arXiv subjects

Vimal Bhatia

Publications and source records attributed to Vimal Bhatia.

At least 19 recordsLinked to original sources

arXiv2026

TRACE: A Modular Framework for RIS-Assisted Channel Estimation and Differential Channel-Aware Reconfiguration

Reconfigurable Intelligent Surface (RIS) research tightly couples channel-estimation, control and communication, yet existing implementations often rely on fixed algorithmic pipelines, making it difficult to compare alternative estimation, tracking and communication strategies under identical conditions and to study low-overhead RIS adaptation under time-varying channels. This paper addresses both challenges through two complementary contributions. First, it presents TRACE (Toolkit for RIS-assisted channel-estimation, adaptive control and communication experimentation), a modular socket-based framework that decouples the transmitter, radio environment, controller and receiver through separate control- and data-plane interfaces, enabling reproducible evaluation across substitutable modules. Second, it proposes the differential channel-aware RIS update (DCAR) algorithm, which estimates channel perturbations from reduced probe observations using a regularized differential update to reduce retraining overhead. TRACE is validated through interchangeable minimum mean square error and orthogonal matching pursuit channel-estimation, Gaussian random walk and Gauss--Markov channel evolution, BPSK, QPSK and 16-QAM modulation techniques and multiple RIS sizes, without modifying the underlying framework. Within TRACE, DCAR is observed to reduce pilot overhead and computational complexity while maintaining beamforming performance close to Kalman-filter-based tracking under time-varying channels.

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arXiv2026

TinyML for On-Device and Edge Analytics in Wireless Networks: A Survey of Deployments, Opportunities, and Concept-Drift Mitigation

Ubiquitous intelligence is essential for enabling real-time, adaptive, autonomous, and scalable operations in the next generation of wireless networks. However, this poses significant challenges in data management and energy consumption on the end-device/edge side, specially under dynamic environmental conditions. This has driven the adoption of tiny machine learning (tinyML), which offers data-driven optimization at the end-device/edge side. In this work, we survey and thoroughly discuss various tapped/untapped deployment possibilities of tinyML in wireless networks. We identify existing frameworks, accustomed to design tinyML algorithms, that could be utilized to solve a range of wireless network problems. We present a federated learning-based tinyML model update procedure, for both battery-powered and batteryless end-devices, to resolve the concept drift problem faced by tinyML models. Furthermore, we discuss the update-aware checkpointing, fault-tolerant bootloader, and intermittent-aware modify operation, which could support federated learning-based tinyML model update in the case of batteryless end-devices. Overall, this paper spells out several areas where end-device/edge intelligence can be utilized in the next generation of wireless systems, as well as ways to mitigate the concept drift problem faced in the case of end-device intelligence.

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arXiv2025

3D-HQAM Constellation Design and Performance Evaluation under AWGN

This paper proposes a simple and effective method for constructing higher-order three-dimensional (3D) signal constellations, aiming to enhance the reliability of digital communication systems. The approach systematically extends the conventional two-dimensional hexagonal quadrature amplitude modulation (2D-HQAM) constellation into a 3D-HQAM signal space, forming structured lattice configurations. To address the increased decision complexity resulting from a larger number of constellation points, a dimension reduction (DR) technique is introduced, allowing the derivation of closed-form symbol error probability (SEP) expressions under additive white Gaussian noise (AWGN) conditions. Theoretical SEPs closely match simulation results, validating the accuracy of the proposed method. The minimum Euclidean distance (MED) of the 3D constellations shows a minimum increase of 12.14% over 2D constellation for 8-HQAM, reaching up to 160.81% for 1024-HQAM constellations. This significant improvement in MED leads to enhanced error performance. Therefore, the proposed 3D constellations are promising candidates for high-quality and reliable next-generation digital communication systems.

