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Table Of Integrals Series And Products

A fast-Fourier-transform method of topography and interferometry is proposed. By computer processing of a noncontour type of fringe pattern, automatic discrimination is achieved between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour-generation techniques. The method has advantages over moire topography and conventional fringe-contour interferometry in both accuracy and sensitivity. Unlike fringe-scanning techniques, the method is easy to apply because it uses no moving components.

Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry

Matrix Differential Calculus with Applications in Statistics and Econometrics

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The World Bank Group

Radio access technologies for cellular mobile communications are typically characterized by multiple access schemes, e.g., frequency division multiple access (FDMA), time division multiple access (TDMA), code division multiple access (CDMA), and OFDMA. In the 4th generation (4G) mobile communication systems such as Long-Term Evolution (LTE) (Au et al., Uplink contention based SCMA for 5G radio access. Globecom Workshops (GC Wkshps), 2014. doi:10.1109/GLOCOMW.2014.7063547) and LTE-Advanced (Baracca et al., IEEE Trans. Commun., 2011. doi:10.1109/TCOMM.2011.121410.090252; Barry et al., Digital Communication, Kluwer, Dordrecht, 2004), standardized by the 3rd Generation Partnership Project (3GPP), orthogonal multiple access based on OFDMA or single carrier (SC)-FDMA is adopted. Orthogonal multiple access was a reasonable choice for achieving good system-level throughput performance with simple single-user detection. However, considering the trend in 5G, achieving significant gains in capacity and system throughput performance is a high priority requirement in view of the recent exponential increase in the volume of mobile traffic. In addition the proposed system should be able to support enhanced delay-sensitive high-volume services such as video streaming and cloud computing. Another high-level target of 5G is reduced cost, higher energy efficiency and robustness against emergencies.

Non-Orthogonal Multiple Access (NOMA) for cellular future radio access

In this article, we propose an ordered multi-branch (OMB) processing for successive interference cancellation (SIC) based symbol vector detection techniques in multiple-input multiple-output (MIMO) spatial multiplexing systems. In the proposed method multiple ordered branches are initiated in parallel where each branch employ SIC based detection with different ordering pattern. To generate multiple branches, in the proposed work, first we consider channel norm (ChN) and log likelihood ratio (LLR) based orderings of the detection sequence, and then difference in the values of ChN and/or LLR of consecutive layers are used. Each branch produces an estimate of the transmitted symbol vector and the best one is selected by using the maximum likelihood (ML) rule. To improve the accuracy of decisions in each branch and achieve a better performance, we also incorporate multiple feedback (MF) strategy based SIC algorithm for symbol vector detection in MIMO systems. Since, all branches process the input vector independently, the proposed algorithm is well suited (in terms of processing speed) for parallel processing receiver architectures. The bit error rate (BER) performance and the computational complexity of the proposed technique is computed, and compared with SIC and multiple feedback SIC (MF-SIC) based MIMO detection algorithms. Simulation results reveal that the proposed methods outperform SIC and MF-SIC algorithms, and achieve near ML performance with less computational complexity.

Ordered multi-branch processing for successive interference cancellation based MIMO detection

AbstractThe explosive growth of wireless subscribers and high data rate demanding multimedia services have pushed the fourth-generation (4G) network to improve and adapt to the emerging issues. This has led to the evolution of cutting-edge fifth-generation (5G) wireless networks. Few of the well-known techniques for boosting 5G networks are non-orthogonal multiple access (NOMA), small cell deployment (a.k.a. HetNets), millimeter-wave (mmWave) communications, intelligent reflecting surfaces (IRSs), etc. One of the basic elements of the physical layer of a wireless network is the multiple access (MA) techniques. The MA techniques deviate in each generation and have grown from frequency division multiple access, used in the first generation, to orthogonal frequency division multiple access, which is adequately accepted in the 4G network. NOMA (MA scheme that violates the criteria of orthogonality) has been considered a promising multiple access technique for the 5G networks. NOMA supports a huge number of connected users (or devices), lowers latency, and boosts spectral efficiency. Accordingly, the application of NOMA is essential in investigating the 5G network and beyond. Furthermore, NOMA is compatible with recent techniques, such as HetNets, device to device (D2D) communication, mmWave, and IRS. This integrates NOMA with the contending 5G and beyond techniques of great research interest and is presented in this chapter. This chapter introduces a scenario in which a heterogeneous cellular network (HCN) is considered with three tiers, namely, macro base station (macroBS) tier underlaid with femto base station (femtoBS) tier, and D2D tier. NOMA principle is applied in the femtoBS tier and the D2D tier, while the macroBS tier does not use NOMA. Offloading from the macroBS tier to the femtoBS tier aids in tackling congestion at the macroBS tier. The cooperation introduced using the D2D tier further supports the offloaded macro user (macroU) from the macroBS tier. This support is primarily helpful when the femtoBS tier is using NOMA, and the femtoBS tier is unable to find a pairing user for the offloaded macroU. We introduce theoretical bounds and analysis for outage probability supported by Monte Carlo simulations.KeywordsNon-orthogonal multiple access5G and beyond networksHeterogeneous networksOffloadingD2D cooperationStochastic geometry 

