With the continuous development of Internet things (IoT) technology, air-to-ground (ATG) system has attracted more and attention. The will effectively increase communication coverage improve quality. ATG uses frequency reuse technology in ground layer to further utilize resources. This paper focuses mostly on cochannel interference between 5G BS airborne CPE terminal 3.5 GHz range. be isolated ...

In this paper, we propose AutoCompete, a highly automated machine learning framework for tackling machine learning competitions. This framework has been learned by us, validated and improved over a period of more than two years by participating in online machine learning competitions. It aims at minimizing human interference required to build a first useful predictive model and to assess the pr...

For the purpose of tackling ultra-wideband (UWB) indoor positioning with signal interference, a binary classifier for interference discrimination and errors compensation model combining genetic algorithm (GA) extreme learning machine (ELM) are put forward. Based on distances between four anchors target which calculated time flight (TOF) ranging technique, GA-ELM-based judging existence built up...

For anti-active-interference-oriented cognitive radar systems, the mismatch between acquired and actual interference information may result in serious degradation of anti-active-interference performance. To yield more effective knowledge electromagnetic environment eliminate effect, activity prediction technique, which deduces future behaviors based on current observations, has received increas...

In dynamic environments, data characteristics may drift over time. This leads to deteriorate dramatically the performance of incremental learning algorithms over time. This is because of the use of data which is no more consistent with the characteristics of new incoming one. In this paper, an approach for learning in dynamic environments is proposed. This approach integrates a mechanism to use...

In this paper, we analyze the feasibility of indoor broadband service provisioning using secondary spectrum access to the 960-1215 MHz band, primarily allocated to the distance measuring equipment (DME) system for aeronautical navigation. We propose a practical secondary sharing scheme customized to the characteristics of the DME. Since the primary system performs a safety-of-life functionality...

Low-power machine-type communications devices in machine-to-machine networks are expected to operate autonomously for years, or even decades. Meanwhile, device-to-device (D2D) communications make large benefits on users’ data rate and power consumption because of the proximity between potential D2D transmitters and receivers. In this paper, we facilitate machine-type D2D links where the machine...

In this work we build a computational model of several auditory perceptual learning experiments. The modeled experiments show a pattern of learning interference which may help shed light on the structure of both short and long term stores of perceptual memory. It is our hypothesis that the observed interference patterns can be explained by the relationship of stimuli across tasks and how these ...

Incremental Attribute Learning (IAL) is a feasible approach for solving high-dimensional pattern recognition problems. It gradually trains features one by one. Previous research indicated that supervised machine learning with input attribute ordering can improve classification results. Moreover, input space partitioning can also effectively reduce the interference among features. This study pro...