arXiv subjects

Deepak Mishra

Publications and source records attributed to Deepak Mishra.

89 records · Page 5Linked to original sources

arXiv2019

Utility Regions for DF Relay in OFDMA-based Secure Communication with Untrusted Users

This paper investigates the utility of a trusted decode-and-forward relay in OFDMA-based secure communication system with untrusted users. For deciding whether to use the relay or not, we first present optimal subcarrier allocation policies for direct communication (DC) and relayed communication (RC). Next we identify exclusive RC mode, exclusive DC mode, and mixed (RDC) mode subcarriers which can support both the modes. For RDC mode we present optimal mode selection policy and a suboptimal strategy independent of power allocation which is asymptotically optimal at both low and high SNRs. Finally, via numerical results we present insights on relay utility regions.

cs.IT↗

arXiv2019

Localization: A Missing Link in the Pipeline of Object Matching and Registration

Image registration is a process of aligning two or more images of same objects using geometric transformation. Most of the existing approaches work on the assumption of location invariance. These approaches require object-centric images to perform matching. Further, in absence of intensity level symmetry between the corresponding points in two images, the learning based registration approaches rely on synthetic deformations, which often fail in real scenarios. To address these issues, a combination of convolutional neural networks (CNNs) to perform the desired registration is developed in this work. The complete objective is divided into three sub-objectives: object localization, segmentation and matching transformation. Object localization step establishes an initial correspondence between the images. A modified version of single shot multi-box detector is used for this purpose. The detected region is cropped to make the images object-centric. Subsequently, the objects are segmented and matched using a spatial transformer network employing thin plate spline deformation. Initial experiments on MNIST and Caltech-101 datasets show that the proposed model is able to produce accurate matching. Quantitative evaluation performed using dice coefficient (DC) and mean intersection over union (mIoU) show that proposed method results in the values of 79% and 66%, respectively for MNIST dataset and the values of 94% and 90%, respectively for Caltech-101 dataset. The proposed framework is extended to the registration of CT and US images, which is free from any data specific assumptions and has better generalization capability as compared to the existing rule-based/classical approaches.

cs.CV↗

arXiv2019

OFDMA-based DF Secure Cooperative Communication with Untrusted Users

In this letter we consider resource allocation for OFDMA-based secure cooperative communication by employing a trusted Decode and Forward (DF) relay among the untrusted users. We formulate two optimization problems, namely, (i) sum rate maximization subject to individual power constraints on source and relay, and (ii) sum power minimization subject to a fairness constraint in terms of per-user minimum support secure rate requirement. The optimization problems are solved utilizing the optimality of KKT conditions for pseudolinear functions.

cs.IT↗

arXiv2019

Subcarrier Pairing as Channel Gain Tailoring: Joint Resource Allocation for Relay-Assisted Secure OFDMA with Untrusted Users

Joint resource allocation involving optimization of subcarrier allocation, subcarrier pairing (SCP), and power allocation in a cooperative secure orthogonal frequency division multiple access (OFDMA) communication system with untrusted users is considered. Both amplify and forward (AF), and decode and forward (DF) modes of operations are considered with individual power budget constraints for source and relay. After finding optimal subcarrier allocation for an AF relayed system, we prove the joint power allocation as a generalized convex problem, and solve it optimally. Compared to the conventional channel gain matching view, the optimal SCP is emphasized as a novel concept of channel gain tailoring. We prove that the optimal SCP pairs subcarriers such that the variance among the effective channel gains is minimized. For a DF relayed system, we show that depending on the power budgets of source and relay, SCP can either be in a subordinate role where it improves the energy efficiency, or in a main role where it improves the spectral efficiency of the system. In an AF relayed system we confirm that SCP plays a crucial role, and improves the spectral efficiency of the system. The channel gain tailoring property of SCP, various roles of SCP in improving the spectral and the energy efficiency of a cooperative communication system are validated with the help of simulation results.

cs.IT↗

arXiv2019

Optimal Channel Estimation for Reciprocity-Based Backscattering with a Full-Duplex MIMO Reader

Backscatter communication (BSC) technology can enable ubiquitous deployment of low-cost sustainable wireless devices. In this work we investigate the efficacy of a full-duplex multiple-input-multiple-output (MIMO) reader for enhancing the limited communication range of monostatic BSC systems. As this performance is strongly influenced by the channel estimation (CE) quality, we first derive a novel least-squares estimator for the forward and backward links between the reader and the tag, assuming that reciprocity holds and K orthogonal pilots are transmitted from the first K antennas of an N antenna reader. We also obtain the corresponding linear minimum-mean square-error estimate for the backscattered channel. After defining the transceiver design at the reader using these estimates, we jointly optimize the number of orthogonal pilots and energy allocation for the CE and information decoding phases to maximize the average backscattered signal-to-noise ratio (SNR) for efficiently decoding the tag's messages. The unimodality of this SNR in optimization variables along with a tight analytical approximation for the jointly global optimal design is also discoursed. Lastly, the selected numerical results validate the proposed analysis, present key insights into the optimal resource utilization at reader, and quantify the achievable gains over the benchmark schemes.

