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Hybrid tree search algorithms are described for maximum-likelihood symbol detection in spatial multiplexing (SM) systems. Essentially, the search tree is iteratively expanded in breadth-first (BF) manner until the probability that the current most likely path is correct exceeds the specified threshold, at which point, the depth-first (DF) stage is initiated to traverse the rest of the tree. In contrast with the sphere decoding (SD) algorithm, which starts off with the DF search, the proposed algorithms use the BF stage to enhance the accuracy of the initial DF search direction by exploiting the diversity inherent in the SM scheme. Simulation results demonstrate that, with a moderate increase in the memory requirement, the proposed algorithms achieve a significantly lower complexity than the SD algorithm in many scenarios.