2021
DOI: 10.1109/lcomm.2021.3049195
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Massive Random Access With Trellis-Based Codes and Random Signatures

Abstract: We investigate unsourced and grant-free massive random access in which all the users employ the same codebook, and the basestation is only interested in decoding the distinct messages sent. To resolve the colliding user packets, a novel approach relying on user transmissions with random-like amplitudes selected from a large number of possible signatures is proposed. The scheme is combined with convolutional coding for error correction. The receiver operates by first identifying the signatures used by the trans… Show more

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Cited by 13 publications
(1 citation statement)
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“…In [2], URA over a real-valued Gaussian multiple access channel (MAC) is studied, and a random coding achievability bound quantifying the required energy-per-bit for a given active user load is derived. Several practical transmission schemes are proposed to approach this bound based on dividing the transmission frame into slots [3], [4], coded compressed sensing [5], or spreading the channel-coded bits by random signatures [6], [7]. Furthermore, the on-off division multiple access (ODMA) [8] where a small fraction of the frame is utilized by each user is applied to the URA set-up in [9], [10], offering a promising performance with low complexity.…”
Section: Introductionmentioning
confidence: 99%
“…In [2], URA over a real-valued Gaussian multiple access channel (MAC) is studied, and a random coding achievability bound quantifying the required energy-per-bit for a given active user load is derived. Several practical transmission schemes are proposed to approach this bound based on dividing the transmission frame into slots [3], [4], coded compressed sensing [5], or spreading the channel-coded bits by random signatures [6], [7]. Furthermore, the on-off division multiple access (ODMA) [8] where a small fraction of the frame is utilized by each user is applied to the URA set-up in [9], [10], offering a promising performance with low complexity.…”
Section: Introductionmentioning
confidence: 99%