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The cognitive radio is an emerging technology that enables dynamic spectrum access in wireless networks. The cognitive radio is capable of opportunistically using the available portions of a licensed spectrum to improve the application performance for unlicensed users. The opportunistic use of the available channels in the wireless environment requires dynamic channel assignment to efficiently utilize...
An adaptive beam forming algorithm with antenna array model based on quantum-behaved particle swarm optimization (QPSO) is proposed for improving existent problems of limited beam modulation, unsatisfactory side lobe suppression and poor adaptability. By adjusting beam direction with matrix-weighting, optimizing initial phase and radius of the antenna array, and by tracking user intelligently with...
For improving the accuracy of the traditional maximum entropy threshold segmentation algorithm, an improved maximum entropy segmentation algorithm is proposed. Firstly, it determines the possible range of an optimal segmentation threshold according to a simple statistical method, so as to reduce the interference of the background and magnify the proportion of the target region. Secondly, in a certain...
Cognitive Radio Networks have changed the communication paradigm by opportunistically using available spectrum. In such networks, Secondary User vacates the channel when it detects the Primary User. The frequent channel switching degrades the throughput of Cognitive Radio Networks. Current schemes suggest only the selection of Primary Channel if there is not any licensed user available. We propose...
The suppression of random interference nulling for uniform circular array using an improved binary coding method is investigated in this paper, which is based on Genetic Algorithm (GA) applied to smart antenna beamforming. The code lengths of the algorithm's least amplitude significant bits and least phase significant bits are analyzed, and their impacts on algorithm's performance are discussed. As...
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