HashBeam: Enabling Feedback Through Downlink Beamforming in Unsourced Random Access

TL;DR

HashBeam introduces a novel downlink beamforming method for unsourced random access that enables feedback to active users without knowing their identities, using channel gains and message hashes as proxies.

Contribution

The paper proposes HashBeam, a new feedback scheme for URA that leverages channel gains and message hashes, expanding the design space for reliable communication.

Findings

Number of channel uses is linear in the number of users

Scheme is adaptable to any number of antennas

Uses channel gains and hashes as proxies for user identities

Abstract

Unsourced random access (URA) has emerged as a candidate paradigm for massive machine-type communication (MTC) in next-generation wireless networks. While many excellent uplink schemes have been developed for URA, these schemes do not specify a mechanism for providing feedback regarding whether a user's message was successfully decoded. While this may be acceptable in some MTC scenarios, the lack of feedback is inadequate for applications that demand a high level of reliability. However, the problem of providing feedback to active users is complicated by the fact that the base station does not know the identities of the active users. In this paper, a novel downlink beamforming scheme called HashBeam is presented that enables the base station to provide feedback to the active users within URA, despite not knowing their identities. The key idea of this scheme is that the users' channels and hashes of their messages may be used as proxies for their true identities. The proposed scheme may be adapted to any number of antennas at the base station and it is shown that the required number of channel uses is linear in the number of users to acknowledge. The idea of using channel gains in conjunction with user hashes as discriminating attributes of active users is novel and expands the design space of URA schemes.