{'fraction_non_alphanumeric': 0.01600985221674877, 'fraction_numerical': 0.0, 'mean_word_length': 5.889830508474576, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A novel detection strategy based on ant colony optimization for MIMO systems

This paper proposes two detection schemes based on a novel strategy associated with ant colony optimization (ACO) for multiple-input multiple-output (MIMO) systems. By employing heuristic values and pheromone levels, we jointly exploit local and global information about solution space to constitute transition probability. The proposed constitution rule evaluates the reliability of possible solution more efficiently than previous research. Besides, the unreliable solutions in terms of pheromone levels are deleted before each iteration for reducing the scale of solution space. Both simulations and analysis confirm that the proposed schemes provide improved tradeoff between complexity and performance over traditional detectors.