Green and sustainable communications are crucial for cellular devices and the Internet of Things (IoT) devices in the fifth generation (5G) mobile communication system. Wireless-powered communication (WPC) provides a successful technical paradigm to support wireless information transmission for mobile devices by using harvested radio-frequency (RF) energy. In the meantime, non-orthogonal multicarrier transmission techniques, typically represented by the generalized frequency-division multiplexing (GFDM), can not only enhance spectrum efficiency but also improve the flexibility of resource allocation due to its fine-granularity sub-block. In this paper, a GFDM-based cooperative relay system model is proposed to improve the quality of experience of the cell-edge user. Specifically, the system is composed of one source node, one destination node (cell-edge user), and one relay node. The source node transmits a signal to the destination node and the relay node. The relay node performs information transmission and power transfer to the destination node by using different GFDM sub-block sets. The destination node combines the signals from the source node and relay node. In order to maximize the information rate at the destination node subject to the minimum harvested energy, a joint sub-block, sub-block power, and subslot allocationbased WPC scheme is proposed. To solve the non-convex optimization problem, an iterative algorithm is proposed and its effectiveness is validated by simulations. The simulation results demonstrate that the GFDM-based WPC scheme outperforms the orthogonal frequency-division multiplexing (OFDM), and the subslot optimization can significantly increase the information rate at the destination node.INDEX TERMS 5G, wireless powered communication, generalized frequency division multiplexing, cooperative relay, optimization.
There are some urgent problems in the construction of the Pearl River Delta smart water conservancy project. In terms of operation, this project still needs improvement. Particularly, localization and tracking of personnel and equipment are the technical issues that urgently need to be solved. In order to improve the accuracy and the environmental adaptability of personnel and equipment localization algorithms in the construction and operation of pipeline network, this paper proposes a fingerprint localization algorithm (KF-KNN) based on frequency modulation (FM) signals. Firstly, the FM data collection device is used to obtain the received signal strength indicator (RSSI) fingerprint information within the coverage area, and train them to build a fingerprint database. Secondly, the k-nearest neighbors (KNN) technology is used to complete the rough localization calculation based on the RSSI data received by the module, which includes the RSSI fingerprint database and the environmental noise parameters. Finally, the Kalman filter model is used to predict and optimize the rough position information in order to have better environmental adaptability and effectively improve the accuracy of localization. The analysis results show that the proposed KF-KNN algorithm has better performance in localization with average localization error as low as 1.9 meters compared with the original KNN and the weighted k-nearest neighbors (WKNN) fingerprint localization models.
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