RLNC-based back-off frequency spectrum prediction method in CR network

Abstract

The invention discloses a random-linear-network-code (RLNC)-based back-off frequency spectrum prediction method in a cognitive radio (CR) network. With utilization of frequency spectrum predictability caused by RLNC introduction into a main user channel of cognitive radio and a prediction effect on a frequency spectrum by a hidden markov model, a back-off prediction method is introduced to carry out frequency spectrum state prediction at a next time slot. With the method, defects that frequency spectrum state is switched frequently and the spectrum hole can not be sensed easily in the traditional CR network and the reliability is low of the existing frequency spectrum prediction algorithm can be overcome. With introduction of back-off prediction method, the frequency spectrum state prediction at a next time slot is carried out by using the frequency spectrum predictability caused by RLNC introduction into the cognitive radio network and the prediction effect on the frequency spectrum by the hidden markov model, so that frequency spectrum prediction reliability is improved.

Description

technical field [0001] The invention relates to the field of frequency spectrum prediction in cognitive radio networks, in particular to a backoff spectrum prediction method based on random linear network coding in cognitive radio networks. Background technique [0002] With the rapid development of wireless communication technologies such as mobile Internet and smart mobile terminals, the demand for spectrum resources in wireless communication systems has increased sharply. However, under the fixed spectrum allocation method, spectrum resources are limited, and the contradiction between spectrum supply and demand has become increasingly prominent. Therefore, The increasing scarcity of spectrum resources has become a new bottleneck restricting the development of wireless communications. However, while spectrum resources are scarce, the fixed spectrum allocation method also leads to a great waste of spectrum resources. According to the work report of the Federal Communicatio...

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Problems solved by technology

[0005] In summary, aiming at the problems of frequent spectrum state transitions and the low reliability of existing spectrum prediction algorithms, the present invention combines the predictive effect of hidden Markov models on spectrum and introduces random linear network coding (Random Linear Network Coding) into cognitive radio networks. Network Coding, RLNC) brings spectrum predictability, and proposes a backoff spectrum prediction method based on random linear network coding in cognitive radio networks, aiming to achieve reliable prediction of spectrum status

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