BITS Faculty Publications

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Author: search.filters.author.Bitragunta, SainathSubject: search.filters.subject.Optimization

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Now showing 1 - 9 of 9
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    Efficient routing for QKD network using novel quantum optimization approach
    (IEEE, 2025) Bitragunta, Sainath; Bhatia, Ashuthosh
    With exponential growth and associated milestones set in quantum information and quantum computing (QC) technologies, QC is becoming a threat to existing key encryption strategies that leverage asymmetric cryptographic algorithms like RSA (Rivest, Shamir, Adleman) encryption. Since these algorithms form the backbone of Internet communication, it becomes essential to utilize secure quantum methods for key generation and distribution. The quantum key distribution (QKD) networks have since been extensively researched and implemented with various communication protocols, primarily utilizing the Quantum Entanglement and Quantum Key Correction paradigms. Efficient routing is one of the significant problems in classical and hybrid networks. It is important to propose novel hybrid and efficient routing protocols based on modern optimization approaches to design secure, fidelitous, and efficient quantum information networks. We perform this optimization by generating a cost function to implement quantum optimization algorithms, namely the Quantum Approximate Optimization Algorithm (QAOA). We further draw a comparison with the state-of-the-art graph theory-based optimization techniques. The primary objective of this paper is to fabricate a robust quantum communication network and to subsequently analyze the effectiveness of quantum based techniques to carry out network routing and link optimization, generating scope for the utilization of quantum architecture to enhance security in Q KD networks.
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    Fuzzy Logic and AI-Powered, SDR Relay for Secure and Efficient Cooperative Radio Communication
    (IEEE, 2024) Bitragunta, Sainath; Bhatia, Ashuthosh
    In this article, we develop a novel approach that leverages the capabilities of fuzzy logic and artificial intelligence (AI) to develop an intelligent, efficient cooperative RCN. Software defined radio (SDR) is flexible, scalable, and reconfigurable. Considering heterogeneous radio communication networks (RCNs), conventional relays do not perform well due to their limitations (security vulnerabilities in cooperative Internet-of-Things (IoT), inefficiencies in half-duplex relaying, etc.). We propose an AI-powered, fuzzy logic-based SDR relay to address these issues. These intelligent relays could be useful and outperform conventional relays due to their adaptability and reconfigurabilty, with added intelligence based on AI and fuzzy logic. The proposed next generation SDR relays offer significant advantages over traditional relays and have the potential to revolutionize the field of radio communication. Specifically, we analyze the decimation technique in SDR signal-to-interference plus noise ratio (SINR) resampler, Mamdani fuzzy logic controller, and use a machine learning (ML) model that uses RADIOML data set. Based on the simulation results, we show that applying fuzzy logic with an ML-enabled SDR relay could improve energy efficiency and reliability performance in advanced radio networks.
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    Optimizing the Order of Modulation for Minimized Distortion in Green Communication Networks
    (IEEE, 2018) Bitragunta, Sainath
    Energy is required for transmission of data over a wireless channel. This energy can be obtained using fixed batteries or via harvesting energy. In this paper, we optimize the energy distribution to minimize the overall distortion in a wireless network. The network model has energy harvesting nodes which transmit data in a time division multiple access (TDMA) scheme. First, we establish a relation between allocated energy and normalized minimum distortion by assuming a fixed battery system. We then use this relation to optimize the energy distribution to minimize overall distortion in an energy harvesting system. Following that, we incorporate path loss in our model and simulate the system to decide the optimum order of quadrature amplitude modulation (QAM), given a bit error rate threshold. This work not only models efficient usage of harvested energy but also ensures optimal utilization of the available bandwidth, while minimizing overall distortion.
