Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Fuzzy Logic Control for Multiresolutive Adaptive PN Acquisition Scheme in Time-Varying Multipath Ionospheric Channel

Communication with remote places is a challenge often solved using satellites. However, when trying to reach Antarctic stations, this solution suffers from poor visibility range and high operational costs. In such scenarios, skywave ionospheric communication systems represent a good alternative to satellite communications. The Research Group in Electromagnetism and Communications (GRECO) is designing an HF system for long haul digital communication between the Antarctic Spanish Base in Livingston Island (62.6S, 60.4W) and Observatori de l’Ebre in Spain (40.8N,0.5E) (Vilella et al., 2008). The main interest of Observatori de l’Ebre is the transmission of the data collected from the sensors located at the base, including a geomagnetic sensor, a vertical incidence ionosonde, an oblique incidence ionosonde and a GNSS receiver. The geomagnetic sensor, the vertical incidence ionosonde and the GNSS receiver are commercial solutions from third parties. The oblique incidence ionosonde, used to sound the ionospheric channel between Antarctica and Spain, was developed by the GRECO in the framework of this project. During the last Antarctic campaign, exhaustive measurements of the HF channel characteristics were performed, which allowed us to determine parameters such as availability, SNR, delay and Doppler spread, etc. In addition to the scientific interest of this sounding, a further objective of the project is the establishment of a backup link for data transmission from the remote sensors in the Antarctica. In this scenario, ionospheric communications appear to be an interesting complementary alternative to geostationary satellite communications since the latter are expensive and not always available from high-latitudes. Research work in the field of fuzzy logics applied to the estimation of the above mentioned channel was first applied in (Alsina et al., 2005a) for serial search acquisition systems in AWGN channels, afterwards applied to the same channel but in the multiresolutive structure (Alsina et al., 2009a; Morán et al., 2001) in papers (Alsina et al., 2007b; 2009b) achieving good results. In this chapter the application of fuzzy logic control trained for Rayleigh fading channels (Proakis, 1995) with Direct-Sequence Spread-Spectrum (DS-SS) is presented, specifically suited for the ionospheric channel Antarctica-Spain. Stability and reliability of the reception, which are currently being designed, are key factors for the reception. It is important to note that the fuzzy control design presented in this chapter not only resolves the issue of improving the multiresolutive structure performance presented by (Morán et al., 2001), but also introduces a new option for the control design of many LMS adaptive structures used for PN code acquisition found in the literature. (El-Tarhuni & Sheikh, 1996) presented an LMS-based system to acquire a DS-SS system in Rayleigh channels; years after, (Han et al., 2006) improved the performance of the acquisition system designed by (El-Tarhuni & Sheikh, 1996). And also in other type of channels, LMS filters are used as an acquisition system, even in oceanic transmissions (Stojanovic & Freitag, 2003). Although the fuzzy control system presented in this chapter is compared to the stability control used in (Morán et al., 2001) it also can be used to improve all previous designs performance in terms of stability and robustness. Despite this generalization, the design of every control system should be done according to the requirements of the acquisition system and the specific channel characteristics

Spread Spectrum Watermarking: Principles and Applications in Fading Channel

ISBN 978-953-51-0618-

Pilot-aided estimation and equalisation of a Radio-over-Fibre system in Wideband Code Division Multiple Access

In this study, the impact of a Radio-over-Fibre (RoF) subsystem on the capacity performance of wideband code division multiple access is evaluated. This study investigates the use of pilot-aided channel estimation to compensate for the optical subsystem non-linearities for different channel conditions, estimation intervals and coding schemes. The results show that pilot-aided channel estimation is an effective method for compensating the composite impairments of the optical subsystem and the radio frequency (RF) channel. It is found that there is always a suitable pilot power level which maximises the system capacity performance regardless of coding scheme and channel condition. Also, the peak capacity is only slightly affected by a decrease in the estimation interval

Multilane traffic density estimation with KDE and nonlinear LS and tracking with Scalar Kalman filtering

