Abstract
Hyper-cellular network (HCN) architecture was proposed based on the separation of traffic and control coverage. In this paper, we mainly focus on the decoupling structure for traffic and control coverage. We also provide the decoupling principle with accompanying conditions and examples. With this knowledge, we discuss two key problems in the control process. For channel estimation under partial measurement, based on channel correlation between the spatial and time domain, we propose two channel prediction methods. One method is using traffic base-stations (BSs) to periodically measure channels and make decisions. The other is online and offline learning-based channel prediction. As for the massive connectivity problems in control coverage, sparse coding multiple access is adopted as a grant-free access method to support massive connectivity, low latency, and high reliability for control coverage.
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