In this paper, a metric function for Gibbs sampling multiple-input multiple-output (MIMO) detection is proposed. In conventional Gibbs sampling MIMO detection, an exponential function is used in the calculation of a metric for the selection of candidate symbols. However, the exponential function can be implemented by a look-up table and may require a large amount of memory. This paper proposes a metric function based on a simple fraction. The proposed metric substitutes the exponential function though it increases the number of multiplication operations. It is shown by numerical results obtained through computer simulation that the proposed metric function improves the performance under a high signal-to-noise ratio condition in a large scale MIMO system since its curve is close to that of the exponential function when an input metric distance approaches to zero.


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    Title :

    Low Complexity Metric Function for Gibbs Sampling MIMO Detection


    Contributors:


    Publication date :

    2018-08-01


    Size :

    263954 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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