Tezin basılısı, İstanbul Şehir Üniversitesi Kütüphanesi'ndedir.With increasing population, the determination of traffic density becomes very critical in managing the urban city roads for safer driving and low carbon emission. In this study, Kernel Density Estimation is utilized in order to estimate the traffic density more accurately when the speeds of the vehicles are available for a given region. For the proposed approach, as a first step, the probability density function of the speed data is modeled by Kernel Density Estimation. Then, the speed centers from the density function are modeled as clusters. The cumulative distribution function of the speed data is then determined by Kolmogorov-Smirnov Test, whose complexity is less when compared to the other techniques and whose robustness is high when outliers exist. Then, the mean values of clusters are estimated from the smoothed density function of the distribution function, followed by a peak detection algorithm. The estimation of variance values and kernel weights, on the other hand, are found by a nonlinear Least Square approach. As the estimation problem has linear and non-linear components, the nonlinear Least Square with separation of parameters approach is adopted, instead of dealing with a high complexity nonlinear equation. Finally, the tracking of former and latter estimations of a road is calculated by using Scalar Kalman Filtering with scalar state - scalar observation generality level. Simulations are carried out in order to assess theperformanceoftheproposedapproach. Forallexampledatasets, theminimummean square error of kernel weights is found to be less than 0.002 while error of mean values is found to be less than 0.261. The proposed approach was also applied to real data from sample road traffic, and the speed center and the variance was accurately estimated. By using the proposed approach, accurate traffic density estimation is realized, providing extra information to the municipalities for better planning of their cities.Declaration of Authorship ii Abstract iii Öz iv Acknowledgments vi List of Figures ix List of Tables x Abbreviations xi 1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Methods to Find Probability Density Function and Cumulative Distribution Function . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 1.3 Traffic Density Estimation with Kernel Density Estimation . . . . . . . . 4 1.4 The Approaches for Determination of Key Parameters of Traffic Density Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . .5 1.5 Tracking between Estimated Data and New Data . . . . . . . . . . . . . . 6 1.6 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2 Literature Review 7 2.1 Methodologies Used for Estimation of Traffic Density . . . . . . . . . . . . 7 2.2 An Example Study of Traffic Density Estimation with KDE and CvM . . 9 2.3 Three Complementary Studies for Traffic Density Estimation and Tracking 9 2.4 Comparison of Three Different Nonlinear Estimation Techniques on the Same Problem . . . . . . . . . . . . . . . . . . . . . . . . .10 2.4.1 A Maximum Likelihood Approach for Estimating DS-CDMA Multipath Fading Channels . . . . . . . . . . . . . . . . . . . . . . . . 12 2.4.2 Channel Estimation for the Uplink of a DS-CDMA System . . . . 12 2.4.3 A Robust Method for Estimating Multipath Channel Parameters in the Uplink of a DS-CDMA System. . . . . . . . . . . . . . .13 3 The Model 16 3.1 Finding Density Distribution with KDE . . . . . . . . . . . . . . . . . . . 16 3.2 Finding Empirical CDF with KS Test . . . . . . . . . . . . . . . . . . . . 18 3.3 Determination of Speed Centers via PDA . . . . . . . . . . . . . . . . . . 20 3.4 Estimation of Variance and Kernel Weights with Nonlinear LS Method . . 21 3.5 Tracking of Traffic Density Estimation with Scalar Kalman Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4 Numerical Calculations for Traffic Density Estimation 26 4.1 An Example Traffic Scenario with Five Speed Centers . . . . . . . . . . . 26 4.2 The Estimation of A Real Time Data . . . . . . . . . . . . . . . . . . . . . 29 4.3 Traffic Density Estimation with Different Kernel Numbers . . . . . . . . . 29 5 Examples to Test Tracking Part of the Model 31 5.1 Tracking with the Change only in Mean Values . . . . . . . . . . . . . . . 32 5.2 Tracking with the Change only in Kernel Weights . . . . . . . . . . . . . . 35 5.3 Tracking with the Change in All Three Parameters . . . . . . . . . . . . . 36 6 Assesment 38 7 Conclusion 41 A Derivation of Newton-Raphson Method for the Estimation of Variance Values and Kernel Weights 43 Bibliography 4

Cancellation Techniques for Co-channel Interference in MIMO-OFDM Systems and Evaluating Their Performance

In a wireless communication system, the transmitted signal is exposed to various surfaces where it bounces and results in several delayed versions of the same signal at the receiver end. The delayed signals are in the form of electromagnetic waves that are diffracted and reflected from the various object surfaces. These result in co-channel interferences for wireless systems. MIMO has proven to be a striking solution for the new generation of wireless systems. MIMO-OFDM system with QPSK modulation is considered as the wireless system for studying the performance of interference cancellation techniques. The BER performance is studied in channels such as Rayleigh and Rician Fading Channels. The effects of interference are reduced to a certain extent by the inclusion of CDMA (spread spectrum technique) as Technique 1. The effects of interference on this system have been further reduced using the LMS filter as Technique 2. Hence, to show better performance in MIMO-OFDM systems, it is recommended to employ both CDMA and LMS filters to decrease the effects of co-channel interference. It is observed that the parameter BER reduces as the SNR increases for both these channels. Doi: 10.28991/esj-2021-01313 Full Text: PD

Performance Evaluation of Maximal Ratio Receiver Combining Diversity with Prime Interleaver for Iterative IDMA Receiver

The antenna diversity mechanism is established as the well known mechanism for reduction of probability of occurrence of communication failures (outages) caused by fades. In receiver diversity, multiple antennas are employed at the receiver side in case of transmitter diversity, multiple antennas are the integral part of transmitter section.. In this paper, Maximal Ratio Receiver Combining (MRRC) diversity technique is evaluated to mitigate the effect of fading in IDMA scheme employing random interleaver and prime interleaver with single transmit two receiving antennas in low rate coded environment. For the performance evaluation, channel is assumed to be Rayleigh multipath channel with BPSK modulation. Simulation results demonstrate the significant improvement in BER performance of IDMA with maximal ratio receiver combining (MRRC) diversity along with prime interleaver and random interleaver and it has also been observed that BER performance of prime interleaver is similar to that of random interleaver with reduced bandwidth and memory requirement at transmitter and receiver side. Keywords: Multipath Fading, MRRC diversity, Multi user detection, Interleave-Division Multiple Access (IDMA) Scheme, Random Interleaver, Prime Interleave