Under the presumption that the encoders' perceptions are restrictively free Markov chains given an imperceptible time-invariant irregular variable, comes about on the structure of ideal ongoing encoding and translating capacities may receive. The issue with these channels and impeccable memory at the beneficiary is then considered. Another strategy to discover the structure of ideal ongoing encoders is utilized. An adequate measurement with a period invariant area is found in this issue. This technique misuses the vicinity of normal data between the encoders and the collector when correspondence is over quiet channels. In this paper, we have used the lower bound, upper bound and characterize the encoder. In the past configuration approach they took after Markov Chain way to deal with assessing the upper bound and characterize the encoder. But by using the lower bound and upper bound Markov and Poisson distribution can be seen as an estimate to the binomial appropriation. The close estimation is sufficient to be helpful when the specimen size (N) has been tolerably extensive (say N > 50 || N > 100) and the likelihood (p) is just moderately little (p < .2) The benefit of the Markov and Poisson appropriation, obviously, is that if N is substantial, you require just knowing p to focus the inexact dispersion of occasions. With the binomial dissemination you additionally need to know N.