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arXiv2025

Comprehensive Review of Deep Unfolding Techniques for Next-Generation Wireless Communication Systems

The application of machine learning in wireless communications has been extensively explored, with deep unfolding emerging as a powerful model-based technique. Deep unfolding enhances interpretability by transforming complex iterative algorithms into structured layers of deep neural networks (DNNs). This approach seamlessly integrates domain knowledge with deep learning (DL), leveraging the strengths of both methods to simplify complex signal processing tasks in communication systems. To provide a solid foundation, we first present a brief overview of DL and deep unfolding. We then explore the applications of deep unfolding in key areas, including signal detection, channel estimation, beamforming design, decoding for error-correcting codes, sensing and communication, power allocation, and security. Each section focuses on a specific task, highlighting its significance in emerging 6G technologies and reviewing recent advancements in deep unfolding-based solutions. Finally, we discuss the challenges associated with developing deep unfolding techniques and propose potential improvements to enhance their applicability across diverse wireless communication scenarios.

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arXiv2024

Accurate Closed-Form Solution for Symbol Error Probability in Hexagonal QAM

Future communication systems are anticipated to facilitate applications requiring high data transmission rates while maintaining energy efficiency. Hexagonal quadrature amplitude modulation (HQAM) offers this owing to its compact symbol arrangement within the two-dimensional (2D) plane. Building on the limitations of the current approaches, this letter presents a straightforward and precise approximation for calculating the symbol error probability (SEP) of HQAM in additive white Gaussian noise (AWGN) channel. The analytical and simulation results align across several signal-to-noise ratios (SNR). In addition, the proposed approximation is effective for accurately estimating the SEP of HQAM in scenarios with slow-fading, including those subject to Rayleigh fading.

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arXiv2024

Goal-Oriented Sensor Reporting Scheduling for Non-linear Dynamic System Monitoring

Goal-oriented communication (GoC) is a form of semantic communication where the effectiveness of information transmission is measured by its impact on achieving the desired goal. In Internet-of-Things (IoT) networks, GoC can enable sensors to selectively transmit data relevant to the intended goals of the receiver, thereby facilitating timely decision-making, reducing network congestion, and enhancing spectral efficiency. In this paper, we consider an IoT scenario where an edge node polls sensors monitoring the state of a non-linear dynamic system (NLDS) to respond to the queries of several clients. This work delves into the foregoing GoC problem and solution, which we termed goal-oriented scheduling (GoS). The latter utilizes deep reinforcement learning (DRL) with meticulously devised action space, state space, and reward function. A long short-term memory network is used to estimate the inter-query duration and the corresponding estimation standard deviation. This empowers the proposed DRL scheduler to make judicious decisions, even when no queries are posed. Numerical analysis demonstrates that the proposed GoS reduces the mean square error (MSE) of the query responses compared to the benchmark scheduling methods even as the number of clients and DRL action space increase, which proves its scalability. Moreover, this is attained without polling sensors during $70\% - 87\%$ of the testing phase, thus promoting energy efficiency. Lastly, the complexity of the proposed GoS is relatively lower than the benchmark scheduling methods.

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arXiv2023

On Performance of Integrated Satellite HAPS Ground Communication: Aerial IRS Node vs Terrestrial IRS Node

With a motive of ubiquitous connectivity over the globe with enhanced spectral efficiency, intelligent reflecting surfaces (IRS) integrated satellite-terrestrial communications is a topic of research interest in an infrastructure-deficient remote terrains. In line with this vision, this paper entails the performance analysis of satellite-terrestrial networks leveraging both aerial and terrestrial IRS nodes, with the support of high altitude platforms over diverse fading channels including shadowed Rician, Rician, and Nakagami-$m$ fading channels. The merits of IRS in enhancing spectral efficiency is analyzed through closed-form expressions of outage probability and ergodic rate. Further, the average symbol error rate analysis for the higher-order quadrature amplitude modulation (QAM) schemes such as hexagonal QAM, rectangular QAM, cross QAM, and square QAM is performed. Practical constraints like antenna gains, path loss, and link fading are considered to characterize the satellite terrestrial links. Finally, a comparison between the high-altitude platforms based IRS node and terrestrial IRS nodes is performed and various insights are drawn under various fading scenarios and path loss conditions. This paper contribute towards understanding and potential implementation of IRS-integrated satellite-terrestrial networks for efficient and reliable communication.

