Adaptive Multiuser Channel Estimation using Reduced Kalman/LMS Algorithm

This paper presents an adaptive multiuser channel estimator using the reduced-Kalman least-mean-square (RK-LMS) algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh distributed tap coefficients. The multiuser channel estimator based on minimum-mean-square-error (MMSE) criterion is used to predict the filter coefficients. We also present its convergence characteristics and tracking performance using the RK-LMS algorithm. Unlike the previously available Kalman filtering algorithm based approach (Chen, Chen IEEE Trans Signal Process 49(7): 1523–1532, 2001) the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser channel estimator used in the code division multiple access wireless systems. The computer simulation results are presented to demonstrate the substantial improvement in its tracking performance under the smoothly time-varying environment.

SPICE compatible analytical electron mobility model for biaxial strained-Si-MOSFETs

This paper describes an analytical model for bulk electron mobility in strained-Si layers as a function of strain.Phonon scattering,columbic scattering and surface roughness scattering are included to analyze the full mobility model.Analytical explicit calculations of all of the parameters to accurately estimate the electron mobility have been made.The results predict an increase in the electron mobility with the application of biaxial strain as also predicted from the basic theory of strain physics of metal oxide semiconductor(MOS) devices.The results have also been compared with numerically reported results and show good agreement.     

An energy‐efficient and balanced clustering approach for improving throughput of wireless sensor networks

Maximizing the lifespan of wireless sensor networks is currently drawing a lot of attention in the research community. In order to reduce energy consumption, sensor nodes that are far from the base station avoid sending data directly. As a result, several disjoint clusters are formed, and nodes within a cluster send their data through the cluster head to avoid long transmissions. However, several parameters related to transmission cost need to be considered when selecting a cluster head. While most of the existing research work considers energy and distance as the most stringent parameters to reduce energy consumption, these approaches fail to create a fair and balanced cluster. Consequently, unbalanced clusters are formed, resulting in the degradation of overall performance. In this research work, a cluster head selection algorithm is proposed that covers all parts of the sensing area in a balanced manner, saving a significant amount of energy. Furthermore, a capture effect–based intracluster communication mechanism is proposed that efficiently utilizes the time slot under various traffic conditions. A Näive Bayes classifier is used to adapt the window size dynamically according to the traffic pattern. Finally, a simulation model using OMNeT++ is developed to compare the proposed approach with the pioneer clustering approach, LEACH, and the contemporary LEACH‐MAC protocol in terms of performance. The results of the simulation indicate that the proposed approach improves the overall performance in terms of network lifetime, energy efficiency, and throughput.     

Adaptive DFE Multiuser Receiver for CDMA Systems using Two-Step LMS-Type Algorithm: An Equalization Approach

This paper presents an adaptive decision feedback equalizer (DFE) based multiuser receiver for code division multiple access (CDMA) systems over smoothly time-varying multipath fading channels using the two-step LMS-type algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh-distributed tap coefficients. The receiver uses an adaptive minimum mean square error (MMSE) multiuser channel estimator based on the reduced Kalman least mean square (RK-LMS) algorithm to predict these tap coefficients (Kohli and Mehra, Wireless Personal Communication 46:507–521, 2008). We propose the design of adaptive MMSE feedforward and feedback filters by using the estimated channel response. Unlike the previously available Kalman filtering algorithm based approach (Chen and Chen, IEEE Transactions on Signal Processing 49:1523–1532, 2001), the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser receiver. The computer simulation results are presented to show the substantial improvement in its bit error rate performance over the conventional LMS algorithm based receiver. It can be inferred that the proposed multiuser receiver proves to be robust against the nonstationarity introduced due to channel variations, and it is also beneficial for the multiuser interference cancellation and data detection in CDMA systems.     

An improved LMI-based criterion for the design of optimal guaranteed cost controller for 2-D discrete uncertain systems

An improved criterion for the design of optimal static-state feedback guaranteed cost controller for two-dimensional (2-D) discrete uncertain systems described by the Fornasini-Marchesini second local state-space (FMSLSS) model is proposed. The design problem of the optimal guaranteed cost controller is formulated as a convex optimization problem with linear matrix inequality (LMI) constraints. The proposed method yields tighter upper bound of the closed-loop cost function as compared to a recently reported method.     

