The need for an internet connection is growing globally. So, day-by-day people needrnmuch higher data rate connection to meet their need but every physical resource in communicationrnlike frequency band, transmit signal strength are ï¬nite. Within the givenrnlimited resource, higher data speed is accomplished by a new technology called massivernMultiple Input Multiple Output (massive MIMO) system. Massive MIMO fulï¬lls the highrndata rate requirement through antenna diversity gain.rnReceived signal in massive MIMO system is usually distorted by different channel effectsrn(noise, interference, fading). In order to recover the transmitted signal correctly, channelrneffect must be estimated and repaired at the receiver accordingly. This is done by usingrndifferent channel estimation techniques. But which one of the channel estimators shouldrnbe used for a speciï¬c situation is another problem. This thesis will analyze the performancernof different pilot based channel estimation techniques speciï¬cally the least squarern(LS) and minimum mean square error channel (MMSE) estimation methods for massivernMIMO systems and based on the analysis results different discussions and conclusionsrnare made. Furthermore, comparison among their characteristics is simulated in MATLABrnand useful conclusions are given. To achieve this goal different scientiï¬c articles andrnMATLAB simulation results will be used.rnWhen the performance of the channel estimators was tested using the maximum ratiorncombining (MRC) detection algorithms, the result showed that the MMSE estimator performedrnbetter. Different comparison techniques were also run and they showed that thernMMSE estimator was affected more than the LS estimator by the increase in the numberrnof users while the increase in the number of antennas has almost the same effect on bothrnestimators. The paper also gave possible future works in massive MIMO systems thatrncontinue from this work.