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User Activity Detection for Irregular Repetition Slotted Aloha Based MMTC

Srivatsa, CR and Murthy, CR (2022) User Activity Detection for Irregular Repetition Slotted Aloha Based MMTC. In: IEEE Transactions on Signal Processing, 70 . pp. 3616-3631.

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Official URL: https://doi.org/10.1109/TSP.2022.3185891


Irregular repetition slotted aloha (IRSA) is a grant-free random access protocol for massive machine-type communications, in which users transmit replicas of their packet in randomly selected resource blocks within a frame. In this paper, we first develop a novel Bayesian user activity detection (UAD) algorithm for IRSA, which exploits both the sparsity in user activity as well as the underlying structure of IRSA transmissions. Next, we derive the Cramér-Rao bound (CRB) on the mean squared error in channel estimation. We empirically show that the channel estimates obtained as a by-product of the proposed UAD algorithm achieves the CRB. Then, we analyze the signal to interference plus noise ratio achieved by the users, accounting for UAD, channel estimation errors, and pilot contamination. Finally, we illustrate the impact of these non-idealities on the throughput of IRSA via Monte Carlo simulations. For example, in a system with 1500 users and 10 of the users being active per frame, a pilot length of as low as 20 symbols is sufficient for accurate user activity detection. In contrast, using classical compressed sensing approaches for UAD would require a pilot length of about 346 symbols. Our results reveal crucial insights into dependence of UAD errors and throughput on parameters such as the length of the pilot sequence, the number of antennas at the BS, the number of users, and the signal to noise ratio. © 1991-2012 IEEE.

Item Type: Journal Article
Publication: IEEE Transactions on Signal Processing
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to the authors.
Keywords: Channel estimation; Errors; Intelligent systems; Mean square error; Monte Carlo methods; Signal processing; Throughput, Activity detection; Decoding; Grant-free random access; Irregular repetition slotted alohum; Machinetype communication (MTC); Massive machine-type communication; Random access; Signal processing algorithms; Slotted Aloha; Symbol; User activity; User activity detection, Signal to noise ratio
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Division of Interdisciplinary Sciences > Robert Bosch Centre for Cyber Physical Systems
Date Deposited: 29 Sep 2022 11:55
Last Modified: 29 Sep 2022 11:55
URI: https://eprints.iisc.ac.in/id/eprint/76849

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