2020/10/28 by Jinho Choi, Jihong Park, Choi, Jinho +3
Computer Science · Engineering · #Age of Information Optimization #FOS: Computer and information sciences #Information Theory (cs.IT) #IoT Networks and Protocols #Wireless Body Area Networks
paper · pdf · doi:10.48550/arxiv.2010.14755
openalex publication_date 2020/10/28 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Improving the data rate of machine-type communication (MTC) is essential in\nsupporting emerging Internet of things (IoT) applications ranging from\nreal-time surveillance to edge machine learning. To this end, in this paper we\npropose a resource allocation approach for uplink transmissions within a random\naccess procedure in MTC by exploiting multichannel selection diversity, coined\nexplore-before-talk (EBT). Each user in EBT first sends pilot signals through\nmultiple channels that are initially allocated by a base station (BS) for\nexploration, and then the BS informs a subset of initially allocated channels\nthat are associated with high signal-to-noise ratios (SNRs) for data packet\ntransmission by the user while releasing the rest of the channels for other\nusers. Consequently, EBT exploits a multichannel selection diversity gain\nduring data packet transmission, at the cost of exploration during pilot\ntransmission. We optimize this exploration-exploitation trade-off, by deriving\nclosed-form mean data rate and resource outage probability expressions.\nNumerical results corroborate that EBT achieves a higher mean data rate while\nsatisfying the same outage constraint, compared to a conventional MTC protocol\nwithout exploration.\n