In unmanned aerial vehicle ad-hoc network (UANET), the network topology changes with time due to the movement of the unmanned aerial vehicles (UAVs), which brings great challenges to the design of the routing protocol. In traditional routing protocols, when UANET topology changes, nodes cannot dynamically update neighbour nodes and topology information, and routing table calculation cannot accurately reflect the actual transmission path. As a result, network cannot meet the quality of service (QoS) requirements such as low end-to-end delay, high throughput and low packet loss rate. This paper proposes a dynamically optimized link state routing (OLSR) protocol based on Deep Q-Network algorithm (DQN-OLSR). In this protocol, each node first adjusts the sending interval of Hello messages adaptively in real time, according to the position and speed information of its neighbour nodes. Then the protocol uses the DQN algorithm to dynamically adjust the flooding interval of topology control (TC) messages to improve the routing update capability of nodes. The simulation verifies that the UANETs under this protocol have higher throughput and less packet loss rate than ad-hoc on-demand distance vector (AODV), grid routing protocol (GRP) and OLSR protocols, at different movement speeds in random waypoint (RWP) and random walk mobile models. Under nomadic as well as pursue mobile models, DQN-OLSR performs consistently with OLSR QoS performance, with the best performance among all four protocols. By further adding positioning errors to the nodes, it shows that the proposed protocol has good robustness, and the QoS performance degradation keeps within a low level.
Trans-impedance amplifier (TIA) based capacitance–voltage (C–V) readout circuit is an attractive choice for micro-machined gyroscope for its simplicity and superior performance. In this work, the noise and the C–V gain characteristics of the TIA circuit are analyzed in detail. Then, a TIA based readout circuit with a C–V gain of about 286 dB is designed, and a series of experiments are conducted to test the performance of the circuit. Both the analysis and test results show that T-network TIA should be avoided as far as possible for its poor noise performance. All results also show that there is a signal-to-noise ratio (SNR) limit for the TIA based readout circuit, and the SNR can only be further improved by filtering. Hence, an adaptive finite impulse response filter is designed to further improve the SNR of the sensed signal. For a gyroscope with a peak-to-peak variable capacitance of about 200 aF, a SNR of 22.8 dB can be achieved by the designed circuit and a SNR of 47 dB can be obtained by further adaptive filtering. Finally, the solution presented in this paper achieves a capacitive sensing resolution of 0.9 aF.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.