Analysing Primary Signal Sensing Test in Cognitive Radio Networks Using an Alpha-Beta Filter and a Neyman-Pearson Detector

Abstract

The signal strength sensing in the context of cognitive radio networks (CRNs), is very important to predict the primary signal of base station (PBS), particularly when the secondary user (SU) is in a congested environment, and also when is in motion towards the end of coverage of PBS. However, this article presents an analysis on the prediction of primary signal strength in CRNs using an Alpha-Beta Filter (ABF) and a Neyman-Pearson Detector (NPD). The challenge of this contribution is based on a realistic sensing of primary signal strength and to do that, we have assumed that the reporting channels between the SU and the PBS are composited with the shadowing and multipath fading (SMF), and the receiver noise has also added. In this regard, the obtained results were discussed through: the signal-to-noise ratio (SNR) uncertainty, the detection probability (PD) and the False Alarm Probability (PFA), where the average relative error of prediction for the PD will be equal to10-5.

Hybrid Approach to Design of Two Dimensional Stable IIR Digital Filter

“…We have to minimize the functional (4), the aim is to minimize the difference between current and desired magnitude response of the 2-D filter in N 1 ×N 2 points. Since the denominator only contains first-degree factors, we can asseverate the stability conditions as the constraints [1,3]. It is renowned also that a linear, causal, shiftinvariant, single-input, single-output, discrete variables 2-D system is BIBO (Bounded Input Bounded Output) stable if and only if its output is bounded when the input is bounded and the initial conditions are zero.…”

“…A great number of research works have been published in academic journals on the design of 2-D digital filters in the last 20 years. Design techniques for 2-D filters can be widely arranged into two categories: the first based on convenient transformation of 1-D filters [3,5] and the second one based on appropriate optimization techniques [5]. The heuristic methods have been employed to design the 2-D IIR filter, such as neural networks [6], genetic algorithm [7] and the computer language GENETICA [8].…”