Minimal Overhead ARQ Sharing Strategies for URLLC in Multi-Hop Networks

Goel, Jaya; Harshan, J.

doi:10.1109/vtc2021-spring51267.2021.9448948

Cited by 5 publications

(6 citation statements)

References 8 publications

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“…Providing SPCs in multi-hop networks is promising to achieve the expansion of radio range while coping with the high delay of delivering heterogeneous services in 5G wireless networks. In [18], a cooperative automatic-repeatrequest sharing strategy for URLLC in multi-hop networks was studied, where the reliability communication was improved without compromising on the latency requirement. Recently, SPCs with WET were studied in multi-hop transmissions [19] and in dual-hop transmissions [20], where a deep neural network (DNN) was designed to evaluate the BLER performance.…”

Section: A Literature Surveymentioning

confidence: 99%

Short-Packet Communications in Multihop Networks With WET: Performance Analysis and Deep Learning-Aided Optimization

Nguyen

Costa

et al. 2023

IEEE Trans. Wireless Commun.

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In this paper, we study short-packet communications in multi-hop networks with wireless energy transfer, where relay nodes harvest energy from power beacons to transmit short packets to multiple destinations. It is proposed a novel cooperative beamforming relay selection (CRS) scheme which incorporates partial relay selection and distributed multiuser beamforming to achieve a high-reliable transmission in two consecutive hops. A closed-form expression for the average block error rate (BLER) of the CRS scheme is derived, based on which an asymptotic analysis is also carried out. To achieve optimal channel uses allocation, we formulate a fairness end-toend throughput maximization problem which is generally NPhard due to the non-concavity of the objective function and mixed-integer constraints. To solve this challenging problem efficiently, we first relax channel uses to be continuous and transform the relaxed problem into an equivalent non-convex one, but with a more tractable form. We then develop a lowcomplexity iterative algorithm relying on inner approximation framework to convexify non-convex parts that converges to at least a locally optimal solution. Towards real-time settings, we design an efficient deep convolutional neural network (CNN) with multiscale-accumulation connections to achieve the suboptimal solution of the relaxed problem via real-time inference processes. Numerical results are presented to verify the analytical derivations and to demonstrate performance improvements of the CRS scheme over the benchmark ones in terms of BLER, reliability, latency, and throughput in various settings. Moreover, the designed CNN provides the lowest root-mean-square error compared to the state-of-the-art deep learning approaches while the CNN-aided optimization framework estimates accurately the optimal channel uses allocation with low execution time.

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Section: A Literature Surveymentioning

confidence: 99%

Short-Packet Communications in Multihop Networks With WET: Performance Analysis and Deep Learning-Aided Optimization

Nguyen

Costa

et al. 2023

IEEE Trans. Wireless Commun.

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“…Thus, owing to increasing use-cases for achieving high-reliability and low-latency in multi-hop networks, the problem of designing efficient, reliable and importantly low-latency protocols, is of utmost importance in the context of nextgeneration networks. Some of the notable contributions in this field hitherto include [7], [8], [9], [15] and [16]. Among them, [16] attempted to jointly accomplish high-reliability along with low-latency feature by proposing ARQ based Decode and Forward (DF) strategies [14].…”

Section: Novelty Of Our Workmentioning

confidence: 99%

“…None of these contributions address the optimal allocation of ARQs when the total number of ARQs is constrained. A preliminary version of this work is in [15], wherein the SC strategy is proposed. In addition to the contents of [15], this work applies the cluster based ideas on the SC strategy.…”

Section: Novelty Of Our Workmentioning

confidence: 99%

“…A preliminary version of this work is in [15], wherein the SC strategy is proposed. In addition to the contents of [15], this work applies the cluster based ideas on the SC strategy.…”

Section: Novelty Of Our Workmentioning

confidence: 99%

“…Example use-cases include autonomous V2X communication, in which strict deadlines are imposed on Parts of this work were presented at IEEE Vehicular Technology Conference (VTC2021)-Spring in April 2021 [15].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

One-Hop Listening Based ARQs for Low-Latency Communication in Multi-Hop Networks

Goel¹,

Harshan²

2022

Preprint

Self Cite

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Inspired by emerging applications in vehicular networks, we address the problem of achieving high-reliability and low-latency communication in multi-hop wireless networks. We propose a new family of Automatic-Repeat-Requests (ARQs) based cooperative strategies wherein high end-to-end reliability is obtained using packet retransmissions at each hop while the low-latency constraint is met by imposing an upper bound on the total number of packet retransmissions across the network. A hallmark of our strategies is the one-hop listening capability wherein nodes utilize the unused ARQs of their preceding node just by counting the number of failed attempts due to decoding errors. We further extend the idea of one-hop listening to multi-hop listening, wherein a set of consecutive nodes form clusters to utilize the unused ARQs of the preceding nodes, beyond its nearest neighbour, to further improve reliability. Thus, our strategies provide the high-reliability feature with no compromise in the original latency-constraint. For the proposed strategies, we solve non-linear optimization problems on distributing the ARQs across the nodes so as to minimize packet drop probability (PDP) subject to a total number of ARQs in the network. Through extensive theoretical results on PDP and delay profiles, we show that the proposed strategies outperform the best-known strategies in this space.

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Feedback Aggregation Based Retransmission Scheme for Multi-Hop Wireless Networks

Liu

Zhou

et al. 2023

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)

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Minimal Overhead ARQ Sharing Strategies for URLLC in Multi-Hop Networks

Cited by 5 publications

References 8 publications

Short-Packet Communications in Multihop Networks With WET: Performance Analysis and Deep Learning-Aided Optimization

Short-Packet Communications in Multihop Networks With WET: Performance Analysis and Deep Learning-Aided Optimization

One-Hop Listening Based ARQs for Low-Latency Communication in Multi-Hop Networks

Feedback Aggregation Based Retransmission Scheme for Multi-Hop Wireless Networks

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