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In this paper, a spectrum sharing cognitive radio(CR) multiple input and single output (MISO) system is considered, which consists of a secondary user (SU) having multiple transmit antennas and a single receive antenna and a primary user (PU) have a single receive antenna. The channel state information (CSI) on the link between SU and PU is assumed to be perfectly known at the SU transmitter (SU-Tx)...
This paper investigates the sum rate capacity of MIMO broadcast channels (MIMO-BCs) in cognitive radio (CR) networks. An efficient algorithm is proposed for selecting a set of users to achieve a high sum rate capacity of the system. With the above algorithm, the sum rate capacity of MIMO-BCs in CR networks with average interference power constraints and transmit power constraints is derived. We formulate...
Cognitive Radio (CR) has attracted much attention for its ability allowing secondary users (SUs) to share the spectrum with licensed users (PUs). The precondition that PUs bear the coexistence of SUs is that the interference caused by SUs should be under a given threshold. Therefore the main challenge of CR is interference control or even interference cancellation. In this work we employ zero-forcing...
A novel transformer insulation fault diagnosis method is proposed based on a decision tree in this paper. In terms of history samples library of transformer faults, the method applies entropy-based information gain as heuristic information to select test attributes, and uses ID3 algorithm to generate the decision tree. Then, pruning in the tree to eliminate noises, and distilling classification rules...
Chaotic optimization is a new optimization technique. Conventional two-dimension chaotic sequence is not a good way to two-dimension gray histogram image segmentation because it is proportional distributing in [0,1] times [0,1]. In order to generate a better chaotic sequence that is fit to two- dimension gray histogram. A chaotic sequence generating method is proposed based on Arnold chaotic system...
This paper presents an optimization mechanism to facilitate efficient selection of BGP egress for an AS, when IGP link state changes. Most mechanisms for BGP egress selection have primarily focused on achieving an optimized goal by considering it as a static problem, which leads to inflexibility to variations in the topology of an AS, especially for link failures which often occur in an AS network...
The paper demonstrates that radial basis function network (RBFN) with adaptive centers and width can be used effectively for identification of nonlinear dynamic system. The proposed RBFN is trained by hybrid learning algorithm, which uses conjugate gradient optimization algorithm to obtain the center and width of each radial basis function and the least squares method to obtain the weights. To avoid...
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