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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

Media-based modulation (MBM) with massive multiple-input multiple-output (mMIMO) wireless systems is a viable solution to realize the ever-increasing demand for high-speed data and extensive connectivity in beyond 5G and 6G wireless communications. MBM-mMIMO utilizes less transmit power and radio resources measured against mMIMO to yield high spectral efficiency and high data rate. However, symbol detection in the uplink of MBM-mMIMO is challenging due to the sparse nature of the received signal, and the cumulative effect of inter-user interference and noise. In this letter, support recovery error constraint-based low complexity sequential symbol detection technique is proposed for uplink MBM-mMIMO system. The proposed MBM-mMIMO detection technique exploits the upper bound on support recovery error and iteratively minimizes the residual error associated with the estimated transmit vector. A reduced message space is also introduced to further enrich the exploration capability of the proposed technique. Simulation results reveal the viability of proposed techniques over several state-of-the-art MBM-mMIMO detection techniques as BER performance and computational complexity are concerned.

Minimum Error Pursuit Algorithm for Symbol Detection in MBM Massive-MIMO

Design of distributed caching mechanisms is considered as an active area of research due to its promising solution in reducing data load in the backhaul link of a cellular network. In this paper, the problem of distributed content caching in a small-cell Base Stations (sBSs) wireless network that maximizes the cache hit performance is considered. Most of the existing works focus on static demands, however, here, data at each sBS is considered to be correlated across time and sBSs. The caching strategy is assumed to be a weighted combination of past caching strategies. A high probability generalization guarantees on the performance of the proposed caching strategy is derived. The theoretical guarantee provides following insights on obtaining the caching strategy: (i) run regret minimization at each sBS to obtain a sequence of caching strategies across time, and (ii) maximize an estimate of the bound to obtain a set of weights for the caching strategy which depends on the discrepancy. Also, theoretical guarantee on the performance of the LRFU caching strategy is derived. Further, federated learning based heuristic caching algorithm is also proposed. Finally, it is shown through simulations using Movie Lens dataset that the proposed algorithm significantly outperforms LRFU algorithm.

Learning to Cache: Distributed Coded Caching in a Cellular Network With Correlated Demands.

This paper investigates the performance of overlay full-duplex cooperative cognitive radio network in the presence of imperfect self interference cancellation over generalized $\alpha -\mu $ fading channels effected by nonlinearity of the propagation medium. In practice, physical transceivers create distortion which degrades the performance, hence, the impact of transceiver hardware impairments (HIs) is considered. To overcome the energy constraint problem, a hybrid simultaneous wireless information and power transfer receiver is adopted that includes both the time switching and the power splitting protocols. To improve reliability of the communication link, we employ a hybrid relaying protocol that combines both the decode-and-forward and amplify-and-forward relaying protocols. The closed-form expressions of outage probability and asymptotic outage probability are derived for both the primary and the secondary networks over $\alpha -\mu $ fading channels. The diversity order, throughput, and energy efficiency of the considered network are derived. Optimal values of time switching factor is obtained for which the considered network exhibits optimum outage probability, maximum throughput and energy efficiency. Further, optimal value of power splitting factor is obtained for which the considered network shows maximum throughput and energy efficiency. Finally, the Monte-Carlo simulations validate correctness of the derived closed-form expressions.

On Performance of a SWIPT Enabled FD CRN With HIs and Imperfect SIC Over α–μ Fading Channel

Determination of coefficient of thermal expansion (CTE) of metallic bar using coherent gradient sensing (CGS) is reported in this paper. Collimated light interrogated one end of the specimen/sample kept in a furnace. The light which is reflected from the sample is diverted towards the CGS interferometer using the beam splitter (BS). The set-up is arranged such that, the horizontal fringes due to collimation is achieved. Dimensional variation in the specimen is correlated with the size, shape and orientation of the shear fringes. The change in fringe orientation has been used to estimate CTE.

Measurement of Linear Thermal Expansion Coefficient using Coherent Gradient Sensing

Massive multiple-input multiple-output (MIMO) system is a core technology to realize high-speed data for 5G and beyond systems. Though machine learning-based MIMO detection techniques outperform conventional symbol detection techniques, in large user massive MIMO, they suffer from maintaining an optimal bias-variance trade-off to yield optimal performance from an individual model. Hence, in this article, collaborative learning based low complexity detection technique is proposed for uplink symbol detection in large user massive MIMO systems. The proposed detection technique strategically ensembles multiple fully connected neural network models utilizing iterative meta-predictor and reduces the final estimation error by smoothing the variance associated with individual estimation errors. Simulations are carried out to validate the performance of the proposed detection technique under both perfect and imperfect channel state information scenarios. Simulation results reveal that the proposed detection technique achieves a lower bit error rate while maintaining a low computational complexity as compared to several existing uplink massive MIMO detection techniques.

Vimal Bhatia

Papers

Minimum Error Pursuit Algorithm for Symbol Detection in MBM Massive-MIMO

Learning to Cache: Distributed Coded Caching in a Cellular Network With Correlated Demands.

On Performance of a SWIPT Enabled FD CRN With HIs and Imperfect SIC Over α–μ Fading Channel

Measurement of Linear Thermal Expansion Coefficient using Coherent Gradient Sensing

Collaborative Learning based Symbol Detection in Massive MIMO