Quadrature NOMA-ALOHA: Throughput Bounds

This letter studies cross-layer physical (PHY) and medium access control (MAC) contention-based random access for uplink non-orthogonal multiple access assisted by slotted ALOHA (NOMA-ALOHA). In addition, an improved NOMA-ALOHA is proposed by exploiting signal space diversity using π/4-rotated M-ary amplitude shift keying (MASK) with coordinate interleaving (CI), known as quadrature NOMA-ALOHA (QNOMA-ALOHA). In QNOMA-ALOHA, the PHY layer creates a new transmission resource based on two quadrature carriers (cosine and sine) and generates a virtual subslot in the MAC layer. The throughput bounds of QNOMA-ALOHA are derived based on the Poisson model. The numerical results show that the improved NOMA-ALOHA with QNOMA in the PHY layer significantly outperforms the existing NOMA-ALOHA in terms of throughput. The improvement of QNOMA-ALOHA is two times the square root of the power level to slotted ALOHA and two times to NOMA-ALOHA.

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Journal
IEEE Wireless Communications Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lwc.2025.3589461
Primary Topic
Brain Tumor Detection and Classification
Type
article
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article

Quadrature NOMA-ALOHA: Throughput Bounds

I Nyoman Apraz Ramatryana, Gandeva Bayu Satrya, Adel Ben Mnaouer, Gelar Budiman et al.
1 links
IEEE Wireless Communications Letters
Brain Tumor Detection and Classification
article

Quadrature NOMA-ALOHA: Throughput Bounds

I Nyoman Apraz Ramatryana, Gandeva Bayu Satrya, Adel Ben Mnaouer, Gelar Budiman, Khoirul Anwar, Sobia Jangsher
article en

Abstract

This letter studies cross-layer physical (PHY) and medium access control (MAC) contention-based random access for uplink non-orthogonal multiple access assisted by slotted ALOHA (NOMA-ALOHA). In addition, an improved NOMA-ALOHA is proposed by exploiting signal space diversity using π/4-rotated M-ary amplitude shift keying (MASK) with coordinate interleaving (CI), known as quadrature NOMA-ALOHA (QNOMA-ALOHA). In QNOMA-ALOHA, the PHY layer creates a new transmission resource based on two quadrature carriers (cosine and sine) and generates a virtual subslot in the MAC layer. The throughput bounds of QNOMA-ALOHA are derived based on the Poisson model. The numerical results show that the improved NOMA-ALOHA with QNOMA in the PHY layer significantly outperforms the existing NOMA-ALOHA in terms of throughput. The improvement of QNOMA-ALOHA is two times the square root of the power level to slotted ALOHA and two times to NOMA-ALOHA.

IEEE Wireless Communications Letters
Al Ain University (AE), Canadian University of Dubai (AE), Dublin City University (IE), Telkom University (ID)
Openalex Percentile: Top 78%
Brain Tumor Detection and Classification
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