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

There is a paucity of random access protocols designed for alleviating collisions in visible light communication (VLC) systems, where carrier sensing is hard to achieve due to the directionality of light. To resolve the problem of collisions, we adopt the successive interference cancellation (SIC) a...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2016-11, Vol.15 (11), p.7872-7884
Main Authors: Zhao, Linlin, Chi, Xuefen, Yang, Shaoshi
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Collisions
Delays
effective capacity (EC)
Evolutionary computation
heterogeneous QoS
Monte Carlo simulation
multi-packet reception (MPR)
Optical communication
Optimization
Quality of service
Quality of service architectures
Radio frequency
Random access
saturation throughput maximization
Search algorithms
Signal processing algorithms
Uplink
Visible light communication (VLC)
Wireless communication
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Summary:There is a paucity of random access protocols designed for alleviating collisions in visible light communication (VLC) systems, where carrier sensing is hard to achieve 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 multi-packet 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. First, 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 is solved by a memetic search algorithm relying on invasive weed optimization and differential evolution. We demonstrate that our derived EC expression matches the Monte Carlo simulation results accurately, and the performance of our proposed algorithms is competitive.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2016.2608956