A Deep Learning-based Receiver for Asynchronous Grant-Free Random Access in Control-to-Control Networks
In this paper, we study grant-free, asynchronous control-to-control (C2C) communications in an indoor scenario with a shared wireless channel. Each communication node transmits command units, each consisting of a variable-length low-density parity-check (LDPC)--coded payload preceded by a start sequence and followed by a tail sequence. Due to the asynchronous nature of the access, transmissions from different nodes are not aligned over time. As a result, each receiving controller observes the superposition of multiple command units transmitted by different nodes over a receiver-defined superframe interval. Each node transmits one or more replicas of the same command unit. We propose a rec...
| Authors | Massimo Battaglioni, Edoardo Carnevali, Dania De Crescenzo et al. |
|---|---|
| Primary category | cs.IT |
| Published | 12 May 2026 |
| Last updated at source | 12 May 2026 |
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