1,218 research outputs found
On Channel Reciprocity to Activate Uplink Channel Training for Downlink Wireless Transmission in Tactile Internet Applications
We determine, for the first time, the requirement on channel reciprocity to
activate uplink channel training, instead of downlink channel training, to
achieve a higher data rate for the downlink transmission from a multi-antenna
base station to a single-antenna user. We first derive novel closed-form
expressions for the lower bounds on the data rates achieved by the two channel
training strategies by considering the impact of finite blocklength. The
performance comparison result of these two strategies is determined by the
amount of channel reciprocity that is utilized in the uplink channel training.
We then derive an approximated expression for the minimum channel reciprocity
that enables the uplink channel training to outperform the downlink channel
training. Through numerical results, we demonstrate that this minimum channel
reciprocity decreases as the blocklength decreases or the number of transmit
antennas increases, which shows the necessity and benefits of activating the
uplink channel training for short-packet communications with multiple transmit
antennas. This work provides pivotal and unprecedented guidelines on choosing
channel training strategies and channel reciprocity calibrations, offering
valuable insights into latency reduction in the Tactile Internet applications.Comment: 6 pages, 3 figures, Submitted to IEEE ICC 2018 Worksho
ANALYSIS OF INNOVATIVE TEACHING REFORM IN COLLEGE FINANCIAL ACCOUNTING EDUCATION UNDER COGNITIVE IMPAIRMENT
Bolt Detection Signal Analysis Method Based on ICEEMD
The construction quality of the bolt is directly related to the safety of the
project, and as such, it must be tested. In this paper, the improved complete
ensemble empirical mode decomposition (ICEEMD) method is introduced to the bolt
detection signal analysis. The ICEEMD is used in order to decompose the anchor
detection signal according to the approximate entropy of each intrinsic mode
function (IMF). The noise of the IMFs is eliminated by the wavelet soft
threshold de-noising technique. Based on the approximate entropy, and the
wavelet de-noising principle, the ICEEMD-De anchor signal analysis method is
proposed. From the analysis of the vibration analog signal, as well as the bolt
detection signal, the result shows that the ICEEMD-De method is capable of
correctly separating the different IMFs under noisy conditions, and also that
the IMF can effectively identify the reflection signal of the end of the bolt
Graphene Helicoid: The Distinct Properties Promote Application of Graphene Related Materials in Thermal Management
The extremely high thermal conductivity of graphene has received great
attention both in experiments and calculations. Obviously, new feature in
thermal properties is of primary importance for application of graphene-based
materials in thermal management in nanoscale. Here, we studied the thermal
conductivity of graphene helicoid, a newly reported graphene-related
nanostructure, using molecular dynamics simulation. Interestingly, in contrast
to the converged cross-plane thermal conductivity in multi-layer graphene,
axial thermal conductivity of graphene helicoid keeps increasing with thickness
with a power law scaling relationship, which is a consequence of the divergent
in-plane thermal conductivity of two-dimensional graphene. Moreover, the large
overlap between adjacent layers in graphene helicoid also promotes higher
thermal conductivity than multi-layer graphene. Furthermore, in the small
strain regime (< 10%), compressive strain can effectively increase the thermal
conductivity of graphene helicoid, while in the ultra large strain regime
(~100% to 500%), tensile strain does not decrease the heat current, unlike that
in generic solid-state materials. Our results reveal that the divergence in
thermal conductivity, associated with the anomalous strain dependence and the
unique structural flexibility, make graphene helicoid a new platform for
studying fascinating phenomena of key relevance to the scientific understanding
and technological applications of graphene-related materials.Comment: 7 figure
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