TY - GEN

T1 - Low Complexity Metric Function for Gibbs Sampling MIMO Detection

AU - Kobayashi, Yutaro

AU - Sanada, Yukitoshi

PY - 2019/4/12

Y1 - 2019/4/12

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85064900218&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85064900218&partnerID=8YFLogxK

U2 - 10.1109/VTCFall.2018.8690983

DO - 10.1109/VTCFall.2018.8690983

M3 - Conference contribution

AN - SCOPUS:85064900218

T3 - IEEE Vehicular Technology Conference

BT - 2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 88th IEEE Vehicular Technology Conference, VTC-Fall 2018

Y2 - 27 August 2018 through 30 August 2018

ER -