Distributed-Optimization-with-Centralized-Refining

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Distributed-Optimization-with-Centralized-Refining

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Simulation code of the paper: J. Bai and X. Wang “Distributed-Optimization with Centralized-Refining for Efficient Resource Allocation in Future Wireless Networks,” in IEEE Transactions on Communications, accepted, Mar. 2024.

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## Distributed-Optimization with Centralized-Refining for Efficient Resource Allocation in Future Wireless Networks
This is a code package related to the following paper:

J. Bai and X. Wang “Distributed-Optimization with Centralized-Refining for Efficient Resource Allocation in Future Wireless Networks,” in _IEEE Transactions on Communications_, doi: 10.1109/TCOMM.2024.3379368.

## Content of Code Package
This project includes time limited optimization process of both linear objective function and non-linear objective function. Please following the Note.txt in each file to run the respecitve simulation.

Two excel files include Packet Error Rate (PER) and Throughput performance under different levels of Modulation and Coding Scheme (MCS) and channel conditions using WLAN toolbos in MATLAB. Please find more details of channel simulation in our paper.

## Abstract of the DO-CR
Distributed-Optimization with Centralized-Refining (DO-CR) mechanism to achieve more efficient resource allocation by engaging both access point and all devices. 
Specifically, the new DO-CR mechanism first utilizes the distributed processing capacity of all devices, allowing them to optimize their own resource allocation schemes through a new resource reservation and reporting technique. 
Then a centralized optimizer generates a graph of resource trading topology based on individual optimization results and achieves the Pareto optimal solution by the graph-based algorithm. This Pareto optimal solution simplifies the overall optimization problem and enables the central optimizer to solve it with smaller feasible regions.

## License and Referencing
This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.

## Acknowledgements
This work was supported in part by the Discovery Program of Natural Sciences and Engineering Research Council of Canada (NSERC) under Grant RGPIN2018-06254, and in part by the Canada Research Chair Program.

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