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Symbol G represents the density of the mobile crowd network.
Then the mobile crowd network system is proposed.
Fig. 1 Mobile crowd network for electronic commerce recommendation.
Section 3 studies the signal detection scheme for mobile crowd network.
Finally, the network signal is detected by the signal detection of the mobile crowd network.
Mobile crowd network signal detection strength is expressed in formula (5).
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After the completion of the cloud-assisted QoE guarantee, the mobile crowding network is divided into active user nodes and alternative user nodes.
These results show that the proposed algorithm can be used to mobile crowding network, which has the advantages of high reliability, fast convergence, and global optimization.
Based on the current demand for data services, the mobile nodes of mobile crowding network can be adaptively adjusted, which would guarantee the Quality of Experience of mobile nodes.
For guaranteeing the system performance of the mobile crowding network, based on updating the perceptron network, the mobile nodes should be an effective incentive which should satisfy the conditions and performance requirements.
According to the deployment of n mobile nodes in the mobile crowding network, the mobile node state is defined as M (P, D, L N), where P denotes the transmit power, D represents the distance, and L N represents the perception layer of the mobile node.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com