This paper describes a new method for how interfering MIMO links might transmit more effectively in a random access network. We assume perfect transmitter-side channel state information, zero-forcing pre-coding to gua...
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This paper describes a new method for how interfering MIMO links might transmit more effectively in a random access network. We assume perfect transmitter-side channel state information, zero-forcing pre-coding to guarantee no interference on links that have already won access, and zero-forcing receiver processing at the still-contending links to suppress interference from the links that have already won. We define an effectiveness metric, the Instantaneous Equivalent SNR Percentile (IESP), in which the Equivalent SNR is the SNR of a single-input-single-output (SISO) link that would have the same capacity of a MIMO link after its interference constraints have been met and the IESP is the percentile of the Equivalent SNR, assuming independent Rayleigh fading. We propose that fairness among heterogeneous contending links be realized by giving the shorter contention window to the link with the higher IESP based on its own distribution, enabling links with few antennas to compete with links that have many antennas. Through simulation of the sum capacity of the winning set of links, the proposed contention window design is shown to provide a higher sum capacity than contention based on equal-sized windows.
To improve the measuring accuracy of intrusion detection, a system design of a node for intrusion detection is proposed in this paper. First, the technology that applies the traditional intrusion detection method, suc...
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We propose a semi-informative aware approach using the topic model on query expansion problem in the biomedicine domain. the demographics and disease information is applied to semi-structure the topic model as the “k...
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We propose a semi-informative aware approach using the topic model on query expansion problem in the biomedicine domain. the demographics and disease information is applied to semi-structure the topic model as the “known” label, compared to the traditional latent topics in topic modelling. Then, we suggest to select three terms from the top ranked documents to expand the query, based on the assumption in the pseudo relevance feedback method that the top ranked results in the first retrieval around are relevant. After that, we conduct the experiments on the TREC medical records data sets with extensive analysis and discussions. Numerically, we achieve the improvements of 7.41% on MAP, 9.29% on Bpref and 5.60% on P@10 respectively over the strong baselines.
In recent years, cloud computing has emerged as an enabling technology, in which virtual machine migration and dynamic resource allocation is one of the hot issues. During the migration of virtual machine, access requ...
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As a latest immune algorithm, dendritic cell algorithm (DCA) has been successfully applied into the abnormal detection. First, this paper reviewed the research progress of DCA from the following aspects: signal extrac...
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Coverage enhancement is one of the hot research topics in wireless multimedia sensor net- works. A novel Coverage-enhancing algorithm based on three-dimensional Directional perception and co-evolution (DPCCA) is propo...
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Coverage enhancement is one of the hot research topics in wireless multimedia sensor net- works. A novel Coverage-enhancing algorithm based on three-dimensional Directional perception and co-evolution (DPCCA) is proposed in multimedia sensor networks on the basis of the model whose pitch angle and deviation angle can be adjusted. Based on the proposed elliptical cone sensing model, we can derive the coverage area of the node and calculate the optimal pitch angle according the information of monitoring area and the nodes, and then the deviation angle is optimized based on co-evolution al- gorithm, which eliminate the overlapped and blind sensing area effectively. A set of simulations demonstrate the ef- fectiveness of our algorithm in coverage ratio.
In this paper, a downlink multi-carrier cognitive radio (CR) network is considered. The CR network consists of one cognitive base station (CBS) and a set of secondary users (SUs) sharing the same spectrum with the pri...
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ISBN:
(纸本)9781479964123
In this paper, a downlink multi-carrier cognitive radio (CR) network is considered. The CR network consists of one cognitive base station (CBS) and a set of secondary users (SUs) sharing the same spectrum with the primary user (PU). Chunk-based resource allocation is adopted where subcarriers are grouped into chunks for allocation to the SUs. The problem of chunk-based resource allocation under the interference power constraint and the transmit power constraint is investigated. The objective is to maximize the sum rate of the SUs. For this, based on Lagrange dual method, a near-optimal joint chunk and power allocation scheme is proposed. The complexity of the optimal scheme is exponential in the number of chunks, while the complexity of the proposed scheme is reduced significantly to only linear in the number of chunks, and at the same time, it is shown that the proposed scheme achieves almost the same performance that can be achieved by the optimal scheme. The impacts of the interference power constraint, the transmit power constraint, number of subcarriers within the chunk and the channel coherence bandwidth on the performance of the proposed scheme are investigated. Particularly, it is shown that increasing the channel coherence bandwidth does not always lead to improvement of the SU performance.
keys are very important for data management. Due to the hierarchical and flexible structure of XML, mining keys from XML data is a more complex and difficult task than from relational databases. In this paper, we stud...
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In this paper, a novel feedback linearization sliding mode controlled parallel active power filter with indirect current control approach is presented in the three-phase three-wire grid. The feedback linearization ind...
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Real-world networks often contain communities with pervasive overlaps such that nodes simultaneously belong to several groups. Community extraction, emerging in recent years, is considered to be a promising solution f...
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Real-world networks often contain communities with pervasive overlaps such that nodes simultaneously belong to several groups. Community extraction, emerging in recent years, is considered to be a promising solution for finding meaningful communities from social networks. In this paper, we explore overlapping community extraction from a link partitioning perspective. First, we define the local link structure composed of a set of closely interrelated links, by extending the similarity of link-pairs to that of a group of links. Second, based upon our prior work, we transform the problem of mining local link structures into a pattern mining problem, and thus present an efficient mining algorithm. Third, we propose to use the hypergraph to assemble all local link structures, and employ hMETIS for hypergraph partitioning. Finally, based on extracted link communities, we restore the membership of nodes in the original graph owing to its links. Experimental results on various real-life social networks validate the effectiveness of the proposed method.
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