cs.IT↗

arXiv2018

How You See Me

Convolution Neural Networks is one of the most powerful tools in the present era of science. There has been a lot of research done to improve their performance and robustness while their internal working was left unexplored to much extent. They are often defined as black boxes that can map non-linear data very effectively. This paper tries to show how CNN has learned to look at an image. The proposed algorithm exploits the basic math of CNN to backtrack the important pixels it is considering to predict. This is a simple algorithm which does not involve any training of its own over a pre-trained CNN which can classify.

cs.CV↗

arXiv2018

Stellar Cluster Detection using GMM with Deep Variational Autoencoder

Detecting stellar clusters have always been an important research problem in Astronomy. Although images do not convey very detailed information in detecting stellar density enhancements, we attempt to understand if new machine learning techniques can reveal patterns that would assist in drawing better inferences from the available image data. This paper describes an unsupervised approach in detecting star clusters using Deep Variational Autoencoder combined with a Gaussian Mixture Model. We show that our method works significantly well in comparison with state-of-the-art detection algorithm in recognizing a variety of star clusters even in the presence of noise and distortion.

cs.LG↗

arXiv2018

Energy Sustainable IoT with Individual QoS Constraints Through MISO SWIPT Multicasting

Enabling technologies for energy sustainable Internet of Things (IoT) are of paramount importance since the proliferation of high data communication demands of low power network devices. In this paper, we consider a Multiple Input Single Output (MISO) multicasting IoT system comprising of a multiantenna Transmitter (TX) simultaneously transferring information and power to low power and data hungry IoT Receivers (RXs). Each IoT device is assumed to be equipped with Power Splitting (PS) hardware that enables Energy Harvesting (EH) and imposes an individual Quality of Service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO Simultaneous Wireless Information and Power Transfer (SWIPT) multicasting IoT system with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic Radio Frequency (RF) EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent semi-definite relaxation formulation and then prove it possesses unique global optimality. We also derive tight upper and lower bounds on the globally optimal solution that are exploited in obtaining low complexity algorithmic implementations for the targeted joint design. Analytical expressions for the optimal TX beamforming directions, power allocation, and IoT PS ratios are also presented. Our representative numerical results including comparisons with benchmark designs corroborate the usefulness of proposed framework and provide useful insights on the interplay of critical system parameters.

cs.IT↗

arXiv2018

Joint Optimal Design for Outage Minimization in DF Relay-assisted Underwater Acoustic Networks

This letter minimizes outage probability in a single decode-and-forward (DF) relay-assisted underwater acoustic network (UAN) without direct source-to-destination link availability. Specifically, a joint global-optimal design for relay positioning and allocating power to source and relay is proposed. For analytical insights, a novel low-complexity tight approximation method is also presented. Selected numerical results validate the analysis and quantify the comparative gains achieved using optimal power allocation (PA) and relay placement (RP) strategies.

cs.IT↗

arXiv2018

Transmit Precoding and Receive Power Splitting for Harvested Power Maximization in MIMO SWIPT Systems

We consider the problem of maximizing the harvested power in Multiple Input Multiple Output (MIMO) Simultaneous Wireless Information and Power Transfer (SWIPT) systems with power splitting reception. Different from recently proposed designs, with our optimization problem formulation we target for the jointly optimal transmit precoding and receive uniform power splitting (UPS) ratio maximizing the harvested power, while ensuring that the quality-of-service requirement of the MIMO link is satisfied. We assume practical Radio-Frequency (RF) energy harvesting (EH) receive operation that results in a non-convex optimization problem for the design parameters, which we first formulate in an equivalent generalized convex problem that we then solve optimally. We also derive the globally optimal transmit precoding design for ideal reception. Furthermore, we present analytical bounds for the key variables of both considered problems along with tight high signal-to-noise ratio approximations for their optimal solutions. Two algorithms for the efficient computation of the globally optimal designs are outlined. The first requires solving a small number of non-linear equations, while the second is based on a two-dimensional search having linear complexity. Computer simulation results are presented validating the proposed analysis, providing key insights on various system parameters, and investigating the achievable EH gains over benchmark schemes.

cs.IT↗

arXiv2018

Unsupervised Despeckling

Contrast and quality of ultrasound images are adversely affected by the excessive presence of speckle. However, being an inherent imaging property, speckle helps in tissue characterization and tracking. Thus, despeckling of the ultrasound images requires the reduction of speckle extent without any oversmoothing. In this letter, we aim to address the despeckling problem using an unsupervised deep adversarial approach. A despeckling residual neural network (DRNN) is trained with an adversarial loss imposed by a discriminator. The discriminator tries to differentiate between the despeckled images generated by the DRNN and the set of high-quality images. Further to prevent the developed DRNN from oversmoothing, a structural loss term is used along with the adversarial loss. Experimental evaluations show that the proposed DRNN is able to outperform the state-of-the-art despeckling approaches.

