Joint authorized user perception and link state estimation method and device

Abstract

Aiming at the problem of spectrum sensing in cognitive radio, the present invention designs a joint spectrum sensing and link state estimation method device. This method for the first time incorporates a link state information between the primary user and the secondary user as another hidden state in spectrum sensing, and thus establishes a general dynamic state space model; based on Bayesian Based on the sequential estimation framework and Bernoulli random finite set theory, a Bernoulli filtering mechanism is designed, which can obtain the joint blind estimation of the primary-secondary link state information while sensing and detecting the working status of the licensed frequency band (algorithm process has been Attached). The method makes full use of the primary-secondary link state information, thereby significantly improving spectrum sensing performance; at the same time, the obtained primary-secondary link state information can also be used for subsequent resource optimization; in addition, the joint user perception and The method and device for estimating link state information is versatile and can be extended to other primary-secondary link state information.

Description

technical field [0001] Aiming at the problem of licensed spectrum sensing in cognitive radios (CRs), the present invention designs and proposes a new joint licensed spectrum sensing and link state estimation method, so it can be called deep sensing (deepsensing). While detecting authorized users, the link state information (primary to secondary link state, PS-LSI) between unknown authorized users and secondary users is taken into consideration, and a dynamic space state model (discrete state-space model) is established. , DSM); the above authorized user perception and joint link state estimation problem is modeled as a Bernoulli random finite state (BRFS), and a Bernoulli filtering mechanism is designed to sense and detect the licensed frequency band At the same time, the joint blind estimation of PS-LSI is realized. The method and device have sufficient scalability and can handle any PS-LSI (such as time-varying channel gain). belongs to the field of communication. Backgr...

AI Technical Summary

Problems solved by technology

However, in practice, the unknown PS-LSI will increase the received signal uncertainty, which in turn will negatively affect the spectrum sensing performance

Especially considering the actual time-varying fading channel, the dynamic channel gain that changes with time will greatly increase the difficulty of detection, resulting in poor spectrum sensing performance

Although the existing literature considers the statistical probability distribution function (probability density function, PDF) of channel fading, and reduces the negative impact of random fading to a certain extent through the idea of ​​marginalization; however, the statistical probability distribution can only reflect the instantaneous randomness of fading Behavior, can not describe the relevant time-varying migration properties, so it is impossible to track the time-varying channel in real time, so its detection performance is still unacceptable

Images