Department of Electrical and Electronics Engineering

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Analysis of Adversarial Jamming From a Quantum Game Theoretic Perspective
(IEEE, 2023-03) Bitragunta, Sainath
Over recent years, quantum communication systems have demarcated themselves as promising candidates for deployment in next-generation communication networks (6G and beyond). Several recent experimental demonstrations of such complex systems have been highly successful and have been instrumental in transitioning this field from the theoretical to the practical domain. In this article, we investigate the application of quantum game theory for the modeling and analysis of jamming in the context of quantum networks. We begin with a general model of jamming based on the Colonel Blotto game and generalize it to the context of quantum networks. We provide an in-depth analysis of the two-person quantum Colonel Blotto game (QCBG) in relation to classical versus classical, classical versus quantum, and quantum versus quantum strategies. We also investigate the Nash equilibria for such games via a multiagent adversarial reinforcement learning-based system. Finally, we discuss further optimizations on this model and outline several open problems for further research along these lines.
Application of Game Theory to Cooperative Underlay Cognitive Radio IoT
(IEEE, 2019) Bitragunta, Sainath
Internet of things (IoT) is a new paradigm in wireless communication that offers a host of new opportunities to exploit the finite resources available. Cognitive radio networks (CRNs) employ these spectrum opportunities by using their inherent adaptive nature to automatically detect available channels in the spectrum and change transmission parameters to allow more communications to run concurrently, thus improving overall efficiency. The application of game theoretic principles to solving problems in this domain allows for the creation of fairly realistic models that clearly outline the relationship between the stakeholders involved, under the assumption of rationality. This paper presents a model for an IoT-based CRN in the underlay mode of operation. A triangular lattice with a set of relays is considered to model the secondary user network. The interference and power constraints accounted for in calculating the Nash equilibrium bring the model closer to direct applicability in the real world by including variations depending on channel strength and desirability.
Bayesian-based Projectile Angle Parameter Estimation, CRLB and Analysis
(IEEE, 2022) Bitragunta, Sainath
In this article, the authors consider the problem of estimating projectile angle using two different criteria, namely, maximum likelihood (ML) estimation and minimum mean square error (MMSE) estimation. The authors develop a simple estimation approach for very small projectile angles for the latter technique, MMSE estimation criteria. The projectile angle is present in the simple horizontal range equation implicitly. The authors circumvent this using the approximation for small projectile angles. In addition to insightful mathematical analysis, including CRLB, the authors present useful performance plots for CRLB and MMSE.
Best beam selection and PHY switching policy for hybrid FSO/RF inter-satellite communication link
(IET, 2020-10) Bitragunta, Sainath
Free space optical (FSO) inter-satellite links could often be non-reliable due to the imperfect line of sight (LOS) links. To achieve more reliable communication, the authors propose hybrid inter-satellite links. However, this leads to new challenges like switching physical (PHY) layers at the satellite's transmitter. In this work, they propose a novel hybrid radio frequency-FSO (RF/FSO) satellite system. For it, they develop a novel best beam selection policy (BBSP) and switching of FSO and RF to improve the reliability of the inter-satellite links. To obtain more insights, they investigate the performance of BBSP by deriving expressions for the outage probability, average spectral efficiency, and average bit error rate of the BBSP. For the PHY switching, they compare the instantaneous error probabilities of RF and FSO links and find the signal-to-noise ratio threshold at which it is more efficient to switch to RF. They further improve this threshold by considering a satellite transmitting multiple beams and choosing the best source beam. To validate the analytical findings, they simulate the proposed model with CubeSat level parameters. They and that the BBSP delivers superior performance in terms of various performance measures, which shows its applicability in next-generation satellite systems.
A Comparative Error Performance Study of Power Adaptive Regenerative Relaying Policy, and Benchmark Relaying Policies
(IEEE, 2020) Bitragunta, Sainath
Non-regenerative and regenerative relays have attracted a great deal of interest in the collaborative wireless communication systems. It is a known fact that device to device communication with relay assistance has catered enhanced network performance. In this work, the authors consider two relay-assisted collaborative device to device (D2D) wireless communication system. In it, power adaptive regenerative relays help the source to forward its transmitted signal. One of the two power adaptive regenerative relays is selected based on a probabilistic relay selection policy. For the two hop collaborative D2D system model, we derive the fading-averaged symbol error rate (FASER) expression for the proposed power adaptive regenerative relaying policy (PARRP) in an insightful scaling regime. Furthermore, in the scaling regime, we derive closed-form FASER expressions for the benchmark policies and compare their performance with that of PARRP. We find that the PARRP delivers superior FASER performance in comparison to the benchmark policies.
