Common-mode voltage reduction for matrix converters using all valid switch states

This paper presents a new space vector modulation(SVM) strategy for matrix converters to reduce the common-mode voltage (CMV). The reduction is achieved by using the switch states that connect each input phase to a different output phase, or the switch state that connects all the output phases to the input phase with minimum absolute voltage. These two types of states always produce lower peak CMV than the others, especially the former ones that result in zero CMV at the output side of matrix converters. In comparison with the existing SVM methods, this strategy has a very similar software overhead and calculation time. Simulation and experiment results are shown to validate the effectiveness of the proposed modulation method in reducing not only the peak value but also the root-mean-square value of the CMV

Federated Meta Learning Enhanced Acoustic Radio Cooperative Framework for Ocean of Things Underwater Acoustic Communications

Sixth-generation wireless communication (6G) will be an integrated architecture of "space, air, ground and sea". One of the most difficult part of this architecture is the underwater information acquisition which need to transmitt information cross the interface between water and air.In this senario, ocean of things (OoT) will play an important role, because it can serve as a hub connecting Internet of things (IoT) and Internet of underwater things (IoUT). OoT device not only can collect data through underwater methods, but also can utilize radio frequence over the air. For underwater communications, underwater acoustic communications (UWA COMMs) is the most effective way for OoT devices to exchange information, but it is always tormented by doppler shift and synchronization errors. In this paper, in order to overcome UWA tough conditions, a deep neural networks based receiver for underwater acoustic chirp communication, called C-DNN, is proposed. Moreover, to improve the performance of DL-model and solve the problem of model generalization, we also proposed a novel federated meta learning (FML) enhanced acoustic radio cooperative (ARC) framework, dubbed ARC/FML, to do transfer. Particularly, tractable expressions are derived for the convergence rate of FML in a wireless setting, accounting for effects from both scheduling ratio, local epoch and the data amount on a single node.From our analysis and simulation results, it is shown that, the proposed C-DNN can provide a better BER performance and lower complexity than classical matched filter (MF) in underwater acoustic communications scenario. The ARC/FML framework has good convergence under a variety of channels than federated learning (FL). In summary, the proposed ARC/FML for OoT is a promising scheme for information exchange across water and air

Distributed Interference-Aware Cooperative MAC based on Stackelberg Pricing Game

International audienceCooperative communication can significantly enhance the efficient utilization of spectrum in wireless networks.The performance of wireless cooperative networks depends on careful medium access control and resource allocation such asrelay selection and cooperative link scheduling policy for interference management. Most of the previous centralized worksrely on precise instantaneous channel state information (CSI). In this paper, considering the impact of multi-relay linksinterference on relay selection and dynamic spectrum sharing, we propose a fully distributed relay medium access control (MAC)scheme for wireless cooperative networks based on Stackelberg game framework with only one-hop local CSI, where source nodesthat have their own information to send act as leader users and the others act as follower users. In this scenario, each relay nodeprices its spectrum resource to the corresponding source node to maximize its revenue. In addition, the proposed scheme not onlyhelps source nodes to find relay nodes by channel gains and obtain an optimal system performance, but also helps relay nodes tomaximize their revenue by asking suitable resource price. The interactions between the sources and relays leads iteratively to aStackelberg equilibrium, in which the cooperation system achieves high throughput and low transmission delay. Simulationresults are presented to show the effectiveness of the proposed approach

Landau Levels as a Probe for Band Topology in Graphene Moire Superlattices

We propose Landau levels as a probe for the topological character of electronic bands in two-dimensional moire superlattices. We consider two configurations of twisted double bilayer graphene (TDBG) that have very similar band structures, but show different valley Chern numbers of the flat bands. These differences between the AB-AB and AB-BA configurations of TDBG clearly manifest as different Landau level sequences in the Hofstadter butterfly spectra calculated using the tight-binding model. The Landau level sequences are explained from the point of view of the distribution of orbital magnetization in momentum space that is governed by the rotational C-2 and time-reversal T symmetries. Our results can be readily extended to other twisted graphene multilayers and h-BN/graphene heterostructures thus establishing the Hofstadter butterfly spectra as a powerful tool for detecting the nontrivial valley band topology

Rate control for semi-TCP in multihop wireless networks

Abstract This paper studies the rate control algorithm to improve the performance of semi-TCP, which adopts a buffer-based hop-by-hop congestion control mechanism. By analyzing the impact of the buffer-based sending strategy on the medium contention and interference, we find that this sending strategy is too aggressive to increase the throughput, which leads to severe contention and interference in the channel. Extensive simulations are then carried out and reveal the significance of the channel status of the first hop in rate control. Based on the findings in the simulations, we propose a binary search-based rate control to improve semi-TCP using only local information. The proposed rate control relies on the media status in the first hop to adjust the source rate to approach the peak throughput, without the assistance of end-to-end feedback. Simulation results show the effectiveness of the proposed algorithm in improving the end-to-end throughput and delay

Anti-Eavesdropping by Exploiting the Space–Time Coupling in UANs

Due to the space–time coupling access, we find that anti-eavesdropping opportunities exist in underwater acoustic networks (UANs), where packets can be successfully received only by the intended receiver, but collide at the unintended receivers. These opportunities are highly spatially dependent, and this paper studies the case that linearly deployed sensor nodes directly report data toward a single collector. We found an eavesdropping ring centered around these linearly deployed sensor nodes, where the eavesdropper could steal all the reported data. Since the typical receiving-alignment-based scheduling MAC (TRAS-MAC) will expose the relative spatial information among the sensor nodes with the collector, the eavesdropper can locate the eavesdropping ring. Although moving the collector into the one-dimensional sensor node chain can degrade the eavesdropping ring to a point that constrains the eavesdropping risk, the collector’s location will be subsequently exposed to the eavesdropper. To efficiently protect the reported data and prevent the exposure of the collector’s location, we designed a slotted- and receiving-alignment-based scheduling MAC (SRAS-MAC). The NS-3 simulation results showed the effectiveness of the SRAS-MAC and the TRAS-MAC in protecting data from eavesdropping, which protect 90% of the data from eavesdropping in the one-eavesdropper case and up to 80% of data from eavesdropping in ten-eavesdropper cases. Moreover, unlike TRAS-MAC, which will expose the collector’s location, SRAS-MAC provides multiple positions for the collector to hide, and the eavesdropper cannot distinguish where it is