Estimation of link-dependent parameters in optical transport networks from statistical models

Estimation of link-dependent parameters of optical transport networks is quite complex without the availability of complete network information. However, at the network planning stage these estimations are to be done with incomplete information, and need to be accurate. In this paper, we provide effective methods to estimate link-dependent parameters of optical transport networks when only partial information about the network is available. We use the link length statistical distribution model for these estimations. This approach is applied to 40 real transport networks and shown to be more accurate than the previously proposed methods. The improved accuracy of the proposed methods is achieved without extra network details: only the network node locations and the total number of links are needed.