Considering the significant traction, the market is garnering currently, Market Research Future (MRFR) in its recently published study analysis asserts that the global Depth Sensing market is poised to reach the valuation of USD 7.43 BN by 2023, registering 11.64% CAGR throughout the forecast period (2017 - 2023).
Depth sensing process involves measuring the distance of an object with the help of a depth sensor.
Another important spectrum sensing design issue involves determining how many channels to go through in each sensing.
Reliability of CR spectrum sensing refers to the ability of the CR on minimizing interferences in the spectrum access, where spectrum sensing serves this purpose in gaining channel status before accessing the channel.
Then mobile users should be given incentives to carry out spectrum sensing
. With a limited budget, FC may choose a subset of whole mobile users to carry out spectrum sensing
This study with multi-source remote sensing
image as data source, based on the texture of the land use classification, first of all, the remote sensing
image preprocessing, to convert the image as the feature vector information, texture feature library is established to achieve the fusion of multi-source remote sensing
and Bio-Sensing Research aims to expose and promote new and novel sensing
and biosensing technologies to the wider research community and exploitation partners."
technology has already been adopted by companies that are recognized as having the most progressively managed supply chains.
In this paper, we provide a more in depth and complete analysis of our BSS-based spectrum sensing
compared to our initial contribution  that was only based on the ICA algorithm.
In this paper, we have proposed a new sensing
channel model that considers combined impact of shadowing fading and multipath effects.
can provide information that is useful for many crop management decisions, including the detection of nutrient deficiencies, excesses or deficiencies of soil water, damage caused by insects, weeds, or diseases, and the magnitude of these factors in various portions of fields.
In spectrum sensing
, it is desired to minimize spectrum sensing
error (i.e., sum of false alarm and miss detection probabilities) since minimizing spectrum sensing
error both reduces collision probability with primary user and enhances usage level of vacant spectrum.