Likelihood-based tree search for low complexity detection in large MIMO systems
A recently reported result on large/massive multiple-input multiple-output (MIMO) detection
shows the utility of the branch and bound (BB)-based tree search approach for this problem …
shows the utility of the branch and bound (BB)-based tree search approach for this problem …
Sequential and global likelihood ascent search-based detection in large MIMO systems
AK Sah, AK Chaturvedi - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Neighborhood search algorithms have been proposed for low complexity detection in
large/massive multipleinput multiple-output systems. They iteratively search for the vector …
large/massive multipleinput multiple-output systems. They iteratively search for the vector …
Local search based near optimal low complexity detection for large MIMO System
M Chaudhary, NK Meena… - 2016 IEEE International …, 2016 - ieeexplore.ieee.org
This paper presents a low complexity detection technique with near Maximum Likelihood
(ML) performance for large multiple-input multiple-output (MIMO) systems. Large MIMO …
(ML) performance for large multiple-input multiple-output (MIMO) systems. Large MIMO …
Best-first tree search with probabilistic node ordering for MIMO detection: Generalization and performance-complexity tradeoff
The tree representation of the multiple-input multiple-output (MIMO) detection problem is
illuminating for the development, interpretation, and classification of various detection …
illuminating for the development, interpretation, and classification of various detection …
A* algorithm inspired memory-efficient detection for MIMO systems
Implementation of a best-first detection algorithm for multiple-input multiple-output (MIMO)
systems requires large amounts of memory especially in large systems with high-order …
systems requires large amounts of memory especially in large systems with high-order …
An unconstrained likelihood ascent based detection algorithm for large MIMO systems
AK Sah, AK Chaturvedi - IEEE Transactions on Wireless …, 2017 - ieeexplore.ieee.org
Neighborhood search algorithms have been proposed for detection in large multiple-input
multiple-output systems. They iteratively search for the best vector in a fixed neighborhood …
multiple-output systems. They iteratively search for the best vector in a fixed neighborhood …
Low-complexity adaptive tree search algorithm for MIMO detection
KC Lai, LW Lin - IEEE Transactions on Wireless …, 2009 - ieeexplore.ieee.org
In this paper, a reduced-complexity multiple-input multiple-output (MIMO) detector for the
spatial multiplexing systems is described. It incorporates the idea of Ungerboeck's set …
spatial multiplexing systems is described. It incorporates the idea of Ungerboeck's set …
Bit-level reduced neighborhood search for low-complexity detection in large MIMO systems
P Mann, AK Sah, R Budhiraja… - IEEE Wireless …, 2017 - ieeexplore.ieee.org
Neighborhood search algorithms (NSAs) reduce the detection complexity in a multiple-input
multiple-output (MIMO) system equipped with a large number of antennas. These algorithms …
multiple-output (MIMO) system equipped with a large number of antennas. These algorithms …
Beyond fixed neighborhood search in the likelihood ascent algorithm for MIMO systems
AK Sah, AK Chaturvedi - 2016 IEEE International Conference …, 2016 - ieeexplore.ieee.org
Neighborhood search algorithms have been proposed for detection in large/massive
multiple-input multiple-output (MIMO) systems. They iteratively search for the best vector in a …
multiple-input multiple-output (MIMO) systems. They iteratively search for the best vector in a …
A hybrid MMSE and K-Best detection scheme for MIMO systems
A new multiple-input multiple-output (MIMO) detection scheme combining minimum-mean-
square-error (MMSE) detection and the K-best detection algorithm is proposed. The …
square-error (MMSE) detection and the K-best detection algorithm is proposed. The …