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arXiv2022

Online Learning to Cache and Recommend in the Next Generation Cellular Networks

An efficient caching can be achieved by predicting the popularity of the files accurately. It is well known that the popularity of a file can be nudged by using recommendation, and hence it can be estimated accurately leading to an efficient caching strategy. Motivated by this, in this paper, we consider the problem of joint caching and recommendation in a 5G and beyond heterogeneous network. We model the influence of recommendation on demands by a Probability Transition Matrix (PTM). The proposed framework consists of estimating the PTM and use them to jointly recommend and cache the files. In particular, this paper considers two estimation methods namely a) Bayesian estimation and b) a genie aided Point estimation. An approximate high probability bound on the regret of both the estimation methods are provided. Using this result, we show that the approximate regret achieved by the genie aided Point estimation approach is $\mathcal{O}(T^{2/3} \sqrt{\log T})$ while the Bayesian estimation method achieves a much better scaling of $\mathcal{O}(\sqrt{T})$. These results are extended to a heterogeneous network consisting of M small base stations (sBSs) with a central macro base station. The estimates are available at multiple sBSs, and are combined using appropriate weights. Insights on the choice of these weights are provided by using the derived approximate regret bound in the multiple sBS case. Finally, simulation results confirm the superiority of the proposed algorithms in terms of average cache hit rate, delay and throughput.

cs.IT↗

arXiv2021

Study of visual processing techniques for dynamic speckles: a comparative analysis

Main visual techniques used to obtain information from speckle patterns are Fujii method, generalized difference, weighted generalized difference, mean windowed difference, structural function (SF), modified SF, etc. In this work, a comparative analysis of major visual techniques for natural gum sample is carried out. Obtained results conclusively establish SF based method as an optimum tool for visual inspection of dynamic speckle data.

cs.CV↗

arXiv2021

Defect detection and NDE of low-modulus PMMA material using mechanical loading and WFT analysis

In present communication, we report our investigations undertaken towards detection of defects and non-destructive evaluation of low-modulus sample of Poly Methyl Metha Acrylate (PMMA) material using phase measuring deflectometry and windowed Fourier transform (WFT). The slope of the phase provides the information regarding defects and surface variation of the object. Experimental results conclusively establish the viability of the technique.

physics.app-ph↗

arXiv2021

Securing Optical Networks using Quantum-secured Blockchain: An Overview

Deployment of optical network infrastructure and network services is growing exponentially for beyond 5G networks. Since the uptake of e-commerce and e-services has seen unprecedented serge in recent months due to the global COVID-19 pandemic era, the security of such transactions in optical communication has gained much importance. Optical fiber communication networks are vulnerable to several types of security threats, such as single point failure, wormhole attacks, and sybil attacks. Therefore, blockchain is a promising solution to protect confidential information against attacks and helps in achieving trusted network architecture by creating a distributed ledger platform. Recently, blockchain has received much attention because of its decentralized and distributed ledger technology. Hence, blockchain has also been employed to protect network against such attacks. However, blockchain technology's security relies on the platform of computational complexity, and because of the evolution of quantum computers, it will become insecure in the near future. Therefore, for enhancing blockchain security, research focus on combining quantum key distribution (QKD) with blockchain. This new technology is known as quantum-secured blockchain. The article describes the attacks in optical networks and provides a solution to protect network against security attacks by employing quantum-secured blockchain in optical networks. It provides a brief overview of blockchain technology with its security loopholes and focuses on QKD, which makes blockchain technology more robust against quantum-attacks. Next, the article provides a broad view of quantum-secured blockchain and presents the network architecture for future research and development of secure and trusted optical communication networks using quantum-secured blockchain.

cs.NI↗

arXiv2021

On Performance of Energy Harvested Cooperative NOMA Under Imperfect CSI and Imperfect SIC

With the advent of 5G and the need for energy-efficient massively connected wireless networks, in this work, we consider an energy harvesting (EH) based multi-relay downlink cooperative non-orthogonal multiple access (NOMA) system with practical constraints. The base station serves NOMA users with the help of decode-and-forward based multiple EH relays, where relays harvest the energy from the base station's radio frequency. A relay is selected from the multiple K-relay by using a partial relay selection protocol. The system is considered to operate in half-duplex mode over a generalized independent and identical Nakagami$-m$ fading channel. The closed-form expression of outage probability and ergodic rate are derived for users, under the assumption of imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC) at the receiver node. Expression of outage probability and ergodic rate for both users under the assumption of perfect CSI and perfect SIC are also presented. Further, the asymptotic expression for the outage probability is also shown. The derived analytical expressions are verified through Monte-Carlo simulations.

