Adaptive Mixing Probability Scheme in Mixed Gibbs Sampling MIMO Signal Detection
Author:
Affiliation:
1. Dept. of Electronics and Electrical Engineering, Keio University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Software
Link
https://www.jstage.jst.go.jp/article/transcom/E106.B/12/E106.B_2023EBP3018/_pdf
Reference11 articles.
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2. [2] G.J. Foschini and W.J. Gans, “On limits of wireless communication in a fading enviroment when using multiple antennas,” Wireless Personal Communication, vol.6, no.3, pp.314-335, March 1998. 10.1023/a:1008889222784
3. [3] T. Datta, N.A. Kumar, A. Chockalingam, and B.S. Rajan, “A novel Monte-Carlo-sampling-based receiver for large-scale uplink multiuser MIMO systems,” IEEE Trans. Veh. Technol., vol.62, no.7, pp.3019-3038, Sept. 2013. 10.1109/tvt.2013.2260572
4. [4] B. Farhang-Boroujeny, H. Zhu, and Z. Shi, “Markov chain Monte Carlo algorithms for CDMA and MIMO communication systems,” IEEE Trans. Signal Process., vol.54, no.5, pp.1896-1909, May 2006. 10.1109/tsp.2006.872539
5. [5] Y. Sanada, “Gibbs sampling MIMO detection with maximum ratio combining,” 28rd IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications, Oct. 2017. 10.1109/pimrc.2017.8292198
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