Advancements of MultiRate Signal processing for Wireless Communication Networks: Current State Of the Art

With the hasty growth of internet contact and voice and information centric communications, many contact technologies have been urbanized to meet the stringent insist of high speed information transmission and viaduct the wide bandwidth gap among ever-increasing high-data-rate core system and bandwidth-hungry end-user complex. To make efficient consumption of the limited bandwidth of obtainable access routes and cope with the difficult channel environment, several standards have been projected for a variety of broadband access scheme over different access situation (twisted pairs, coaxial cables, optical fibers, and unchanging or mobile wireless admittance). These access situations may create dissimilar channel impairments and utter unique sets of signal dispensation algorithms and techniques to combat precise impairments. In the intended and implementation sphere of those systems, many research issues arise. In this paper we present advancements of multi-rate indication processing methodologies that are aggravated by this design trend. The thesis covers the contemporary confirmation of the current literature on intrusion suppression using multi-rate indication in wireless communiquE9; networks

Identification of linear periodically time-varying (LPTV) systems

A linear periodically time-varying (LPTV) system is a linear time-varying system with the coefficients changing periodically, which is widely used in control, communications, signal processing, and even circuit modeling. This thesis concentrates on identification of LPTV systems. To this end, the representations of LPTV systems are thoroughly reviewed. Identification methods are developed accordingly. The usefulness of the proposed identification methods is verified by the simulation results. A periodic input signal is applied to a finite impulse response (FIR)-LPTV system and measure the noise-contaminated output. Using such periodic inputs, we show that we can formulate the problem of identification of LPTV systems in the frequency domain. With the help of the discrete Fourier transform (DFT), the identification method reduces to finding the least-squares (LS) solution of a set of linear equations. A sufficient condition for the identifiability of LPTV systems is given, which can be used to find appropriate inputs for the purpose of identification. In the frequency domain, we show that the input and the output can be related by using the discrete Fourier transform (DFT) and a least-squares method can be used to identify the alias components. A lower bound on the mean square error (MSE) of the estimated alias components is given for FIR-LPTV systems. The optimal training signal achieving this lower MSE bound is designed subsequently. The algorithm is extended to the identification of infinite impulse response (IIR)-LPTV systems as well. Simulation results show the accuracy of the estimation and the efficiency of the optimal training signal design

Performance analysis of FBMC over OFDM in Cognitive Radio Network

Cognitive Radio (CR) system is an adaptive, reconfigurable communication system that can intuitively adjust its parameters to meet users or network demands. The major objective of CR is to provide a platform for the Secondary User (SU) to fully utilize the available spectrum resource by sensing the existence of spectrum holes without causing interference to the Primary User (PU). However, PU detection has been one of the main challenges in CR technology. In comparison to traditional wireless communication systems, due to the Cross-Channel Interference (CCI) from the adjacent channels used by SU to PU, CR system now poses new challenges to Resource Allocation (RA) problems. Past efforts have been focussed on Orthogonal Frequency Division Multiplexing (OFDM) based CR systems. However, OFDM technique show various limitations in CR application due to its enormous spectrum leakage. Filter Bank based Multicarrier (FBMC) has been proposed as a promising Multicarrier Modulation (MCM) candidate that has numerous advantages over OFDM. In this dissertation, a critical analysis of the performance of FBMC over OFDM was studied, and CR system was used as the testing platform. Firstly, the problem of spectrum sensing of OFDM based CR systems in contrast to FBMC based were surveyed from literature point of view, then the performance of the two schemes was analysed and compared from the spectral efficiency point of view. A resource allocation algorithm was proposed where much attention was focused on interference and power constraint. The proposed algorithms have been verified using MATLAB simulations, however, numerical results show that FBMC can attain higher spectrum efficiency and attractive benefit in terms of spectrum sensing as opposed to OFDM. The contributions of this dissertation have heightened the interest in more research and findings on how FBMC can be improved for future application CR systems

Measurements, Models, Systems and Design

531 s.

Blind LPTV joint equalization and interference suppression

The problem of jointly equalizing a digital communication signal distorted by a linear time-invariant channel and rejecting co-channel or adjacent-channel digital interference is tackled. Owing to the presence of the interfering signal, the proposed optimum linear MMSE equalizer turns out to be periodically time-varying (LPTV). Moreover, new simple and effective blind channel identification procedures are presented, which can be applied as long as the desired and interfering signal exhibit different circularity and/or cyclo-stationarity properties. Simulation results confirm the effectiveness of the proposed techniques