Environmental interference and physical defects in the communication medium can causernErrors during data transmission. Coding is a method of detecting and correcting these errors tornEnsure that information is transferred intact from its source to its destination.rnThe error detecting and correcting capability of a particular coding scheme is correlated withrnIts code rate and complexity. A high code rate means information content is high and codingrnOverhead is low. However, the fewer bits used for coding redundancy, the lesser errorrnProtection is provided. A tradeoff must be made between bandwidth availability and thernAmount of redundancy added for error protection.rnThere are many types of error correcting codes. Each code is distinguished by the method usedrnTo add redundancy and how much of this redundancy is added to the information going out ofrnThe transmitter.rnThe type of errors that tend to occur on the communication channel determines the choice ofrnThe coding scheme for error protection. A channel with burst errors will tend to have cluster ofrnBit errors that occur during one transmission and thus different from channels with randomrnErrors. The prime objective of this work is to compare burst error correcting capability ofrnCyclic and convolutional code on different channels.rnViiirnTo achieve the objective, (15,9) cyclic and (3,2,8) convolutional codes with burst length, l=3 ,rn(21,9) cyclic and (3,2,13) convolutional codes with burst length, l=6 and (21,3) cyclic andrn(3,2,18) convolutional codes with burst length, l=9 are selected .probability of error , p(e) isrnImportant parameter used to measure and compare the performance of the three selected codes