Spatial multiplexing techniques and multifrequency cells for massive machine-type communications in future 6G networks

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Future 6G networks are envisioned to provide communication services to very dense infrastructures, where up to ten million devices per square kilometer could be deployed. With such a large number of devices, human intervention is not feasible and the entire communication process and management must be automated. Besides, while some applications will require enhanced broadband communications, other scenarios will be supported by channels with a limited bitrate. In this context, 6G verticals are designed to pack the required network resources for specific applications and isolate one scenario from the others, with each one providing the needed Quality-of-Service. Nevertheless, even in verticals fully prepared for massive communications, direct management of such an incredible number of devices is challenging (if not impossible) for base stations. There are, nevertheless, two scenarios where the management burden could be mitigated: when devices are slept for long periods and when devices transmit an extremely reduced bitrate. In this paper, we propose a solution for massive machine type communications for devices with an extremely reduced throughput. The proposed solution defines two levels of cells, the first level operating at native 6G frequencies, while the second one operating at high frequency (shortwave). Symbols and bit stream in the first-level cells are spatially multiplexed to cover second-level cells. In that way, hardware devices do not employ a full OFDM (Orthogonal frequency-division multiplexing) symbol, but only use one orthogonal subcarrier each. Coding and modulation at the interface between the two levels of cells are configured to make possible the access of all hardware devices to communication services. In order to validate the proposed technology, we describe our experimental evaluation based on a simulation scenario. The results show how the management workload is reduced more than ten times in 6G base stations thanks to our proposed solution.

​Future 6G networks are envisioned to provide communication services to very dense infrastructures, where up to ten million devices per square kilometer could be deployed. With such a large number of devices, human intervention is not feasible and the entire communication process and management must be automated. Besides, while some applications will require enhanced broadband communications, other scenarios will be supported by channels with a limited bitrate. In this context, 6G verticals are designed to pack the required network resources for specific applications and isolate one scenario from the others, with each one providing the needed Quality-of-Service. Nevertheless, even in verticals fully prepared for massive communications, direct management of such an incredible number of devices is challenging (if not impossible) for base stations. There are, nevertheless, two scenarios where the management burden could be mitigated: when devices are slept for long periods and when devices transmit an extremely reduced bitrate. In this paper, we propose a solution for massive machine type communications for devices with an extremely reduced throughput. The proposed solution defines two levels of cells, the first level operating at native 6G frequencies, while the second one operating at high frequency (shortwave). Symbols and bit stream in the first-level cells are spatially multiplexed to cover second-level cells. In that way, hardware devices do not employ a full OFDM (Orthogonal frequency-division multiplexing) symbol, but only use one orthogonal subcarrier each. Coding and modulation at the interface between the two levels of cells are configured to make possible the access of all hardware devices to communication services. In order to validate the proposed technology, we describe our experimental evaluation based on a simulation scenario. The results show how the management workload is reduced more than ten times in 6G base stations thanks to our proposed solution. Read More