MIMO Channel Matrix Condition Number Estimation and Threshold Selection for Combined K-Best Sphere Decoders
Author:
Affiliation:
1. Instituto de Telecomunicaciones y Aplicaciones Multimedia (iTEAM), Universidad Politecnica de Valencia
2. Departmento de Sistemas Informaticos y Computacion (DSIC), Universidad Politecnica de Valencia
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Software
Link
https://www.jstage.jst.go.jp/article/transcom/E92.B/4/E92.B_4_1380/_pdf
Reference8 articles.
1. [1] I. Berenguer and X. Wang, “Space-Time coding and signal processing for MIMO communications, ” J. Computer Science and Technology, vol.18, no.6, pp.689-702, Nov. 2003.
2. [2] Z. Guo and P. Nilsson, “Algorithm and implementation of the K-Best Sphere Decoding for MIMO detection, ” IEEE J. Sel. Areas Commun., vol.24, no.3, pp.491-503, March 2006.
3. [3] M. Shabany, K. Su, and P.G. Gulak, “A pipelined scalable high-throughput implementation of a Near-ML K-Best complex lattice decoder, ” IEEE International Conference on Audio, Speech and Signal Processing (ICASSP 2008), Las Vegas, Nevada, USA, April 2008.
4. [4] H. Artes, D. Seethaler, and F. Hlawatsch, “Efficient detection algorithms for MIMO channels: A geometrical approach to approximate ML detection, ” IEEE Trans. Signal Process., vol.51, no.11, pp.2808-2820, Nov. 2003.
5. [5] J. Maurer, G. Matz, and D. Seethaler, “Low-complexity and full-diversity MIMO detection based on condition number thresholding, ” IEEE International Conference on Audio, Speech and Signal Processing (ICASSP 2007), Honolulu, Hawaii, USA, April 2007.
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