Gain Adapted Optimum Mixture Estimation Scheme for Single Channel Speech Separation

This paper presents the proof of an Optimum mixture estimator for the single channel speech separation problem, which is a technique for separating two speech signals from a single recording of their mixture. The presented work is an attempt to solve a fundamental limitation in the current single channel speech separation techniques, in which it is assumed that the data used in the training as well as test phases of the separation model have the same energy levels. To overcome this limitation, a gain adapted Optimum mixture estimator is derived, which estimates the mixture of speech signals under the different signal-to-signal ratios (SSRs). Specifically, the speakers’ gains are incorporated as unknown parameters into the separation model, and then the estimator is derived in terms of the source distributions and SSR. It is demonstrated that the use of the Optimum mixture estimator results in the lower estimation error than the non-linear mapping (log and inverse-log operations)-based Mixture-Maximization (MixMax) or Quadratic estimators. The experimental results based on the real speech data also depict that the proposed estimator improves the mixture estimation performance significantly when compared with MixMax or Quadratic estimators with the gain adaptation.     

Nanocomposite Hydrogel Materials for Defective Cartilage Repair and Its Mechanical Tribological Behavior—A Review

Osteoarthritis (OA) is a regressive ailment that affects a large population of patients. The most common symptoms of OA in humans are cartilage abnormalities. Hydrogels are excellent candidates for cartilage regeneration and are widely accepted as implants. In the past few decades, numerous types of hydrogels have been synthesized to repair cartilage defects. This study highlights recent advances in hydrogel development for the treatment of cartilage defects. In addition, the detailed progression of tailored nanocomposite hydrogels is summarized, and emphasis has been placed on the mechanical properties, especially the tribological behavior of the developed nanocomposite hydrogels.     

Kitkaite NiTeSe,an Ambient-Stable Layered Dirac Semimetal with Low-Energy Type-II Fermions with Application Capabilities in Spintronics and Optoelectronics

The emergence of Dirac semimetals has stimulated growing attention, owing to the considerable technological potential arising from their peculiar exotic quantum transport related to their nontrivial topological states. Especially, materials showing type-II Dirac fermions afford novel device functionalities enabled by anisotropic optical and magnetotransport properties. Nevertheless, real technological implementation has remained elusive so far. Definitely, in most Dirac semimetals, the Dirac point lies deep below the Fermi level, limiting technological exploitation. Here, it is shown that kitkaite (NiTeSe) represents an ideal platform for type-II Dirac fermiology based on spin-resolved angle-resolved photoemission spectroscopy and density functional theory. Precisely, the existence of type-II bulk Dirac fermions is discovered in NiTeSe around the Fermi level and the presence of topological surface states with strong (≈50%) spin polarization. By means of surface-science experiments in near-ambient pressure conditions, chemical inertness towards ambient gases (oxygen and water) is also demonstrated. Correspondingly, NiTeSe-based devices without encapsulation afford long-term efficiency, as demonstrated by the direct implementation of a NiTeSe-based microwave receiver with a room-temperature photocurrent of 2.8 µA at 28 GHz and more than two orders of magnitude linear dynamic range. The findings are essential to bringing to fruition type-II Dirac fermions in photonics, spintronics, and optoelectronics.     

Investigations on mode-division multiplexed free-space optical transmission for inter-satellite communication link

Wireless Networks - Inter-satellite data transmission links are very crucial for providing global inter-connectivity. We report designing and investigations on high date rate inter-satellite...     

Lightpath Rerouting Algorithm to enhance blocking performance in all-optical WDM network without wavelength conversion

In this paper, we have proposed an efficient wavelength rerouting algorithm for dynamic provisioning of lightpath. In wavelength-division multiplexed (WDM) networks rerouting of lightpath can be used to improve throughput and to reduce blocking probability. We have proposed a Lightpath Rerouting Algorithm (LRRA) for dynamic traffic in WDM optical networks. The results have shown that LRRA can improve blocking performance of the network. In this paper, low complexity algorithm has been developed which is used for the calculation of blocking probability of network. The proposed algorithm has also been applied on the realistic network such as NSFnet for calculation and optimization of blocking probability of the network. The results have also shown that the proposed algorithm can be implemented to huge networks for good blocking performance of the network.