Affiliation:
1. Department of Physics and Computer Science Wilfrid Laurier University Waterloo Ontario Canada
2. Department of Electrical and Computer Engineering Ryerson University Toronto Ontario Canada
3. Redline Communications Markham Ontario Canada
4. Department of Computer S Ryerson University Toronto Ontario Canada
Abstract
AbstractIndustrial Internet of Things (IIoT) deployment underlying cellular networks has been drawing increasing attention in recent years. In this work, we consider group based resource allocation for industrial IoT networks where cellular‐IoT (C‐IoT) devices support uplink transmission for multiple IoT groups/clusters. The joint group and subcarrier optimization problem is formulated for maximizing the cell/group throughput under the optimal group member selection, subcarrier and minimum data rate constraints. Depending on the interference information, the interference aware group allocation (IA‐GA) is proposed to find the cellular user and cellular‐IoT device grouping for each subcarrier. However, to achieve the maximizing the cell/group throughput, another iterative algorithm, namely genetic algorithm based group allocation (GA‐GA) method is proposed, which provides an optimal solution for the user grouping in the most of the cases where an iterative technique is used for the sub‐carrier allocation. Simulations results show that the proposed IA‐GA and GA‐GA methods provide enhanced cell throughput gain and accessibility of the C‐IoTs.
Funder
Natural Sciences and Engineering Research Council of Canada
Subject
Electrical and Electronic Engineering
Cited by
1 articles.
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1. An Energy-Efficient Downlink Resource Allocation In Cellular IoT H-CRANs;2023 2nd International Conference on Futuristic Technologies (INCOFT);2023-11-24