In most cellular propagation environments, a LOS propagation path does not exist to all of the BSs that participate in locating a target MS. The signal received by the receiver is a multipath and interference mixed signal, which is NLOS signal. In NLOS conditions, the traditional location algorithms perform poorly. Therefore, a scattering-model-based location method for cellular network was proposed in this paper. Based on the Ring of Scatters (ROS) model, with the use of the mean value of the TOA measurements, the method mitigated the effects of NLOS.
With the previous proposed G/G/1 model, this paper analyzed the throughput expression in an unsaturated 802.11e one-hop ad hoc network. The expression is validated and the throughput performance is discussed by the simulations. The throughput expression derived in this paper will provide a way to analyze the impact of major QoS specific features on the throughput and hence can improve the performance of the network.
The facial expression recognition technology has been widespread concerned and researched, and many methods have been presented. This paper focuses on studying and analyzing the feature extraction, feature dimension reduction and two-against-two multi-class Support Vector Machine (SVM) method, and an algorithm is proposed for recognition of six basic facial expressions. According to expression feature information in the different face region, the algorithm adopts local nonuniform feature point extraction to reduce the feature dimension. After transforming the feature points with Gabor filters, the Gabor expression features are obtained. And the feature dimension is further reduced by discrete wavelet transform (DWT) and discrete cosine transform (DCT). At last, the tow-against-two classification method and an optimum decision scheme are used to realize quick and accurate expression classification. Experimental results show the algorithm can achieve higher recognition rate, recognition speed and stronger robust.
Along with the gradual increase of intelligent and information equipment on the battlefield, the fierce electronic warfare between the enemy and us makes the electromagnetic environment of the battlefield more and more severe. The anti-jamming capability of conventional frequency-hopping communication system is inadequate such as anti-dynamic interference, anti-intercept, etc., thus posing a serious threat to normal military communication. Moreover, currently the data transmission rate of frequency-hopping system is fairly lower, and cannot meet the increasing large-capacity real-time data transmission requirements. This article deeply researches self-adaptive MIMO-OFDM technology and frequency-hopping communication technology, and introduces the research on frequency-hopping communication technology based on self-adaptive MIMO-OFDM system. The research shows that self-adaptive MIMO-OFDM-based technology can effectively enhance the frequency-hopping communication system’s anti-jamming and anti-intercepting capability, and improve the data transmission rate.
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