{'fraction_non_alphanumeric': 0.017902813299232736, 'fraction_numerical': 0.0008525149190110827, 'mean_word_length': 5.278074866310161, '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 Generalized Framework to Find Optimal Almost Blank Subframe Density in Any Wireless Network

With advancements in mobile communications and technologies, Almost Blank Subframe (ABS) has found a lot of applications. It has been applied in heterogeneous networks to optimize various performance metrics, in LTE Licensed Assisted Access (LTE-LAA) for harmonious coexistence of LTE with WiFi in unlicensed spectrum, in enabling D2D communication in licensed spectrum, and so on. In any scenario, optimizing ABS density is very important in order to maximize the resource utilization, and hence other performance metrics. In this paper, we propose a generalized framework to find optimal ABS density that can be applied in any wireless network and application which balances the shortage and under-utilization of resources at various entities. To the best of our knowledge there does not exist such a framework which can be applied across various wireless networks and applications. We also propose models to apply our framework in heterogeneous networks and LTE-LAA. Through extensive simulations we show that the results obtained using our framework is the optimal solution.