Modeling and Comparison of Primary User Detection Techniques in Cognitive Radio Networks

Abstract

In this paper, we investigate the problem of spectrum sensing in cognitive radio networks. Compared with related work that aims to propose techniques at different layers of the network protocol stack for detecting primary users, we aim to investigate the capabilities and limitations of different primary user detection techniques from the perspective of network optimization. The goal is to understand the fundamental performance tradeoffs of different primary user detection techniques without being limited by existing cognitive radio software and hardware platforms. To proceed, we first identify several dimensions for designing primary user detection techniques in cognitive radio networks, and then formulate primary user detection techniques using mixedinteger nonlinear programming (MINLP). Evaluation results show the benefits of using the proposed optimization framework for profiling the fundamental characteristics of primary user detection techniques.

Cognitive-Radio Systems for Spectrum, Location, and Environmental Awareness

“…Several single-antenna spectrum-sensing techniques were proposed in [15][16][17][18][19][20][21][22][23][24][25]. As discussed in [13,14], there are three common techniques for detection of spectrum opportunities: energy detectors, autocor relation detectors, and cyclic autocorrelation detectors. As illus trated in Figure 2, an energy-detector receiver at SU-2 is a com mon spectrum-sensing method for determining the spectrum opportunities.…”

“…Relying on the fact that spectrum awareness (i.e., sensing, shaping, learning, and optimization) is one of the most crucial features of cognitive-radio systems, a significant portion of the studies in the literature focused on spectrum awareness and related issues [6][7][8][9][10][11][12]. Energy detectors, autocorrelation detectors, and cyclic autocorrelation detectors are three common techniques in the literature for detection of spectrum opportunities [13,14]. Various approaches for spectrum sensing in cognitive-radio sys tems have been proposed in the literature.…”

Cognitive strategies for security in wireless sensor networks

“…However, they use the spectrum sensing information in order to generate the behavior pattern of the node transmissions. For example, in [66], the PU modeling problem is studied. The model is used to look for differences between a PU and attackers.…”

“…2 PUE attack is one of the most important new attacks in CR. PUE attack has been modelled in cognitive scenarios[66,62]. Chen and Park are the first researches that classify the PUE attacks in two different categories depending of their objective: Selfish PUE attacks.…”