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In this paper, we propose to leverage the emerging deep learning techniques for spatiotemporal modeling and prediction in cellular networks, based on big system data. First, we perform a preliminary analysis for a big dataset from China Mobile, and use traffic load as an example to show non-zero temporal autocorrelation and non-zero spatial correlation among neighboring Base Stations (BSs), which...
The densification of small cells (SCs) and caching at the edge are two promising approaches to improve the network throughput, reduce end-to-end delay and backhaul cost in future 5G wireless networks. However, current analysis and design only focus on the system state at a certain time, neglecting the temporal-spatial fluctuation of traffic and the content popularity variations, which are often affected...
In wireless cellular system, due to the convergence of user behavior, there usually exists some typical scenarios which exhibit different traffic patterns, e.g. stadium, campus and central business district (CBD). Accurate traffic scenario recognition and analysis will lead to more efficient resource management and better QoS (quality-of-service) provision. In this paper, with the idea of social network...
Understanding the spatial traffic patterns of wireless cellular system could facilitate the performance analysis and system design. In this paper, a novel method based on base stations social network (BSSN) is proposed for the prediction of spatial traffic in wireless cellular system. Firstly a BSSN, which can describe the spatial traffic relationship between base stations (BSs), is established with...
Due to the multidimensional nature of the hyperspectral image (HSI), multi-way arrays (called tensor) are one of the possible solutions for analyzing such data. In tensor algebra, CANDECOMP/PARAFAC decomposition (CPD) is a popular tool which has been successfully applied for the HSI data processing. However, on the one hand, CPD requires large memory for temporal variables. As a result, the memory...
Research on automated facial expression analysis (FEA) has been focused on applying different feature extraction methods on texture space and geometric space, using holistic or local facial regions based on regular grids or facial anatomical structure. Not much work has been investigated by taking human perception into account. In this paper, we propose to study the facial expressive regions using...
In this paper, the relationship between traffic and radio resources is analyzed combined with the real LTE network data. We found that the correlation between traffic and resources in LTE networks is much more complex than that in traditional networks like 2G and 3G, which can be exploited to predict their trends. So we employ a prediction method based on multidimensional correlation and cluster analysis...
The design and analysis of one-dimensional(1D) nearly-orthogonal symmetric wavelet filter banks has been studied. Methods for analyzing the correlation of the nearly-orthogonal filter banks are proposed. The basic idea is to impose multiple zeros at the aliasing frequency to a symmetric filter, minimize the deviation of the filter satisfying the orthogonal condition, then a nearly orthogonal filter...
Symbol synchronization is a critical component in the design of an underwater acoustic modem. Without accurate symbol synchronization, higher bit error rates incur thus reducing the reliability and quality of service of the wireless network. This paper provides a practical description of the design choices and hardware implementation details required to build a compact and efficient symbol synchronizer...
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