Comparative Performance Investigation of MIMO-OTFS and MIMO-OFDM using Deep Neural Network Modeling
(IEEE, 2021) Bitragunta, Sainath
We consider two popular wireless physical layers (PHYs), namely, multi-input multi-output (MIMO)-orthogonal frequency division multiplexing (OFDM) and MIMO-orthogonal time frequency and space (OTFS) modulation. For them, we develop and implement a deep neural network (DNN) model for fading channel estimation and investigate the mean square error (MSE) performance. While MIMO offers spatial multiplexing to enhance data rates, OFDM provides diversity to combat intersymbol interference. However, OFDM has limitations in high Doppler environments. The OTFS modulation, a newly developed two-dimensional modulation scheme, overcomes OFDM’s limitations. The OTFS modulation technique is helpful in high Doppler fading channels and offers several advantages. In the high Doppler scenario, we find that the OTFS outperforms the OFDM modulation scheme. The added benefit of OTFS over OFDM lies in exploiting channel diversity better in both the time domain and frequency domain when we employ the technique with appropriate equalizers. We show via simulations that DL-enabled MIMO-OTFS DNN exhibits a minimum MSE of value 0.4246, which is less than that of MIMO-OFDM DNN, which is 0.5355 for fading scenarios with high Doppler. Furthermore, we compare our DNN model with the existing linear interpolation technique for channel estimation in MIMO-OTFS at high Doppler.
Comparative Performance Study of CNN-based Algorithms and YOLO
(IEEE, 2022) Bitragunta, Sainath
Tasks such as image classification, object detection, to mention a few, play an important role in computer vision. Numerous algorithms have been developed to improve the performance of such tasks for benchmark datasets. Although advanced algorithms offer state-of-the-art performance on such tasks, it is also important to analyze their algorithmic feasibility over the time to make it practical for end-user applications. This paper analyzes two such groups of algorithms, namely, Convolutional Neural Networks (CNN) based algorithms with You Only Look Once (YOLO) in terms of speed and accuracy.
A Comparative Study of Noise Cancellation Using Least Mean Squares Adaptive Filter and Recurrent Neural Network Filter
(IEEE, 2018) Bitragunta, Sainath
Algorithms in artificial neural networks (ANN) are evolving as better alternatives to conventional algorithms applied in various electrical engineering applications in general and signal processing applications in particular. Specifically, we focus on a special type of ANN called recurrent neural networks (RNN), which delivers superior performance on sequential data due to the presence of internal memory. In the present paper, we comparatively analyze the performance of RNN and least mean squares (LMS) adaptive filter on audio data for active noise cancellation. We use normalized mean squared error (NMSE) as performance measure for comparison. Furthermore, we also investigate the number of epochs for training and the time taken to give the desired output via numerical simulations. Our simulations show that RNN filter delivers better NMSE performance than conventional LMS filter.
Deep Fade Event's Probability Performance Analysis of Non-Orthogonal Multiple Access Scheme Realization in Power Domain
(IEEE, 2019) Bitragunta, Sainath
In this paper, the author investigates the deep fade event probability performance of non-orthogonal multiple access (NOMA). For the analysis, the author considers the downlink of a mobile wireless network scenario wherein the users assumes random locations. The author develops an insightful analysis which comprises of analytical results for deep fade event probability. Specifically, the author derives a tractable closed-form upper bound on deep fade probability in a more practical and insightful scenario in which a user is probabilistically active. To numerically evaluate the performance of insightful analytical results, the author plots the deep fade probability for various simulation parameters. From the numerical plots, the author observes that the user's deep fade event probability improves as the number of users increases. Finally, the author suggests a few adaptive techniques to improve deep fade probability performance.
Doubly Constrained Underlay Cognitive Radio System: Optimization and Analysis
(IEEE, 2019) Bitragunta, Sainath
In this paper, we consider a doubly constrained underlay cognitive radio (CR) system. In it, a secondary user (SU) transmitter (Tx) is subject to average interference constraint, and spectral efficiency constraint. For the underlay system, we investigate both average energy efficiency and average spectral efficiency. Specifically, we develop an algorithm that determines the suboptimal operating point of transmit power with which the SU-Tx must operate for maximum energy efficiency. We derive an analytical expression for the fading-averaged spectral efficiency assuming Rayleigh fading with path loss and shadowing. To validate the analytical results, we simulate the model in MATLAB using Monte-Carlo simulations and investigate the system performance. The analysis that we present is useful for constrained cognitive radio systems and networks.
