Cognitive network downlink resource allocation method based on LTE (long term evolution)

Abstract

The invention relates to a cognitive network downlink resource allocation method based on LTE (long term evolution). The method comprises steps as follows: equally allocating subcarriers in proportion; allocating the power of each user; allocating the power of each user on each subcarrier with a water injection method. According to the method, the subcarriers are allocated firstly, then subcarrier power is allocated through linear time complexity calculation, the equal proportionality principle is considered finally, meanwhile, total transmitted power constraint and master user interference threshold constraint of a system are satisfied, and the capacity of the system is maximized.

Description

technical field [0001] The present invention relates to the technical field of cognitive radio system resource allocation, in particular to an LTE-based cognitive network downlink resource allocation method. Background technique [0002] With the explosive growth of smart mobile terminals, the majority of mobile terminal users have increasingly strong demands for broadband and ubiquitous Internet access. The ubiquitous and broadband wireless network access has become a major trend in the development of mobile communication systems. Following this trend, 3GPP (3rd Generation Partnership Project) launched the long-term evolution LTE (Long Term Evolution) of the wireless access network, aiming at providing high-speed network access services anytime and anywhere. On the other hand, after years of rapid development of mobile communication systems, there are many kinds of communication systems in the real network environment. Excessive communication systems cause frequency band ...

AI Technical Summary

Problems solved by technology

[0006] So far, most of the cognitive radio system resource allocation technologies are optimized to maximize the system capacity, and there are relatively few algorithms that consider the fairness among multiple cognitive users, and the joint subcarrier and carrier power allocation cannot be realized. optimization, therefore, it is necessary to study the optimal resource allocation algorithm based on fairness among cognitive users

[0007] In addition, most of the existing cognitive radio system resource allocation technologies require relatively high computational complexity, but in practical applications, especially in real systems, it is unlikely to explain the high computational complexity

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