A complementary-defected ground structure (DGS) common stopband filter is proposed. The filter uses two kinds of DGS patterns: a Π-shaped DGS pattern is used in both sides of the filter and a button-headed H-shaped DGS pattern is adopted at the middle of the filter. The filter utilizes the mutual inductance and mutual capacitance that exists among the DGS patterns to improve the in-band gain-flatness of the filter, which is useful to broaden the bandwidth and improve the rejection ratio in the low cutoff frequency. The simulated and measured results show that the differential signal under the DGS filter is nearly intact and the common-mode noise can be reduced by 15 dB from 3.2 to 12.4 GHz. The area of the filter is only 10 mm × 10 mm. The fractional bandwidth of the stopband can reach 118%.

Wireless sensor networks (WSNs), one of the fundamental technologies of the Internet of Things (IoT), can provide sensing and communication services efficiently for IoT-based applications, especially energy-limited applications. Clustering routing protocol plays an important role in reducing energy consumption and prolonging network lifetime. The cluster formation and cluster head selection are the key to improving the performance of the clustering routing protocol. An energy-efficient routing protocol based on multi-threshold segmentation (EERPMS) was proposed in this paper to improve the rationality of the cluster formation and cluster heads selection. In the stage of cluster formation, inspired by multi-threshold image segmentation, an innovative node clustering algorithm was developed. In the stage of cluster heads selection, aiming at minimizing the network energy consumption, a calculation theory of the optimal number and location of cluster heads was established. Furthermore, a novel cluster head selection algorithm was constructed based on the residual energy and optimal location of cluster heads. Simulation results show that EERPMS can improve the distribution uniformity of cluster heads, prolong the network lifetime and save up to 64.50%, 58.60% and 56.15% network energy as compared to RLEACH, CRPFCM and FIGWO protocols respectively.

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