Orthogonal frequency division multiplexing (OFDM) is an emerging technique for high data rate wireless communication systems over frequency selective channels and can be considered as one of the most promising techniques for future wireless system. However, it is well known that OFDM-based systems are sensitive to the inter-carrier interference (ICI) generated by a carrier frequency offset (CFO), which degrades the error probability performance for both single-antenna OFDM systems. Moreover, in a multipath fading environment, performances of OFDM system in a wireless channel are severely degraded by random variations in the amplitude of the received signals as well as by the presence of inter-symbol interference (ISI) and inter-carrier-interference (ICI) which also limit the OFDM system performance. Recently, Alamouti STBC has gained much attention as an effective transmit diversity scheme to provide reliable transmission with high peak data rates to increase the capacity of wireless communication system. In this research work, an advanced method for STBC-OFDM is proposed. The advancements which is done to the existing method is remapping of complex data after STBC encoding and serial to parallel conversion of complex data. This modification actually doubles the length of the data. At the receiver end again demapping of data is done which halfs the data length. This procedure helps in reduction of chances of error in the signal. The main objective of proposed method is to reduced the BER and SER in STBC-OFDM system. For each simulation, blocks of 1024 symbols are simulated. The proposed system is simulated with two transmitter antennas, two receiver antennas. We have used channel conditions, which have two independent paths with path delays in seconds and average path gains = [0 - 20] dB. The performance of the proposed method is compared with that of existing STBC-OFDM system using BER and SER. MATLAB R2013 has been used as an implementation platform to simulate the proposed method. Wireless communication toolbox and generalized MATLAB toolbox is used for the same.