Nonlinear Channel Equalization Approach for Microwave Communication Systems

The theoretical principles of intersymbol interference (ISI) and channel equalization in wireless communication systems are addressed. Several conventional and well-known equalization techniques are discussed and compared such as zero forcing (ZF) and maximum likelihood (ML). The main section in this chapter is devoted to an abstract concept of equalization approach, namely, dual channel equalization (DCE). The proposed approach is flexible and can be employed and integrated with other linear and nonlinear equalization approaches. Closed expressions for the achieved signal-to-noise ratio (SNR) and bit error rate (BER) in the case of ZF-DCE and ML-DCE are derived. According to the obtained outcomes, the DCE demonstrates promising improvements in the equalization performance (BER reduction) in comparison with the conventional techniques

Analyzing Chaos Systems and Fine Spectrum Sensing Using Detrended Fluctuation Analysis Algorithm

A numerical study that uses detrended fluctuation analysis (DFA) algorithm of time series obtained from linear and nonlinear dynamical systems is presented. The DFA algorithm behavior toward periodic and chaotic signals is investigated and the effect of the time scale under analysis is discussed. The displayed results prove that the DFA algorithm response is invariant (stable performance) to initial condition and chaotic system parameters. An initial idea of DFA algorithm implementation for fine spectrum sensing (SS) is proposed under two-stage spectrum sensor approach with test statistics based on the scaling exponent value. The outcomes demonstrate a promising new SS technique that can alleviate several imperfections such as noise power uncertainty and spatial correlation between the adjacent antenna array elements

Antenna Arrays and Beam-formation

Spatial processing and smart antenna beam formation are considered as completely essential approaches to be employed for forthcoming progress in the standards and implementation of the wireless communication systems. The book aims, besides introducing up-to-date contributions that are not readily available in the related literature, to present and demonstrate the recent research ideas in the field of antenna array design and beam-forming algorithms in a synthetic, coherent, and unified manner for the interested researchers. The presented topics range from relatively straightforward mathematical analysis and derivations to simulation and empirical results. The book is designed to serve as an informative reference for the researcher involved in the analysis of the spatial signal processing techniques for smart antenna systems. The book will help the readers, in particular wireless communication researchers, to have wider futuristic and innovative visions for the advances in the field

Spectrum Sensing under Correlated Antenna Array Using Generalized Detector in Cognitive Radio Systems

We derive the probability of false alarm and detection threshold under employment of the generalized detector (GD) in cognitive radio (CR) systems for two scenarios: firstly, the independent antenna array elements; the secondly, the correlated antenna array elements. The energy detector (ED) and GD spectrum sensing performances are compared under the same initial conditions. The simulation results show that implementation of the GD improves the spectrum sensing performance in CR systems both for independent and correlated antenna array elements

SNR Wall Effect Alleviation by Generalized Detector Employed in Cognitive Radio Networks

The most commonly used spectrum sensing techniques in cognitive radio (CR) networks, such as the energy detector (ED), matched filter (MF), and others, suffer from the noise uncertainty and signal-to-noise ratio (SNR) wall phenomenon. These detectors cannot achieve the required signal detection performance regardless of the sensing time. In this paper, we explore a signal processing scheme, namely, the generalized detector (GD) constructed based on the generalized approach to signal processing (GASP) in noise, in spectrum sensing of CR network based on antenna array with the purpose to alleviate the SNR wall problem and improve the signal detection robustness under the low SNR. The simulation results confirm our theoretical issues and effectiveness of GD implementation in CR networks based on antenna array