Fixing the Complexity of the Sphere Decoder for MIMO Detection
By Luis G. Barbero, John S. Thompson. IEEE Transactions on Wireless Communications, 2008
490 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/99f6713ee3baef580761a3a192b74232d9ee37d7
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Erik G. Larsson
- Fredrik Tufvesson
- Ove Edfors
- Lajos Hanzo
- T. Marzetta
- Fredrik Rusek
- Shaoshi Yang
- Emil Björnson
In Electrical and Electronic Engineering
- Emil Björnson
- Erik G. Larsson
- Luca Sanguinetti
- T. Marzetta
- Fredrik Tufvesson
- Lajos Hanzo
- Rui Zhang
- Mohamed-Slim Alouini
Citations in the corpus
- Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays (2012, methodology): “For FCSD, we chooser = 8.”
- An Overview of Signal Processing Techniques for Terahertz Communications (2020, background): “Despite the fact that sequential processing in sphere decoding results in variable complexity and limits parallelism, several algorithmic and architectural optimizations have been proposed [250] to fix its complexity [251].”
- 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]”