The multiple input Multiple Output (MIMO) is a wireless technology that can offer high spectral efficiency, capacity gain and/or diversity gain. On the other hand, the Worldwide Interoperability for Microwave Access (WiMAX) is a promising wireless technology which delivers data at high rates covering larger area. To retrieve desired signals in such technologies, we need to incorporate appropriate Channel estimation and signal detection techniques at the receiver. Thus, in this paper we propose Scaled Least Square-Maximum Likelihood (SLS-ML) and Reduced Minimum Mean Square Error-ML (RMMSE-ML) receivers for MIMO system under WiMAX environment. The proposed techniques are consistently outperforming the exiting Least Square-Maximum Likelihood (LS-ML) and Minimum Mean Square Error-ML (MMSE-ML) receivers. The RMMSE and SLS techniques minimize channel estimation error and the Maximum Likelihood (ML) detector cancels residual interference from other transmitting antennas. In the simulation study, the Bit Error Rate (BER) performance evaluation of 2×2 and 4×4 antenna structures with different detector and channel estimator techniques over various Erceg's channel models has been discussed. The investigations show that the ML detection applied to the mobile WiMAX systems provide better performance than other detector systems, irrespective of the number of antenna array size and the fading effect.