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This paper discusses the physical layer abstraction algorithms for the integration of next-generation high-speed wireless local area network (WLAN) based on 802.11n and Long term evolution (LTE) cellular mobile communication network. Both the received bit information rate (RBIR) algorithm and the exponential effective signal-to-noise-ratio (SNR) mapping (EESM) algorithm are compared and analyzed in the heterogeneous network which is the integration of next-generation high-speed WLAN based on 802.11n and LTE cellular mobile communication network, and an appropriate method for the physical layer abstraction (PLA) algorithms selection is proposed by Link Level Simulation (LLS) and comparative analysis.

This paper describes a novel method for extracting fingerprints of executables. A new data visual approach based on data field is imported. The 3-tuple (in-degree, out-degree, function call relationship) extracted from call graph are used for constructing data field and the potential field graph. This potential field graph is fingerprinted by the method of shape invariant moments which is mature and statistic approach to analyze the shape of image. Experimental results show that the shape invariant moments of the potential field graph can be used to identify different executable programs as a fingerprint.