Optimal Power Control Method Based on Pricing in Cognitive Networks

Abstract

The invention provides an optimal power control method based on pricing in a cognitive network. The optimal power control method comprises the following steps: initiating the number of secondary users and tolerance factors; conducting descending order on the secondary users according to the tolerance factors of the secondary users; calculating judging factors of the secondary users; determining the magnitude relation of the judging factors and the tolerance factors, if the condition is met, giving the optimal power of the secondary users and a pricing method of a primary user, and completing the method; otherwise, setting the power of the secondary user with the lowest tolerance factor into zero, continuously executing operations on the other secondary users according to the fourth step, and giving the optimal power of the secondary users and the pricing method of the primary user. According to the optimal power control method based on pricing in the cognitive network, under the conditions that the primary user knows the tolerance factors of the secondary users and channel information of the whole cognitive network, a closed-form solution of the optimal power distribution of the secondary users and the optimal price of the primary user can be given through iteration with the frequencies not exceeding the total number of the secondary users.

Description

technical field [0001] The present invention relates to the technical field of power control in a cognitive network, in particular to a pricing-based optimal power control method in a cognitive network. Background technique [0002] Under the cognitive network, the secondary user can access the spectrum for data transmission by renting the spectrum of the primary user. In order to ensure its own quality of service and the incentive to obtain spectrum lease, the primary user can charge for the interference of the secondary user. First, the primary user sets a certain price for the unit interference power of each secondary user, and broadcasts the price to each secondary user; the secondary user controls its own power through a non-cooperative game based on the price. This interaction between primary users and secondary users can be analyzed by Stackelberg game. Since the pricing of the primary user will affect the power of the secondary user, thereby affecting its own incom...

AI Technical Summary

Problems solved by technology

Since the algorithm decouples the mutual interference between the secondary users by taking the worst-case interference of the secondary users, thereby ignoring the mutual interference links between the secondary users, the power control method obtained by this pricing method is suboptimal , and cannot maximize the main user's income

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