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Focusing on high order multiple-input multiple-output (MIMO) systems, this paper presents an orthogonal grouping-based near optimal detection algorithm (OGNO). Compared to existing detection algorithms, the proposed algorithm provides a new viewpoint of reducing the receiver detection complexity in high order MIMO systems. With the proper parameters, the OGNO can achieve the almost same performance as the optimal maximum likelihood detection (MLD) algorithm but much lower complexity. Meanwhile, the fixed computational complexity offers a practical real-time hardware implementation. The advantage of complexity reduction comes from the orthogonal grouping, which can convert a higher order MIMO system into several lower order MIMO systems, where each subsystem can also be viewed a group. These groups perform detection separately. Due to more than one candidate sequence output from each group, the overall optimal sequence is obtained through ranking combination static group search. The bit error performance evaluation of the proposed algorithm is given by computer simulation and its complexity is evaluated by measuring the total number of floating-point operations (flops). Furthermore, it will be implemented into our real-time FGPA 8Ã8 MIMO-OFDM test-bed and the results from RF experiments will be given in the future.