Energy Efficiency Performance Analysis of Single and Multi-Receive Antenna Backscatter Communication System
(IEEE, 2022) Bitragunta, Sainath
Ambient backscatter communication (AmBSC) via ambient energy harvesting passive tags is helpful in the passive internet of things (IoT). Since energy is a limited resource, energy-efficient BSC is essential in passive IoT and could provide long-term profitability. We first consider a simple three-node BSC system set up with a single tag node. In it, all nodes have a single transceiving antenna. We analyze the BSC link's energy efficiency performance over the frequency-flat Rayleigh fading channels for this model. Specifically, we derive analytical expressions for average energy efficiency for the ambient BSC. We then consider an ambient BSC system having a receiver with multiple antennas with antenna selection. For this complex BSC system model, we analyze and evaluate average energy efficiency. We validate derived analytical results using Monte-Carlo simulations. In addition to exact energy efficiency, we also derive its upper bound. The detailed analysis and new insightful results that we present are helpful to design and optimize ambient BSC systems in terms of energy efficiency.
Energy efficient and delay-constrained sleep period optimization for green radio communication
(Elsevier, 2018-10) Bitragunta, Sainath
Green communication technology research deals with the methods to achieve efficient energy utilization by radio communication devices. Recent advances in this area include radio resource optimization, radio resource management, and optimal sleep control. In this paper, we focus on the problem of optimizing mean cost subject to a constraint on sleep period. We solve this problem and find the optimal solution to the sleep period and investigate the behavior of the optimum sleep period and the standard deviation of the cost function. We then present numerical results for optimum sleep period, and statistical parameters, namely, standard deviation, and deviation figure. This work not only models mean cost optimally but also compares with ad hoc average costs, which do not account both energy consumption and delay.
Energy Harvesting Cooperative Wireless Systems: Probabilistic Modeling and Statistical Analysis
(IEEE, 2019) Bitragunta, Sainath
In this work, we consider a two-hop cooperative wireless system that consists of multiple energy harvesting (EH) relays. The system uses a time-switching based relaying protocol for EH and information processing at the amplify-and-forward (AF) relay nodes. For it, we formulate an order statistics problem of finding the distribution of maximum energy harvested among several EH relay nodes by considering two different fading models, namely, path loss and Rayleigh fading model, path loss and shadow fading model. For these models, we derive analytical expressions for the mean value of maximum harvested energy distribution. Furthermore, we also present an insightful outage analysis and numerical results to validate the analytical expressions. The analysis that we present lead to an essential application of the best EH relay selection in EH cooperative wireless systems and networks.
Energy harvesting relay outage probability analysis of cooperative communication system over small and large scale fading channels
(IEEE, 2017) Bitragunta, Sainath
We consider an energy harvesting (EH) relay-assisted, two hop, cooperative communication system. For it, we analytically characterize EH relay outage probability when the source device transmissions undergo small scale fading as well as large scale fading. In the analysis, we develop simple yet insightful upper bound for the EH relay outage probability. Furthermore, we investigate asymptotic outage probability of EH relay. We validate our analytical results with Monte-Carlo simulations. Assuming other system parameters fixed, our results show that the EH relay outage probability decreases with the increase in the harvesting power.
Energy Harvesting, Hybrid, Cooperative Wireless System Modeling and Outage Performance Analysis
(IEEE, 2018) Bitragunta, Sainath
We consider radio frequency-energy harvesting (RF-EH) non-cooperative system, and, an RF-EH relay-assisted, two hop, hybrid cooperative communication system that comprises of a digital link, and an analog link that uses phase modulation. For the two system models, we analytically characterize outage probability when the node transmissions undergo small scale fading as well as path loss. In the analysis, we develop simple yet insightful closed-form expressions for outage probability. We validate our analytical results with Monte-Carlo simulations. Our numerical results show that the outage can be significantly improved by using pre-emphasis and de-emphasis (PE-DE)
Environment-Aware Green UAV-Assisted, CubeSat Communication Network Energy Efficiency and Outage Probability Analysis
(IEEE, 2024-08) Bitragunta, Sainath
Rapid advancements in internet-of-things (IoT), unmanned aerial vehicles (UAVs), and energy harvesting (EH) technologies can be leveraged to design and develop green and reliable cooperative Cube satellite communication (CSC) systems and networks. In this work, we propose a novel cooperative CSC system model comprising green UAVs as intelligent relays equipped with IoT sensors, intelligent processing and EH modules, and transceivers. Using a novel and intelligent probabilistic transmission policy (PTP) that we propose, CubeSats can conserve energy by deactivating transmissions in unfavorable weather conditions based on control signals from the smart UAV via a telemetry link. We extend this model to include multiple CubeSats and analyze it by deriving and evaluating network energy efficiency and its lower bound. Our numerical plots show that the proposed PTP significantly outperforms the continuous transmission policy (CTP). At a specific transmission probability of 0.125, PTP is 40 times more energy efficient than CTP. We extend the work and develop a novel and insightful performance analysis for energy efficiency outage (EEO) probability. Specifically, we derive closed-form approximate expressions for EEO probability and present numerical results. Furthermore, we analyze the performance of clustered CSC networks and present numerical results to assess EEO probability, providing valuable insights for future large-scale green CSC network design and deployment.