NOMA for 5G and Beyond Wireless Networks

Recently, intelligent reflecting surfaces (IRSs) and nonorthogonal multiple-access (NOMA) have emerged as energy and spectrally efficient techniques for next-generation wireless networks. Thus, in this article, IRS-aided downlink sparse code multiple access (SCMA) system is analyzed for the next-generation wireless networks. In the proposed IRS-aided SCMA (IRS-SCMA), the base station (BS) communicates with single-antenna users with the help of an IRS. The impact of different phase shift methods at the IRS panel is studied in the IRS-SCMA, and observed that the average phase shift method has a very close performance to the perfect phase shift (optimal) with low complexity. We analyze symbol error rate and sum-rate performance of the IRS-SCMA. Simulation results show that the proposed IRS-SCMA outperforms the corresponding IRS-aided power domain nonorthogonal multiple access (PD-NOMA), and SCMA without IRS schemes. Further, the impacts of various system's parameters, such as the number of IRS reflecting elements, channel fading, SCMA codebooks, IRS location, and the number of users on the system performance are studied.

Intelligent Reflecting Surface-Aided Downlink SCMA

Millimeter wave (mmWave) multiple-input multiple-output (MIMO) is a potential physical layer technology for the fifth and the sixth-generation (5G/6G) wireless communication systems. However, existing works in mmWave hybrid processing do not adequately address the impact of unavoidable residual transceiver hardware impairments (RTHI). In this paper, channel estimation in an RTHI-affected channel in the mmWave hybrid MIMO system is investigated. Due to the RTHI, pilot and received information signals gets deteriorated, which makes channel estimation extremely challenging. Greedy-based iterative methods like orthogonal matching pursuit (OMP) and classical channel estimation techniques such as least squares (LS) provide very high computational complexity due to inversions of large matrices. We, therefore, provide a variable step-size zero-attracting least mean square (VSS-ZALMS) based channel estimator for the system under consideration to overcome these difficulties. Simulation results show that the proposed estimation algorithm significantly outperforms in terms of computational complexity and error performance compared to OMP, Bayesian compressive sensing (BCS), and sparse Bayesian learning (SBL).

Variable Step-size Zero Attractor LMS based Channel Estimator for Millimeter Wave Hybrid MIMO System with Hardware Impairments

Viability assessment is one of the most important parameters for ensuring high crop yield. Hence, in this work, a machine learning (ML) based automatic approach for detection of seed viability is developed by using laser biospeckle technique. Temporal (absolute value difference (AVD)), as well as spatial features (contrast, and the spatial absolute value difference (SAVD)) from the acquired speckle images were extracted to train and test several state-of-the-art ML models. Obtained results showed that artificial neural network (ANN) based predictive model possess better performance as compared to other models with overall accuracy of 97.65% for classifying the viable seeds.

Vimal Bhatia

Papers

Ordered multi-branch processing for successive interference cancellation based MIMO detection

NOMA for 5G and Beyond Wireless Networks

Intelligent Reflecting Surface-Aided Downlink SCMA

Variable Step-size Zero Attractor LMS based Channel Estimator for Millimeter Wave Hybrid MIMO System with Hardware Impairments

Machine Learning based Biospeckle Technique for Identification of Seed Viability using Spatio-temporal Analysis