638 research outputs found
A dependency look at the reality of constituency
A comment on "Neurophysiological dynamics of phrase-structure building during
sentence processing" by Nelson et al (2017), Proceedings of the National
Academy of Sciences USA 114(18), E3669-E3678.Comment: Final versio
The relation between dependency distance and frequency
International audienceThis present pilot study investigates the relationship between dependency distance and frequency based on the analysis of an English dependency treebank. The preliminary result shows that there is a non-linear relation between dependency distance and frequency. This relation between them can be further formalized as a power law function which can be used to predict the distribution of dependency distance in a treebank
Boosting Fronthaul Capacity: Global Optimization of Power Sharing for Centralized Radio Access Network
The limited fronthaul capacity imposes a challenge on the uplink of
centralized radio access network (C-RAN). We propose to boost the fronthaul
capacity of massive multiple-input multiple-output (MIMO) aided C-RAN by
globally optimizing the power sharing between channel estimation and data
transmission both for the user devices (UDs) and the remote radio units (RRUs).
Intuitively, allocating more power to the channel estimation will result in
more accurate channel estimates, which increases the achievable throughput.
However, increasing the power allocated to the pilot training will reduce the
power assigned to data transmission, which reduces the achievable throughput.
In order to optimize the powers allocated to the pilot training and to the data
transmission of both the UDs and the RRUs, we assign an individual power
sharing factor to each of them and derive an asymptotic closed-form expression
of the signal-to-interference-plus-noise for the massive MIMO aided C-RAN
consisting of both the UD-to-RRU links and the RRU-to-baseband unit (BBU)
links. We then exploit the C-RAN architecture's central computing and control
capability for jointly optimizing the UDs' power sharing factors and the RRUs'
power sharing factors aiming for maximizing the fronthaul capacity. Our
simulation results show that the fronthaul capacity is significantly boosted by
the proposed global optimization of the power allocation between channel
estimation and data transmission both for the UDs and for their host RRUs. As a
specific example of 32 receive antennas (RAs) deployed by RRU and 128 RAs
deployed by BBU, the sum-rate of 10 UDs achieved with the optimal power sharing
factors improves 33\% compared with the one attained without optimizing power
sharing factors
Nanoscale Reconfigurable Intelligent Surface Design and Performance Analysis for Terahertz Communications
Terahertz (THz) communications have been envisioned as a promising enabler to
provide ultra-high data transmission for sixth generation (6G) wireless
networks. To tackle the blockage vulnerability brought by severe attenuation
and poor diffraction of THz waves, a nanoscale reconfigurable intelligent
surface (NRIS) is developed to smartly manipulate the propagation directions of
incident THz waves. In this paper, the electric properties of the graphene are
investigated by revealing the relationship between conductivity and applied
voltages, and then an efficient hardware structure of electrically-controlled
NRIS is designed based on Fabry-Perot resonance model. Particularly, the phase
response of NRIS can be programmed up to 306.82 degrees. To analyze the
hardware performance, we jointly design the passive and active beamforming for
NRIS aided THz communication system. Particularly, an adaptive gradient descent
(A-GD) algorithm is developed to optimize the phase shift matrix of NRIS by
dynamically updating the step size during the iterative process. Finally,
numerical results demonstrate the effectiveness of our designed hardware
architecture as well as the developed algorithm.Comment: 9 pages, 8 figures. arXiv admin note: substantial text overlap with
arXiv:2012.0699
Rediscovering Greenberg's Word Order Universals in UD
International audienceThis paper discusses an empirical refoundation of selected Greenbergian word order univer-sals based on a data analysis of the Universal Dependencies project. The nature of the data we work on allows us to extract rich details for testing well-known typological universals and constitutes therefore a valuable basis for validating Greenberg's universals. Our results show that we can refine some Greenbergian universals in a more empirical and accurate way by means of a data-driven typological analysis
Two-stage time-domain pilot contamination elimination in large-scale multiple-antenna aided and TDD based OFDM systems
Pilot contamination (PC) is a major impediment of large-scale multi-cell multiple-input multiple-output (MIMO) systems. Hence we propose an optimal pilot design for timedomain channel estimation, which is capable of completely eliminating PC. More specifically, a sophisticated combination of downlink training and ‘scheduled’ uplink training is designed with the aid of the optimal pilot set. Given the optimal pilot set, every user acquires its unique downlink time-domain channel state information (CSI) through downlink training. The estimated downlink CSIs are then embedded in the uplink training. As a result, PC can be completely eliminated, at the cost of a slight increase in training computational complexity. Our simulation results demonstrate the power of the proposed scheme. Most significantly, our scheme imposes a modest training overhead of (L + 3), training-phase durations corresponding to the number of OFDM symbols, where L is the number of cells, which is substantially lower than that imposed by some of the existing PC elimination schemes. Therefore, it imposes a less stringent requirement on the channel’s coherence time. Finally, our scheme does not need any information exchange between base stations
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