Time Optimal Spectrum Sensing

TL;DR

This paper proposes a novel approach to spectrum sensing in cognitive radio by dynamically allocating scanning time based on historical traffic data, formulated as an optimization problem to improve efficiency.

Contribution

It introduces a new method that uses historical spectrum traffic information and formulates the time allocation as an integer linear programming problem.

Findings

Optimized spectrum scanning time improves efficiency.

Formulation as an integer linear programming problem.

Utilizes historical traffic data for better spectrum sensing.

Abstract

Spectrum sensing is a fundamental operation in cognitive radio environment. It gives information about spectrum availability by scanning the bands. Usually a fixed amount of time is given to scan individual bands. Most of the times, historical information about the traffic in the spectrum bands is not used. But this information gives the idea, how busy a specific band is. Therefore, instead of scanning a band for a fixed amount of time, more time can be given to less occupied bands and less time to heavily occupied ones. In this paper we have formulated the time assignment problem as integer linear programming and source coding problems. The time assignment problem is solved using the associated stochastic optimization problem.