摘要：We propose a medium access control(MAC) protocol for uplink transmissions in wireless local area networks(WLANs),where both stations and access points(APs) are equipped with multiple antennas. The protocol solves some common problems in utilizing multiple input multiple output(MIMO) under the 802.11 protocol,e.g.,how to deploy preamble(training sequence) used for channel estimation and how to enable simultaneous data transmissions,and facilitates two simultaneous uplink data transmissions via a cross-layer approach. Furthermore,we develop a 3D discrete-time Markov model to analyze the per-formance of the proposed WLAN scheme. The analytical results are verified by simulation,and numerical results show that the system throughput can be significantly improved by our proposed scheme as compared with conventional schemes.

摘要：In this study, a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis. In the proposed hybrid intelligent system, support vector machines are used as a tool to extract typical features and filter its noise, which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines. Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets. Therefore, the proposed hybrid intelligent system overcomes the difficulty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches. In addition, the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.