A VLSI architecture of a K-best lattice decoding algorithm for MIMO channels

By K. Wong, Chi-Ying Tsui, R. Cheng, Wai Ho Mow. IEEE International Symposium on Circuits and Systems proceedings, 2002

420 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/6a170b3abb352613863393f5ce1d321697a7d5da

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Peter Nilsson
2. Lajos Hanzo
3. Christoph Studer
4. Zhan Guo
5. Shaoshi Yang

In Computer Networks and Communications

1. Lajos Hanzo
2. Shaoshi Yang
3. Chris Dick
4. Peter Nilsson
5. Christoph Studer
6. Zhan Guo
7. Guohui Wang
8. Neev Samuel

In Electrical and Electronic Engineering

1. Lajos Hanzo
2. Shaoshi Yang
3. Chris Dick
4. Peter Nilsson
5. Christoph Studer
6. Zhan Guo
7. Neev Samuel
8. Ami Wiesel

Citations in the corpus

• Algorithm and implementation of the K-best sphere decoding for MIMO detection (2006, methodology): “The drawback with the VLSI architecture of [12] is that the decoding throughput is limited to 10 Mb/s at a 100 MHz clock frequency.”
• Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs (2015, background): “There exist a number of other variants of the tree-search based MIMO detectors, which mainly fall into three categories: the depth-first tree-search detector [53], [54], [57]–[61], [80], [82], [319], the breadth-first tree-search detector [62]–[64], [320] and the best-first tree-search detector [68]”
• Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations (2014, background): “tion [13]–[15] or soft-output sphere decoding (SD) [16]–[18],”