Adding Exploration To Tree-Based Mimo Detectors Using Insights From Bio-Inspired Firefly Algorithm

The standard multiple-input multiple-output (MIMO) detectors exploit the available information to resolve the detection problem. Alternative algorithms, such as bio-inspired or geometrical detectors, mix exploitation with exploration to bypass local minima and enhance the results. This paper examines the benefits of adding exploration to the traditional tree-based detectors. For this purpose, a new interpretation of the bio-inspired detector based on the firefly algorithm (FA) is proposed. It is studied in a tree search paradigm and extended to soft-outputs. The findings suggest that the addition of a stochastic exploration to tree-based detectors significantly improves performance with a small computational overhead.