Achieving Maximum Throughput in Random Access Protocols with Multipacket Reception

Bae, Yun Han; Choi, Bong Dae; Alfa, Attahiru Sule

doi:10.1109/tmc.2012.254

Cited by 35 publications

(37 citation statements)

References 18 publications

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“…make retransmissions impractical or costly at best. As a result, rather than treating collisions as losses, modern proposals of grant-free random access protocols have evolved towards the use of more sophisticated forward error correction techniques, often referred to as multipacket reception (MPR) [5]- [10].…”

Section: Introductionmentioning

confidence: 99%

Neural Network Aided Decoding for Physical-Layer Network Coding Random Access

Pastore¹,

Kerret²,

Navarro³

et al. 2018

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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Hinging on ideas from physical-layer network coding, some promising proposals of coded random access systems seek to improve system performance (while preserving low complexity) by means of packet repetitions and decoding of linear combinations of colliding packets, whenever the decoding of individual packets fails. The resulting linear combinations are then temporarily stored in the hope of gathering enough linearly independent combinations so as to eventually recover all individual packets through the resolution of a linear system at the end of the contention frame. However, it is unclear which among the numerous linear combinations-whose number grows exponentially with the degree of collision-will have low probability of decoding error. Since no analytical framework exists to determine which combinations are easiest to decode, this makes the case for a machine learning algorithm to assist the receiver in deciding which linear combinations to target. For this purpose, we train neural networks that approximate the error probability for every possible linear combination based on the estimated channel gains and demonstrate the effectiveness of our approach by numerical simulations.

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Section: Introductionmentioning

confidence: 99%

Neural Network Aided Decoding for Physical-Layer Network Coding Random Access

Pastore¹,

Kerret²,

Navarro³

et al. 2018

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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“…In [17], a stop theory based RTS/CTS scheme was proposed to reduce the overhead of the RTS contention in MPR-aided systems. The authors of [18] proposed a flexible CSMA algorithm that adjusted the transmission probability according to the estimated number of active users for the non-saturation MPR-aided RF system. Relying on the zeroforcing based SIC (ZF-SIC) algorithm, the authors of [19] proposed an analytical model to characterize the saturation throughput and mean access delay of CSMA/CA-aided RF networks.…”

Section: Introductionmentioning

confidence: 99%

Optimal ALOHA-Like Random Access With Heterogeneous QoS Guarantees for Multi-Packet Reception Aided Visible Light Communications

Zhao

Chi

Yang

2016

IEEE Trans. Wireless Commun.

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There is a paucity of random access protocols designed for alleviating collisions in visible light communication (VLC) systems, where carrier sensing is hard to be achieved due to the directionality of light. To resolve the problem of collisions, we adopt the successive interference cancellation (SIC) algorithm to enable the coordinator to simultaneously communicate with multiple devices, which is referred to as the multipacket reception (MPR) capability. However, the MPR capability could be fully utilized only when random access algorithms are properly designed. Considering the characteristics of the SIC aided random access VLC system, we propose a novel effective capacity (EC)-based ALOHA-like distributed random access algorithm for MPR-aided uplink VLC systems having heterogeneous quality-of-service (QoS) guarantees. Firstly, we model the VLC network as a conflict graph and derive the EC for each device. Then, we formulate the VLC QoS-guaranteed random access problem as a saturation throughput maximization problem subject to multiple statistical QoS constraints. Finally, the resultant non-concave optimization problem (OP) is solved by a memetic search algorithm relying on invasive weed optimization and differential evolution (IWO-DE). We demonstrate that our derived EC expression matches the Monte Carlo simulation results accurately, and the performance of our proposed algorithms is competitive. Index Terms-Visible light communication (VLC), multipacket reception (MPR), random access, heterogeneous QoS, effective capacity (EC), saturation throughput maximization.Linlin Zhao received her B.Eng. and M.S. degrees from the

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“…Ref. [24] derived the optimal transmission probability maximizing a system throughput for both slotted-Aloha and slotted CSMA protocols with MPR. Based on the results of the optimal transmission probability, they developed a simple distributed algorithm for estimating the number of active nodes.…”

Section: Introductionmentioning

confidence: 99%