Estimation and Analysis of Maximum Energy Harvested in RF-EH Wireless System Over Different Fading Channels
(Springer, 2024-02) Bitragunta, Sainath
Parameter estimation is an important problem in practical wireless systems and networks. Specifically, accurate estimation of harvested energies is vital in autonomous, green wireless systems and networks whose essential energy resources are ambient radio frequency (RF) signals. In this paper, I address the problem of estimating the maximum energy harvested among multiple energy harvesting (EH) relays in a double-hop EH relay-assisted cooperative wireless system. In the system considered, multiple EH relays harvest energy from RF signals they receive from the RF source over Rayleigh fading channels. I formally state the maximum harvested energy estimation problem in the presence of additive white noise. I derive analytical expressions for the exact minimum mean squared error (MMSE) estimator and MMSE. Further, I obtain an expression for the number of measurements for a special scenario where MMSE and Cramer-Rao lower bound (CRLB) are equal. I further extend the analysis and simulations for Rayleigh fading with shadowing and Nakagami fading to get more analytical and quantitative insights. Finally, the MMSE of the proposed model is compared with a benchmark model that includes quantization noise and multiplicative noise. The analysis is useful for further investigating order statistics of harvested energies and application in green cooperative energy harvesting Internet of Things (IoT)-enabled wireless systems.
Fading Averaged-Spectral Efficiency Analysis of Average Interference-Constrained, Cooperative Device-to-Device Communication System
(IEEE, 2017) Bitragunta, Sainath
We consider a two hop cooperative device-to-device (D2D) communication system. In it, a non-regenerative relay is subject to a tight constraint on the average interference it to the base station (BS). We derive interference-aware, spectral efficiency optimal relay amplification policy as a function of its local fading gains. We then derive expressions for fading-averaged spectral efficiency and its upper bound, and, present numerical results wherein we compare optimum amplification policy with fixed-amplification policy, and, also with a non-cooperative link. In all performance plots, we show that the optimal policy delivers superior performance when compared to fixed-amplification policy, and, non-cooperative link.
Fading-Averaged Spectral Efficiency Analysis of Millimeter Wave Communication Links over Nakagami Fading Channels
(IEEE, 2019-07) Bitragunta, Sainath
Functionalized carbon materials can be synthesized from biomass feedstock using a simple hydrothermal carbonization (HTC) technique. Glucose was selected as the model biomass compound and the starting material for the synthesis of functionalized carbon materials. Iron oxide (Fe3O4) catalyst was introduced in the HTC system, and the effects of the catalyst toward the formation and yield of functionalized carbon materials were investigated. In the present study, the samples synthesized via HTC with and without iron oxide catalyst were characterized in detail (i.e., XRD, FTIR, Raman spectroscopy, and ultimate CHNS elemental analyzer). Results demonstrated that incorporating iron oxide catalyst was equally effective in both functionalization and acceleration of the HTC reactions (hydrolysis, degradation, and re-polymerization) for the carbon formation. Such findings indicated that the formation of functionalized carbon materials with controllable properties has great potential in energy applications, such as H2 storage media and supercapacitor materials.
Fading-Averaged Symbol Error Probability Analysis of Full Duplex Amplify-and-Forward Relaying over Rayleigh Fading Channels
(IEEE, 2018) Bitragunta, Sainath
Half-duplex amplify-and-forward (AF) relay based cooperation has been studied in the literature given its simplicity and practicality. In this paper, we consider a full-duplex relay-assisted AF cooperation model. For it, we analyze the fading-averaged symbol error probability (FA-SEP). Specifically, we derive an expression for exact FA-SEP. To get more insights, we derive tractable upper bound for the exact FA-SEP. Furthermore, we extend our analysis and derive asymptotic FA-SEP in a scaling regime. Finally, we present numerical results to validate our analysis. Our analysis of FA-SEP provides a theoretical benchmark and is useful for analyzing more complex cooperative systems employing multiple full-duplex AF relays.