparts: the PMD monitoring unit, the compensation unit and the control algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Two main kinds of PMD monitoring techniques are usually adopted in various feedback schemes for automatic PMD compensation. One is called electrical spectral hole burning [1][2]5 , in which the feedback signal is the power level of specific tones in the received RF spectrum of the base-band signal. The other is called degree of polarization (DOP) 3,4,6,7 , in which the feedback signal is evaluation for DOP of the optical signal in the fiber link.…”

Section: Introductionmentioning

confidence: 99%

“…The DOP ellipsoid obtained by using a polarization scrambler can determine both the DGD and PSP orientation by its three radii and the orientation angle of ellipsoid 7 . We have introduced the particle swarm optimization (PSO) into automatic PMD compensation as the feedback control algorithm 5,6,8,9 . In this paper we use the PSO technique as a powerful data fitting algorithm for getting a precise analytical DOP ellipsoid equation from limited number of measured SOP samples with fast speed, and getting real-time PMD features such as DGD and PSP.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

PMD monitoring with PSO-based DOP ellipsoid

Zhang

Duan

et al. 2005

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

The polarization mode dispersion (PMD) monitoring system is the key integral part of an adaptive PMD compensator. The degree of polarization (DOP) ellipsoid obtained by using a polarization scrambler can be used as either a feedback or feedforward monitoring signal for automatic polarization mode dispersion compensation. Generally, more than several thousands of sampling data of states of polarization (SOP) must be collected to insure getting a correct DOP ellipsoid. This would result in an unacceptable time consuming for adaptive PMD compensation. In this paper, for the first time, we introduce the particle swarm optimization (PSO) algorithm in determining the real-time DOP ellipsoid with high precision, requiring only 100 sampling data of SOPs. Experimental results confirm that the PSO algorithm is effective for ellipsoid data fitting with high precision within 250ms using our hardware environment.

show abstract

An Experiment of Adaptive PMD Compensation in 10 Gbit/s RZ Optical Communication System using PSO Algorithm

Cited by 4 publications

References 9 publications

A Mobile Robots PSO-based for Odor Source Localization in Dynamic Advection-Diffusion Environment

A Mobile Robots PSO-based for Odor Source Localization in Dynamic Advection-Diffusion Environment

Adaptive PMD compensation up to second-order in 40Gb/s OTDM optical communication system using two-stage compensator

PMD monitoring with PSO-based DOP ellipsoid

Contact Info

Product

Resources

About