Soft Frequency Reuse for Underwater Acoustic Sensor Networks with Interference Mitigation and Adaptive Resources Allocation

Zhang, Yuzhi; Wang, Anyi; Fan, Rong; Zhu, Jingru

doi:10.1109/ieeeconf38699.2020.9389057

Cited by 1 publication

(1 citation statement)

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“…However, because this algorithm does not provide channel state and node exchange information, it can not improve the performance and reliability. Literature [13] divides a channel into different cells and obtains a more accurate CSI based on the channel state information feedback by time-varying channels through self-learning. However, this algorithm can only achieve a higher throughput than traditional frequency multiplexing without considering propagation delay and resource allocation, which has great limitations.…”

Section: Related Workmentioning

confidence: 99%

Joint Channel and Power Assignment for Underwater Cognitive Acoustic Networks on Marine Mammal-Friendly

Xue,

Cao

2023

Applied Sciences

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When marine animals and underwater acoustic sensor networks (UASNs) share spectrum resources, problems such as serious harm caused to marine animals by underwater acoustic systems and scarcity of underwater spectrum resources are encountered. To address these issues, a mammal-friendly underwater acoustic sensor network channel power allocation algorithm is proposed. Firstly, marine animals are treated as authorized users and sensor nodes as unauthorized users. Considering the interference level of sensor nodes on authorized users, this approach improves network service quality and achieves a mammal-friendly underwater communication mechanism. Secondly, to maximize the utility of unauthorized users, the algorithm incorporates a network interference level and node remaining energy into a game-theoretical framework. Using channel allocation and power control, a game model is constructed with a unique Nash equilibrium point. Finally, through simulation, it can be found that the proposed algorithm can obtain a stable optimal power value, and with the increase of network load, the system capacity of the proposed algorithm is significantly improved than that of the traditional cognitive radio technology and the common spectrum allocation algorithm, and the transmitted power of nodes can be controlled according to the size of the residual energy, so as to comprehensively improve the overall performance of the network.

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Section: Related Workmentioning

confidence: 99%