{'fraction_non_alphanumeric': 0.029567053854276663, 'fraction_numerical': 0.0, 'mean_word_length': 5.493150684931507, '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}}
Multi-Channel Estimation of Devices with Preamble Collision in Distributed MTC

In this paper, we consider distributed machine-type communication (MTC) where a number of remote radio heads (RRHs) are randomly deployed over an area for two-step random access. Unlike colocated multiple-input multiple-output (MIMO), although preamble collision happens, it is shown that the channel estimation of multiple devices associated with preamble collision can be carried out so that their data packets can be successfully decoded, which can result in an improved throughput. For multi-channel estimation, we propose an approach based on the distances between active devices and RRHs and use Gibbs sampling to estimate the distances. Simulation results confirm that reasonably high signal-to-interference-plus-noise ratio (SINR) of data signals transmitted from the devices experiencing preamble collision can be achieved thanks to multi-channel estimation.