在本文中，我們通過適當地部署一些具有能量收集功能的無人機進行數據收集，為密集型無線傳感器網絡（DWSN）提出了壽命延長方案。 為了促進數據收集，形成了多個叢集以分擔從DWSN上傳信息數據的負擔。 但是，與文獻不同的是，具有最低能量級別的感測器節點可以被選擇作為簇頭（CH）並由UAV充電，這被稱為低能量導向（LEO）CH選擇。 方案。 此外，為了解決更多叢集的情況，提出了兩層叢集結構。 具體而言，第一層和第二層分別由感測器節點和CH形成。 然後，應用一對一匹配來解決第二層叢集與無人機之間的關聯。 對於正確形成的群集，提出了連續凸優化（S-CVX）過程，以迭代地調整CH的傳輸功率，UAV的位置，每個叢集的分配帶寬以及每個CH上傳數據的時間段。 最後，在最小傳輸速率的要求下，進一步降低了每個感測器節點的傳輸功率。 模擬結果驗證了所提出方案延長DWSN壽命的有效性。

In this paper, we propose a lifetime extension scheme for the dense wireless sensor network (DWSN) by properly deploying some energy harvest-capable UAVs for data aggregation. To facilitate the data aggregation, multiple clusters are formed to share the burdens of uploading the informative data from the DWSN. However, to be differentiated from the literature, the sensor nodes with lowest energy level can have the privileges to be selected as the cluster heads (CHs) and be charged by the UAVs, which is named the low-energy oriented (LEO) CHs selection scheme. Moreover, to tackle the cases with more clusters, the two-tier cluster structure is proposed. To be specific, the first and second tiers are form by the sensor nodes and CHs, respectively. Then, the one-to-one matching is applied to solve the association between the second-tier clusters and UAVs. With properly formed clusters, the successive convex optimization (S-CVX) procedure is proposed to iteratively adjust the transmission power for CHs, the locations of the UAVs, the allocated bandwidth for each cluster and the time period for each CH to upload data. At last, the transmission power for each sensor node is further reduced under the requirement of the minimal transmission rate. The simulation results verify effectiveness of the proposed scheme to extend the lifetime for the DWSN.

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