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arXiv2021

6G for Bridging the Digital Divide: Wireless Connectivity to Remote Areas

In telecommunications, network service accessibility as a requirement is closely related to equitably serving the population residing at locations that can most appropriately be described as remote. Remote connectivity, however, would have benefited from a more inclusive consideration in the existing generations of mobile communications. To remedy this, sustainability and its social impact are being positioned as key drivers of sixth generation's (6G) research and standardization activities. In particular, there has been a conscious attempt to understand the demands of remote wireless connectivity, which has led to a better understanding of the challenges that lie ahead. In this perspective, this article overviews the key challenges associated with constraints on network design and deployment to be addressed for providing broadband connectivity to rural areas, and proposes novel approaches and solutions for bridging the digital divide in those regions.

cs.NI↗

arXiv2020

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

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.

cs.IT↗

arXiv2020

A 6G White Paper on Connectivity for Remote Areas

In many places all over the world rural and remote areas lack proper connectivity that has led to increasing digital divide. These areas might have low population density, low incomes, etc., making them less attractive places to invest and operate connectivity networks. 6G could be the first mobile radio generation truly aiming to close the digital divide. However, in order to do so, special requirements and challenges have to be considered since the beginning of the design process. The aim of this white paper is to discuss requirements and challenges and point out related, identified research topics that have to be solved in 6G. This white paper first provides a generic discussion, shows some facts and discusses targets set in international bodies related to rural and remote connectivity and digital divide. Then the paper digs into technical details, i.e., into a solutions space. Each technical section ends with a discussion and then highlights identified 6G challenges and research ideas as a list.

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arXiv2020

A Survey on Design and Performance of Higher-Order QAM Constellations

As the research on beyond 5G heats up, we survey and explore power and bandwidth efficient modulation schemes in details. In the existing publications and in various communication standards, initially square quadrature amplitude modulation (SQAM) constellations (even power of 2) were considered. However, only the square constellations are not efficient for varying channel conditions and rate requirements, and hence, odd power of 2 constellations were introduced. For odd power of 2 constellations, rectangular QAM (RQAM) is commonly used. However, RQAM is not a good choice due to its lower power efficiency, and a modified cross QAM (XQAM) constellation is preferred as it provides improved power efficiency over RQAM due to its energy efficient two dimensional (2D) structure. The increasing demand for high data-rates has further encouraged the research towards more compact 2D constellations which lead to hexagonal lattice structure based constellations, referred to as hexagonal QAM (HQAM). In this work, various QAM constellations are discussed and detailed study of star QAM, XQAM, and HQAM constellations is presented. Generation, peak and average energies, peak-to-average-power ratio, symbol-error-rate, decision boundaries, bit mapping, Gray code penalty, and bit-error-rate of star QAM, XQAM, and HQAM constellations with different constellation orders are presented. Finally, a comparative study of various QAM constellations is presented which justifies the supremacy of HQAM over other QAM constellations. With this, it can be claimed that the use of the HQAM in various wireless communication systems and standards can further improve the performance targeted for beyond 5G wireless communication systems.

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arXiv2020

6G White Paper on Machine Learning in Wireless Communication Networks

The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented.

cs.IT↗

arXiv2019

Non-orthogonal Multiple Access as an Enabler for Massive Connectivity for 5G and Beyond Networks

Two of the most challenging goals to be achieved in the fifth generation (5G) and beyond communication are massive connectivity and higher capacity. The use of traditional orthogonal multiple access techniques limits the number of users that can be served using the available resources due to orthogonality constraint. Moreover, the available resources may not be utilized effectively by the alloted users thereby resulting in inefficiency and user unfairness. This imposes a severe drawback in cases where the number of users to be served are high, like in the 5G networks. Hence, introducing non-orthogonality to the multiple access scheme is advocated as a supreme methodology to serve multiple users simultaneously, thereby enhancing the connectivity. In scenarios with massive number of users, non-orthogonal multiple access scheme increases the number of active connections by superimposing the signal of multi-users on a same resource block, thereby also utilizing the available resources efficiently.

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