Proposing Decentralized Algorithm for Minimization of Transmission Power and Improving System Performance in Radio Network
DOI:
https://doi.org/10.46243/jst.2023.v8.i04.pp1-17Keywords:
power, radio netwok, minimize, algorithm, engeryAbstract
The minimization of transmission power is a critical issue in radio networks due to its impact on network coverage, energy efficiency, and signal quality. In this paper, we propose a decentralized algorithm for the minimization of transmission power in radio networks. The proposed algorithm allows each node in the network to independently adjust its transmission power based on its local information, without the need for centralized coordination. We evaluate the performance of the proposed algorithm through extensive simulations, comparing it to other centralized and decentralized algorithms in terms of transmission power, network coverage, and signal quality. Our results show that the proposed algorithm outperforms existing decentralized algorithms and can approach the performance of centralized algorithms. Furthermore, the proposed algorithm offers improved scalability and robustness to node failures, making it an attractive solution for large-scale wireless networks. Overall, our study demonstrates the potential of decentralized algorithms for power optimization in radio networks and provides insights into the design and implementation of such algorithms.
References
Kanthavel, R., et al. “Multi-hoped cooperative communication-based wireless underground sensor network design.” International Journal of Communication Systems 35.10 (2022): e5174
Ajay, P., B. Nagaraj, and J. Jaya. “Bi-level energy optimization model in smart integrated engineering systems using WSN.” Energy Reports 8 (2022): 2490-2495
Zhang, Xiaoqi, et al. “IRS empowered UAV wireless communication with resource allocation, reflecting design and trajectory optimization.” IEEE Transactions on Wireless Communications 21.10 (2022): 7867-7880
Akyildiz, I.F., Wang, X. and Wang, W., 2005. Wireless mesh networks: a survey. Computer networks, 47(4), pp.445-487
Amokrane, Ahmed, et al. “Energy efficient management framework for multihop TDMAbased wireless networks.” Computer Networks 62 (2014): 29-42
Santhiya, K. G., and N. Arumugam. “Energy aware reliable routing protocol (EARRP) for mobile ad hoc networks using bee foraging behavior and ant colony optimization.” International Journal of Computer Science Issues (IJCSI) 9 (2012): 1694-0814
Tan, Hexiang, et al. “Energy-aware and deadlineconstrained task scheduling in fog computing systems.” 2020 15th International Conference on Computer Science & Education (ICCSE). IEEE, 2020
Zhou, Tianqing, et al. “Joint user association and power control for load balancing in downlink heterogeneous cellular networks.” IEEE Transactions on Vehicular Technology 67.3 (2017): 2582-2593
Wu, Hua, et al. “A hybrid mobile node localization algorithm based on adaptive MCB-PSO approach in wireless sensor networks.” Wireless communications and mobile computing 2020 (2020)
Guo, Ao, et al. “Distributed power control with soft removal for uplink energy harvesting wireless network.” IET Communications 10.12 (2016): 1456-1463
Chen, Xianfu, et al. “Energy-efficiency oriented traffic offloading in wireless networks: A brief survey and a learning approach for heterogeneous cellular networks.” IEEE Journal on Selected Areas in Communications 33.4 (2015): 627-640
Zheng, Jun, et al. “A Neural Network based Power Allocation Algorithm for D2D Communication in Cellular Networks.” 2021 IEEE Global Communications Conference (GLOBECOM). IEEE, 2021
Published
How to Cite
Issue
Section
