Computation‐constrained spectrum sensing in IoT‐based scenarios

As a key technology to discover idle spectrum in cognitive radio (CR) networks, classical spectrum sensing schemes mainly focus on the improvement of sensing accuracy and available throughput. However, both sensing performance and sensing complexity are significant elements that influence the performance of a CR in computation‐constrained scenarios. Motivated by this, theproposed study is devoted to computation‐constrained spectrum sensing and a tradeoff is considered between sensing performance and sensing complexity. First, the authors give two functions to evaluate the detection efficiency and communication efficiency of a CR. On this basis, two specific models are provided to obtain the optimal sensing operations in computation‐constrained conditions, respectively. Then they analyse these two models and conclude their advantages and disadvantages. Finally, simulation experiments validate the effectiveness of the proposed schemes. Note that computation‐constrained spectrum sensing works as a significant issue in the internet of things (IoT)‐based applications and the proposed schemes provide effective solutions for it.