Autonomous Power Decision for the Grant Free Access MUSA Scheme in the mMTC Scenario

Sensors

WissalBen Ameur¹  Philippe Mary¹  Jean-François Hélard¹  Marion Dumay²  Jean Schwoerer² 

[1] INSA Rennes, CNRS, IETR, University Rennes, 35000 Rennes, France;Orange Labs, 38240 Meylan, France;

关键词: non-orthogonal multiple access (NOMA);    multi-user shared access (MUSA);    successive interference cancellation (SIC);    grant free access;    bit error probability (BEP);    power allocation;   

DOI  :  10.3390/s21010116

来源: DOAJ

【 摘 要 】

Non-orthogonal multiple access schemes with grant free access have been recently highlighted as a prominent solution to meet the stringent requirements of massive machine-type communications (mMTCs). In particular, the multi-user shared access (MUSA) scheme has shown great potential to grant free access to the available resources. For the sake of simplicity, MUSA is generally conducted with the successive interference cancellation (SIC) receiver, which offers a low decoding complexity. However, this family of receivers requires sufficiently diversified received user powers in order to ensure the best performance and avoid the error propagation phenomenon. The power allocation has been considered as a complicated issue especially for a decentralized decision with a minimum signaling overhead. In this paper, we propose a novel algorithm for an autonomous power decision with a minimal overhead based on a tight approximation of the bit error probability (BEP) while considering the error propagation phenomenon. We investigate the efficiency of multi-armed bandit (MAB) approaches for this problem in two different reward scenarios: (i) in Scenario 1, each user reward only informs about whether its own packet was successfully transmitted or not; (ii) in Scenario 2, each user reward may carry information about the other interfering user packets. The performances of the proposed algorithm and the MAB techniques are compared in terms of the successful transmission rate. The simulation results prove that the MAB algorithms show a better performance in the second scenario compared to the first one. However, in both scenarios, the proposed algorithm outperforms the MAB techniques with a lower complexity at user equipment.

【 授权许可】

Unknown