Best-First Tree Search with Probabilistic Node Ordering for MIMO Detection: Generalization and Performance-Complexity Tradeoff

Abstract

Abstract-The tree representation of the multiple-input multiple-output (MIMO) detection problem is illuminating for the development, interpretation, and classification of various detection methods. Best-first detection based on Dijkstra's algorithm pursues tree search according to a sorted list of tree nodes. In the first part of the paper, a new probabilistic sorting scheme is developed and incorporated in a modified Dijkstra's algorithm for MIMO detection. The proposed sorting exploits the statistics of the problem and yields effective tree exploration and truncation in the proposed algorithm. The second part of the paper generalizes the results in the first part and removes some limitations. A generalized Dijkstra's algorithm is developed as a unified tree-search detection framework. The proposed framework incorporates a parameter triplet that allow the configuration of the memory usage, detection complexity, and sorting dynamic associated with the tree-search algorithm. By tuning different parameters, desired performance-complexity tradeoffs are attained and a fixed-complexity version can be produced. Simulation results and analytical discussions demonstrate that the proposed generalized Dijkstra's algorithm shows abilities to achieve highly favorable performance-complexity tradeoffs.Index Terms-Maximum likelihood (ML) decoding, multipleinput multiple-output (MIMO) systems, tree-search detection, Dijkstra's algorithm.

A FFT-Like MIMO Detection Algorithm

“…The second type is the MIMO detection algorithm based on the sphere decoding (i.e., the tree graph model). Similarly, in order to get the results within an acceptable length of time, we choose a version which uses Dijkstra's algorithm and keeps only the best K for each processing [7] [8]. The third type is the proposed clique based MIMO detection algorithm (i.e., the clique graph model).…”

“…Among them, there are two strategies that are widely accepted. The first is the best-K strategy [6], that is, after each processing, only the best K items are retained for the next round; the second is to apply Dijkstra's algorithm to search for the solution [7] [8].…”

Artificial-intelligence-based heuristic searching tools and knowledge representation to solve cryptography problems, puzzles, vehicle detection and path finding

“…This proposed approach produces good signal-tonoise ratio (SNR) values. Chang and Chung (2012) proposed a method for detecting multiple-input multipleoutput (MIMO) based problems. This method works with a new probabilistic sorting scheme and it is coordinated with a modified Dijkstra's algorithm for identifying MIMO.…”

A low complexity detection for the binary MIMO system using Lagrange multipliers

“…However, in MIMO systems, these detectors suffer from inferior performance compared to the maximum-likelihood detector (MLD) and lose diversity due to their sensitivity to illconditioned channel matrices. In recent years, to bridge the performance gap between the low complexity detectors (LDs) and the MLD, several relaxation algorithms and heuristic algorithms such as local neighborhood search algorithms [9]- [11]; tree search algorithms [12] [13], etc, have also been proposed for MIMO systems.…”