Allying method for acknowledging radio communication alliance

Abstract

The invention discloses an allying method for acknowledging a radio communication alliance. The allying method comprises the following steps of: firstly putting forward an establishing method of a communication alliance model based on an RSSI (Received Signal Strength Indication) type cellular topology structure by introducing an alliance game idea, and taking throughput of a maximization system as a solving target of the communication alliance mode; and configuring a layered management mode of first-level base station management and second-level base station management through alliance by an acknowledgement node, and optimizing signaling cost of the system so that the acknowledging node can directly interact signaling with a leader of an alliance by less power without needing of executing signaling interaction with the base station at each time. By establishing a user service triggering mechanism, the throughput of the system is further increased.

Description

technical field [0001] The invention relates to an alliance method for a cognitive radio communication alliance, which belongs to the technical field of cognitive radio. Background technique [0002] With the continuous development of society, the rapid development of science and technology, and the rapid popularization of the Internet of Things, wireless spectrum resources are becoming more and more tense. In this context, cognitive radio (Cognitive Radio, CR) technology emerges as the times require. CR technology can effectively alleviate or solve the above-mentioned shortage of spectrum resources by making full use of idle spectrum resources in time and space. [0003] Cognitive radio, also known as smart radio, is characterized by flexibility, intelligence, and reconfigurability. By sensing the external environment and using artificial intelligence technology to learn from the environment, it can purposefully change certain operating parameters in real time (such as tran...

AI Technical Summary

Problems solved by technology

However, we found that distance-based cognitive sub-user alliances do not consider the transmission efficiency of cognitive sub-users on the channel at this distance. For example, a cognitive sub-user A is closer to cognitive sub-user B than C, A and B formed an alliance after judging by the alliance criterion, but did not establish an alliance with C, but the actual situation may be that the transmission efficiency of the channel between A and B is not as high as that between A and C (the transmission channel gain is large)

For this reason, most of the existing research results are to calculate the channel transmission loss by obtaining a suitable model (such as Hata model or okumuma model, etc.) and corresponding parameters to describe the channel, and then determine whether to form an alliance. Although this can partially solve the above problems, However, it increases the error caused by the mismatch of the channel model and the complexity of the algorithm, which is undoubtedly a major drawback for communication alliances that have high requirements for time complexity.

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