Abstract
This paper describes a novel low complexity scalable multiple-input multiple-output (MIMO) detector that does not require preprocessing and the optimal squared l 2-norm computations to achieve good bit error (BER) performance. Unlike existing detectors such as Flexsphere that use preprocessing before MIMO detection to improve performance, the proposed detector instead performs multiple search passes, where each search pass detects the transmit stream with a different permuted detection order. In addition, to reduce the number of multipliers required in the design, we use l 1-norm in place of the optimal squared l 2-norm. To ameliorate the BER performance loss due to l 1-norm, we propose squaring then scaling the l 1-norm. By changing the number of parallel search passes and using norm scaling, we show that this design achieves comparable performance to Flexsphere with reduced resource requirement or achieves BER performance close to exhaustive search with increased resource requirement.
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The work of the Rice University authors was supported in part by the National Science Foundation under grants EECS-0925942 and CNS-0923479.
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Wu, M., Dick, C., Sun, Y. et al. Low complexity scalable MIMO sphere detection through antenna detection reordering. Analog Integr Circ Sig Process 73, 463–472 (2012). https://doi.org/10.1007/s10470-012-9894-8
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DOI: https://doi.org/10.1007/s10470-012-9894-8