cs.CV↗

arXiv2017

Rotation Adaptive Visual Object Tracking with Motion Consistency

Visual Object tracking research has undergone significant improvement in the past few years. The emergence of tracking by detection approach in tracking paradigm has been quite successful in many ways. Recently, deep convolutional neural networks have been extensively used in most successful trackers. Yet, the standard approach has been based on correlation or feature selection with minimal consideration given to motion consistency. Thus, there is still a need to capture various physical constraints through motion consistency which will improve accuracy, robustness and more importantly rotation adaptiveness. Therefore, one of the major aspects of this paper is to investigate the outcome of rotation adaptiveness in visual object tracking. Among other key contributions, the paper also includes various consistencies that turn out to be extremely effective in numerous challenging sequences than the current state-of-the-art.

cs.CV↗

arXiv2017

Jointly Optimal Spatial Channel Assignment and Power Allocation for MIMO SWIPT Systems

The joint design of spatial channel assignment and power allocation in Multiple Input Multiple Output (MIMO) systems capable of Simultaneous Wireless Information and Power Transfer (SWIPT) is studied. Assuming availability of channel state information at both communications ends, we maximize the harvested energy at the multi-antenna receiver, while satisfying a minimum information rate requirement for the MIMO link. We first derive the globally optimal eigenchannel assignment and power allocation design, and then present a practically motivated tight closed-form approximation for the optimal design parameters. Selected numerical results verify the validity of the optimal solution and provide useful insights on the proposed designs as well as the pareto-optimal rate-energy tradeoff.

cs.IT↗

arXiv2017

Harvested Power Maximization in QoS-Constrained MIMO SWIPT with Generic RF Harvesting Model

cs.IT↗

arXiv2017

Energy-aware Mode Selection for Throughput Maximization in RF-Powered D2D Communications

Doubly-near-far problem in RF-powered networks can be mitigated by choosing appropriate device-to-device (D2D) communication mode and implementing energy-efficient information transfer (IT). In this work, we present a novel RF energy harvesting architecture where each transmitting-receiving user pair is allocated a disjoint channel for its communication which is fully powered by downlink energy transfer (ET) from hybrid access point (HAP). Considering that each user pair can select either D2D or cellular mode of communication, we propose an optimized transmission protocol controlled by the HAP that involves harvested energy-aware jointly optimal mode selection (MS) and time allocation (TA) for ET and IT to maximize the sum-throughput. Jointly global optimal solutions are derived by efficiently resolving the combinatorial issue with the help of optimal MS strategy for a given TA for ET. Closed-form expressions for the optimal TA in D2D and cellular modes are also derived to gain further analytical insights. Numerical results show that the joint optimal MS and TA, which significantly outperforms the benchmark schemes in terms of achievable RF-powered sum-throughput, is closely followed by the optimal TA scheme for D2D users. In fact, about $2/3$ fraction of the total user pairs prefer to follow the D2D mode for efficient RF-powered IT.

cs.IT↗

arXiv2017

Joint Optimization Framework for Operational Cost Minimization in Green Coverage-Constrained Wireless Networks

In this work, we investigate the joint optimization of base station (BS) location, its density, and transmit power allocation to minimize the overall network operational cost required to meet an underlying coverage constraint at each user equipment (UE), which is randomly deployed following the binomial point process (BPP). As this joint optimization problem is nonconvex and combinatorial in nature, we propose a non-trivial solution methodology that effectively decouples it into three individual optimization problems. Firstly, by using the distance distribution of the farthest UE from the BS, we present novel insights on optimal BS location in an optimal sectoring type for a given number of BSs. After that we provide a tight approximation for the optimal transmit power allocation to each BS. Lastly, using the latter two results, the optimal number of BSs that minimize the operational cost is obtained. Also, we have investigated both circular and square field deployments. Numerical results validate the analysis and provide practical insights on optimal BS deployment. We observe that the proposed joint optimization framework, that solves the coverage probability versus operational cost tradeoff, can yield a significant reduction of about $65\%$ in the operational cost as compared to the benchmark fixed allocation scheme.

cs.IT↗

arXiv2014

Comparative Study of Geometric and Image Based Modelling and Rendering Techniques

This is a comparative study of the traditional 3D computer graphics technique of geometric modelling and image-based rendering techniques that were surveyed and implemented.We have discussed the classifications and representative methods of both the techniques. The study has shown that there is a strong continuum between both the techniques and a hybrid of the two is most suitable for further implementations.This hybridisation study is underway to create models of real life situations and provide disaster management training.

cs.GR↗