Low earth orbit (LEO) satellite communications are expected to be incorporated in future wireless networks, in particular 5G and beyond networks, to provide global wireless access with enhanced data rates. Massive mul...
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Deep convolutional neural networks (CNNs) with strong expressive ability have achieved impressive performances on single image super-resolution (SISR). However, their excessive amounts of convolutions and parameters u...
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As Deep Neural Networks (DNNs) have demonstrated superhuman performance in a variety of fields, there is an increasing interest in understanding the complex internal mechanisms of DNNs. In this paper, we propose Relat...
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We present OntoScene, a framework aimed at understanding the semantics of visual scenes starting from the semantics of their elements and the spatial relations holding between them. OntoScene exploits ontologies for r...
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Hybrid energy powered cellular networks are key for proposing green and cost-efficient wireless networks. Yet, the related energy management imposes severe challenges to efficiently manage the power allocation between...
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In this paper, we propose an interpolation formula for periodic functions. This formula can be regarded as an analog of the Sinc approximation, which is an interpolation formula for functions defined on the entire inf...
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In this work, we investigate the non-orthogonal multiple access (NOMA) enabled power allocation for cooperative jamming under a two-user downlink scenario. In particular, we consider that there exists a malicious eave...
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Multispectral pedestrian detection is becoming increasingly important in the field of computer vision due to its applications in driver assistance, surveillance, and monitoring. In this paper, we propose a brightness ...
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In this paper, we examine the use of autoencoders as an optimization tool for the construction of noncoherent space-time MIMO codes. In particular, we consider the quasi-static block fading channel, where the channel ...
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ISBN:
(数字)9781728109626
ISBN:
(纸本)9781728109633
In this paper, we examine the use of autoencoders as an optimization tool for the construction of noncoherent space-time MIMO codes. In particular, we consider the quasi-static block fading channel, where the channel state information is not available at either the transmitter or the receiver, and changes independently between transmissions. Different from traditional constructions which aim to maximize an approximation of the minimum pairwise distance of the constellation, we use the autoencoder to directly target minimizing the probability of error. We show that this different optimization goal leads to constellations with more favorable pairwise distances' distribution and better error performance at low to medium signal to noise ratios where the minimum distance is not the limiting factor. Finally, we present simulation results showing that the constructed codes outperform traditional Grassmannian codes up to a signal-to-noise ratio of 20 dB using the traditional generalized likelihood ratio test detector.
The outage performance of wireless networks with unstructured network topologies is investigated. The network reliability perspective of graph theory is used to obtain the network outage polynomial of generalized wire...
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