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The authors present a unified detection framework for spatial multiplexing Multiple-Input Multiple-Output (MIMO) systems by generalizing Heller's classical feedback decoding algorithm for convolutional codes. The resulting Generalized Feedback Detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established.
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