User Activity Detection for Irregular Repetition Slotted Aloha Based MMTC

Ramesh, Srivatsa, Chirag; Murthy, Chandra R.

doi:10.1109/tsp.2022.3185891

Cited by 7 publications

(2 citation statements)

References 31 publications

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“…In [6] [7], the slotted ALOHA protocol is applied to the MTC. The technique of spread spectrum has been combined to the ALOHA protocol [8] to deal with the collision problem, where the price is the increased bandwidth.…”

Section: Introductionmentioning

confidence: 99%

An Uplink Random Access Scheme Based on ALOHA System Assisted by Gain Division Multiple Access

Lin

Yang²,

Chang

et al. 2023

IEEE Access

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Gain division multiple access (GDMA) is a non-orthogonal multiple access (NOMA) technique for uplink communications. In GDMA, the receiver employs both the magnitudes and phases of channel gains associated to the users to separate users. In the power-domain NOMA, the receiver employs the power levels associated to users to separate users. We apply the GDMA concept together with orthogonal frequency division multiple access (OFDM) to combat the collision problem in the ALOHA system. Our goal is to minimize the complexity of the devices (users) required for coordination and to obtain high throughput simultaneously in the random access protocol. For the proposed unslotted OFDM-GDMA-ALOHA, each user randomly chooses a Zadoff-Chu (ZC) sequence as its preamble for the transmitted packet so that the receiver can simultaneously obtain the information for timing and the information for coarse channel estimation. Moreover, fine channel estimation is obtained by using a cluster-based method. Simulation for a coded unslotted OFDM-GDMA-ALOHA system with BPSK modulation demonstrates that the obtained throughput performance can be better than that obtained by the slotted ALOHA system without using GDMA. We also provide simulation for slotted OFDM-GDMA-ALOHA, which shows that very high throughput can be achieved if the synchronization of slots can be obtained.INDEX TERMS gain devision multiple access (GDMA), non-orthogonal multiple access (NOMA), ALOHA, cluster-based channel estimation.

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Section: Introductionmentioning

confidence: 99%

An Uplink Random Access Scheme Based on ALOHA System Assisted by Gain Division Multiple Access

Lin

Yang²,

Chang

et al. 2023

IEEE Access

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“…In [3], the authors derived an optimal transmission probability distribution for IRSA with a reception capability K = 2, which can make the IRSA protocol achieve a higher load threshold. In [4], the authors proposed a Bayesian algorithm to detect the active users for IRSA, in which both the sparsity in user activity and the underlying structure are jointly considered. For the IoTs, Chen et.…”

Section: Introductionmentioning

confidence: 99%

DS-IRSA: A Deep Reinforcement Learning and Sensing Based IRSA

Hmedoush,

Gu,

Adjih

et al. 2023

GLOBECOM 2023 - 2023 IEEE Global Communications Conference

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One of the main difficulties to enable the future scaling of IoT networks is the issue of massive connectivity. Recently, Modern Random Access protocols have emerged as a promising solution to provide massive connections for IoT. One main protocol of this family is Irregular Repetition Slotted Aloha (IRSA), which can asymptotically reach the optimal throughput of 1 packet/slot. Despite this, the problem is not yet solved due to lower throughput in non-asymptotic cases with smaller frame sizes. In this paper, we propose a new variant of IRSA protocol named Deep-Learning and Sensing-based IRSA (DS-IRSA) to optimise the performance of IRSA in short frame IoTs, where a sensing phase is added before the transmission phase and users' actions in both phases are managed by a deep reinforcement learning (DRL) method. Our goal is to learn to interact and ultimately to learn a sensing protocol entirely through Deep Learning. In this way, active users can coordinate well with each other and the throughput of the whole system can be well improved. Simulation results show that our proposed scheme convergence quickly towards the optimal performance of almost 1 packet/slot for small frame sizes and with enough minislots and can achieve higher throughput in almost all cases.

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Channel State Information Based User Censoring in Irregular Repetition Slotted Aloha

Srivatsa,

Murthy

2023

ICC 2023 - IEEE International Conference on Communications

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Irregular repetition slotted aloha (IRSA) is a massive random access protocol which can be used to serve a large number of users while achieving a packet loss rate (PLR) close to zero. However, if the number of users is too high, then the system is interference limited and the PLR is close to one. In this paper, we propose a variant of IRSA in the interference limited regime, namely Censored-IRSA (C-IRSA), wherein users with poor channel states censor themselves from transmitting their packets. We theoretically analyze the throughput performance of C-IRSA via density evolution. Using this, we derive closed-form expressions for the optimal choice of the censor threshold which maximizes the throughput while achieving zero PLR among uncensored users. Through extensive numerical simulations, we show that C-IRSA can achieve a 4× improvement in the peak throughput compared to conventional IRSA.

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User Activity Detection for Irregular Repetition Slotted Aloha Based MMTC

Cited by 7 publications

References 31 publications

An Uplink Random Access Scheme Based on ALOHA System Assisted by Gain Division Multiple Access

An Uplink Random Access Scheme Based on ALOHA System Assisted by Gain Division Multiple Access

DS-IRSA: A Deep Reinforcement Learning and Sensing Based IRSA

Channel State Information Based User Censoring in Irregular Repetition Slotted Aloha

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