New Methods for Fast Detection for Embedded Cognitive Radio

Abstract

Spectrum Sensing is an important part of Cognitive Radio (CR) process. It can be used to determine if a Primary User (PU) (i.e. a licensed user) is emitting or not in the communication channel. This paper presents and compares three types of FFT-based detection algorithms for LTE-Advanced (LTE-A) cellular network at Orthogonal Frequency Division Multiple Access (OFDMA) level. These detectors sense the usage of the minimum time-frequency called Resource Block (RB). They are also low latency detectors and they only need one particular Orthogonal Frequency Division Multiplexing (OFDM) symbol to detect the usage of one RB. The three new detectors are based respectively on energy, correlation, and one what will be called eogration which combines energy and correlation. We analyze them with the Fisher's ratio and simulations of hypothesis test. The computing complexity of these detectors is also theoretically analyzed to provide guidance for future implementations.