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    Optimizing Fading-Averaged Bandwidth Efficiency of Underlay Cognitive Radio System by Transmit Power Adaptation
    (IEEE, 2019) Bitragunta, Sainath
    Power adaptation has been widely studied in the literature, given its significance in designing power efficient adaptive wireless systems. Specifically, transmit power adaptation is an important technique that is naturally appealing for underlay cognitive radio systems, which are intelligent and reconfigurable. In this paper, we consider a secondary underlay transmitter whose transmissions are constrained by an average interference threshold, also it adapts its transmit power as a function of its local channel state information (CSI). In this paper, we derive the optimal power adaptation factor (PAF) that maximizes the fading-averaged bandwidth efficiency (FABE) and also calculate the corresponding energy efficiency. We develop insightful analysis for average spectral efficiency, that is, FABE and energy efficiency for two scenarios: i). CSI-independent PAF and ii). CSI-dependent PAF. Our numerical results reveal that FABE for transmit power adaptation with CSI-dependent PAF delivers superior performance than the PAF that does not depend on instantaneous CSI at the expense of slight decrease in energy efficiency
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    Spectrally Efficient Cooperative Visible Light Communication with Adaptive Power Sharing for a Generalized System
    (IEEE, 2020) Bitragunta, Sainath
    Visible Light Communication (VLC) is among one-of-the top emerging next-generation technology and a key-enabler for the future networks, utilizing the visible light spectrum to achieve nominal data rates of Gbps. The compatibility of VLC with the existing infrastructure proves to be a major thrust in this domain, but suffers from signal fading and considerable interference provided by the nearby illuminants. Thus, a cooperative gain stage becomes essential to boost the signal present in the Non-line-of-sight (NLOS) with minimum power overheads. This paper proposes an optimal solution for the spectral efficiency of the VLC link: by introducing relay-based adaptive power-sharing schemes for improvement in signal strength, under the constraints of LED linear radiation region and threshold power consumption. DCO-OFDM modulation technique has been used to achieve minimum inter-symbol interference owing to its circular convolution properties. The Analytic analysis, as well as simulation results, are presented to show the effect of the scheme over an uncontrolled relay link. Later, a generalized model is proposed, and analytic methodology is adopted to determine optimal power-sharing coefficients. As a Figure of merit, we observe 18.29 % improvement in spectral efficiency at 13 dB of signal to noise ratio (SNR) when compared to an unoptimized collaborative link.
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    STPAP: Source Transmit Power Adaptation Policy for Collaborative Wireless Systems
    (IEEE, 2020) Bitragunta, Sainath
    For the design of energy-efficient or green communication systems and networks, power adaptation has been studied extensively in the literature. A vital aspect of the same is to minimize the usage of resources wherever possible. This research implements a Source Transmit Power Adaptation Policy (STPAP) for a two hop collaborative wireless communication system. Our objective is to optimize end-to-end fading averaged-energy efficiency (FA-EE) when the source is subject to an average source power constraint. Specifically, we derive an analytical expression for FA-EE in terms of source power, which is adapted as a function of fading channels' state information (CSI). We compare optimal FA-EE results with CSI-independent, fixed source power FA-EE and verify through Monte-Carlo (MC) simulations and analytical results. We find that the proposed STPAP delivers superior performance in terms of FA-EE. We further extend our benchmarking to a scenario where a direct link between source and destination is absent. We also compare optimal FA-EE with fixed power FA-EE and quantify the proposed policy's performance gains.
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    Hybrid, SWIPT-Based, Green Cooperative Wireless System Design and Performance Analysis
    (IEEE, 2021) Bitragunta, Sainath
    We consider a two-hop, hybrid collaborative radio communication system having regenerative and non-regenerative energy harvesting (EH) relays. The regenerative or non-regenerative relay harvests energy from its received radio frequency (RF) signals transmitted by the collaborative EH radio system's source node. We employ simultaneous wireless information and power transfer (SWIPT) with the time-switching EH protocol. We propose an insightful hybrid cooperative relaying protocol and its performance analysis. Specifically, we formulate an ergodic capacity optimization problem with average power constraint on relay transmissions. The proposed hybrid relaying protocol analysis and numerical results provide valuable insights into the effect of various hybrid EH collaborative radio system parameters. These parameters include EH time and non-regenerative relay's amplification factor on system performance in terms of normalized capacity. Furthermore, a comparison between multiple relaying protocols shows that hybrid relaying provides better fading-averaged capacity performance.
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    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.
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    Optimal Spectral Resource Allocation and Pricing for 5G and Beyond: A Game Theoretic Approach
    (IEEE, 2021-09) Bitragunta, Sainath; Chamola, Vinay
    Optimal allocation of the available spectrum is a crucial requirement of 5G and Beyond (B5G) for achieving higher Quality of Service (QoS) and low-latency. However, in 5G and Beyond, this requirement presents a potential need for dimensioning and managing the spectral resource in the cellular services. In this article, we address the issues of spectral distribution using DAG and Vickrey Clarke Groves (VCG) mechanisms by evaluating with a derived parameter for sustainable revenue and social welfare of the entire network. In particular, we modelled a framework to optimize social welfare of the users and the revenue of the cellular operator by proposing an efficient spectral allocation and pricing mechanism.