Although the multiuser detection scheme based on Kalman filtering (K-MUD) proposed by Zhang and Wei, is referred to as a "blind" algorithm, in fact it is not really blind because it is conditioned on perfect knowledge of system parameter, power of the desired user. This paper derives an algorithm to estimate the power of the user of interest, and proposes a completely blind multiuser detection. Computer simulations show that the proposed parameter estimation scheme obtains excellent effect, and that the new detection scheme has nearly the same performance as the K-MUD, there is only slight degradation at very low input signal-to-interference ratios (SIR).

Ontologies are regarded as the solution to data heterogeneity on the Semantic Web (SW), but they also suffer from the heterogeneity problem, which leads to the ambiguity of data information. Ontology Meta-Matching technique (OMM) is able to solve the ontology heterogeneity problem through aggregating various similarity measures to find the heterogeneous entities. Inspired by the success of Reinforcement Learning (RL) in solving complex optimization problems, this work proposes a RL-based OMM technique to address the ontology heterogeneity problem. First, we propose a novel RL-based OMM framework, and then, a neural network that is called evaluated network is proposed to replace the Q table when we choose the next action of the agent, which is able to reduce memory consumption and computing time. After that, to better guide the training of neural network and improve the accuracy of RL agent, we establish a memory bank to mine depth information during the evaluated network's training procedure, and we use another neural network that is called target network to save the historical parameters. The experiment uses the famous benchmark in ontology matching domain to test our approach's performance, and the comparisons among Deep Reinforcement Learning(DRL), RL and state-of-the-art ontology matching systems show that our approach is able to effectively determine high-quality alignments.

The rapid hybrid acquisition of PN sequences is proposed for DS/CDMA systems. The system introduces the excision CFAR method into the background power estimation. A mathematical analysis is done for the single path and multipath environments. The detection performance of the proposed scheme is compared with that of other acquisition schemes. Results show that the proposed method has better detection performance if the excision coefficient is properly selected.

Excitation of plasmons on the surface of a metal grating placed in planar or conical mounting is investigated in detail. Most of the results of numerical computations are compared with experimental data. When a TM wave illuminates a metal grating, total or partial absorption of incident light occurs at angles of incidence at which the plasmon surface waves are excited. In planar mounting the absorption is generally strong and nearly total absorption is observed. While in conical mounting, it is not so strong as that in the planar mounting case and a considerable amount of incident power is reflected. This, however, is accompanied by enhanced TM-TE mode conversion and the greater part of the reflected wave is in the TE polarization. The reciprocal of the TM-wave efficiency, hence, is a practical measure in finding the angles of incidence at which the plasmons are excited. Because the angles are sensitive functions of the refractive index of a material over the grating surface, this phenomenon can be used as an index sensor.

Mobile virtual network operators (MVNOs) are mobile operators without their own infrastructure or government issued spectrum licenses. They purchase spectrum resources from primary mobile network operators (MNOs) to provide communication services under their own brands. MVNOs are expected to play an important role in mobile network markets, as this will increase the competition in retail markets and help to meet the demand of niche markets. However, with the rapidly increasing demand of mobile data traffic, efficient utilization of the limited spectrum resources owned by MVNOs has become an important issue. We propose here a resource sharing mechanism between MVNOs against the background of network functions virtualization (NFV). The proposed mechanism enables MVNOs to improve their quality of service (QoS) by sharing spectrum resources with each other. A nash bargaining solution based decision strategy is also devised to ensure the fairness of resource sharing. Extensive numerical evaluation results validate the effectiveness of the proposed models and mechanisms.