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Sithamparanathan Kandeepan

Publications and source records attributed to Sithamparanathan Kandeepan.

17 recordsLinked to original sources

Pseudo-Noise Superposition for Finite-Alphabet Physical Layer Security

Physical-layer security based on pseudo-noise (PN) superposition is a promising approach for mitigating eavesdropping in future wireless systems. However, under Shannon's capacity formulation with Gaussian signaling, achieving secrecy typically requires allocating substantial transmit power to PN, resulting in a significant reduction in achievable information rate and limiting practical applicability. This limitation is alleviated when finite-alphabet modulation schemes, such as M-ary Quadrature Amplitude Modulation ($M$-QAM), are employed, as expected in practical 6G transceivers. In this work, we analyze the information rate performance of PN-assisted systems under $M$-QAM signaling using mutual information and derive the corresponding achievable secrecy rate. The impact of PN power allocation on both the legitimate user and the eavesdropper is investigated across different modulation orders and channel conditions. Monte Carlo simulations are conducted to evaluate system behavior under varying user and eavesdropper channel conditions and to examine how PN power allocation influences secrecy performance. The results show that, at sufficiently high signal-to-noise ratio (SNR), the information rate becomes largely insensitive to PN power allocation, enabling near-perfect secrecy with $M$-QAM modulation-highlighting a key departure from Shannon-capacity-based secrecy analyses and underscoring the practicality of finite-alphabet security mechanisms for 6G wireless systems.

eess.SP

Intelligent Spectrum Management in Satellite Communications

Satellite Communication (SatCom) networks represent a fundamental pillar in modern global connectivity, facilitating reliable service and extensive coverage across a plethora of applications. The expanding demand for high-bandwidth services and the proliferation of mega satellite constellations highlight the limitations of traditional exclusive satellite spectrum allocation approaches. Cognitive Radio (CR) leading to Cognitive Satellite (CogSat) networks through Dynamic Spectrum Management (DSM), which enables the dynamic adaptability of radio equipment to environmental conditions for optimal performance, presents a promising solution for the emerging spectrum scarcity. In this survey, we explore the adaptation of intelligent DSM methodologies to SatCom, leveraging satellite network integrations. We discuss contributions and hurdles in regulations and standardizations in realizing intelligent DSM in SatCom, and deep dive into DSM techniques, which enable CogSat networks. Furthermore, we extensively evaluate and categorize state-of-the-art Artificial Intelligence (AI)/Machine Learning (ML) methods leveraged for DSM while exploring operational resilience and robustness of such integrations. In addition, performance evaluation metrics critical for adaptive resource management and system optimization in CogSat networks are thoroughly investigated. This survey also identifies open challenges and outlines future research directions in regulatory frameworks, network architectures, and intelligent spectrum management, paving the way for sustainable and scalable SatCom networks for enhanced global connectivity.

cs.NI

Dynamic Scheduling for Enhanced Performance in RIS-assisted Cooperative Network with Interference

Reconfigurable Intelligent Surfaces (RIS) have emerged as transformative technologies, enhancing spectral efficiency and improving interference management in multi-user cooperative communications. This paper investigates the integration of RIS with Flexible-Duplex (FlexD) communication, featuring dynamic scheduling capabilities, to mitigate unintended external interference in multi-user wireless networks. By leveraging the reconfigurability of RIS and dynamic scheduling, we propose a user-pair selection scheme to maximize system throughput when full channel state information (CSI) of interference is unavailable. We develop a mathematical framework to evaluate the throughput outage probability when RIS introduces spatial correlation. The derived analytical results are used for asymptotic analysis, providing insights into dynamic user scheduling under interference based on statistical channel knowledge. Finally, we compare FlexD with traditional Full Duplex (FD) and Half Duplex (HD) systems against RIS-assisted FlexD. Our results show FlexD's superior throughput enhancement, energy efficiency and data management capability in interference-affected networks, typical in current and next-generation cooperative wireless applications like cellular and vehicular communications.

eess.SP

Interference Mitigation in LEO Constellations with Limited Radio Environment Information

This research paper delves into interference mitigation within Low Earth Orbit (LEO) satellite constellations, particularly when operating under constraints of limited radio environment information. Leveraging cognitive capabilities facilitated by the Radio Environment Map (REM), we explore strategies to mitigate the impact of both intentional and unintentional interference using planar antenna array (PAA) beamforming techniques. We address the complexities encountered in the design of beamforming weights, a challenge exacerbated by the array size and the increasing number of directions of interest and avoidance. Furthermore, we conduct an extensive analysis of beamforming performance from various perspectives associated with limited REM information: static versus dynamic, partial versus full, and perfect versus imperfect. To substantiate our findings, we provide simulation results and offer conclusions based on the outcomes of our investigation.

eess.SP

Artificial Intelligence Techniques for Next-Generation Mega Satellite Networks

Space communications, particularly massive satellite networks, re-emerged as an appealing candidate for next generation networks due to major advances in space launching, electronics, processing power, and miniaturization. However, massive satellite networks rely on numerous underlying and intertwined processes that cannot be truly captured using conventionally used models, due to their dynamic and unique features such as orbital speed, inter-satellite links, short pass time, and satellite footprint, among others. Hence, new approaches are needed to enable the network to proactively adjust to the rapidly varying conditions associated within the link. Artificial intelligence (AI) provides a pathway to capture these processes, analyze their behavior, and model their effect on the network. This article introduces the application of AI techniques for integrated terrestrial satellite networks, particularly massive satellite network communications. It details the unique features of massive satellite networks, and the overarching challenges concomitant with their integration into the current communication infrastructure. Moreover, this article provides insights into state-of-the-art AI techniques across various layers of the communication link. This entails applying AI for forecasting the highly dynamic radio channel, spectrum sensing and classification, signal detection and demodulation, inter-satellite and satellite access network optimization, and network security. Moreover, future paradigms and the mapping of these mechanisms onto practical networks are outlined.

cs.NI

Next Generation Mega Satellite Networks: Opportunities, Challenges, and Performance

Digital connectivity has become the foundation of prosperity and an essential need for functioning societies. Despite this dependence, limitation on Internet access remains a prevalent issue, largely hinged on socioeconomic and geographic factors. A promising solution to attain global access equality is based on integrated terrestrial-satellite networks that rely on low Earth orbit (LEO) mega constellations. While the benefits of LEO constellations complement the shortcomings of terrestrial networks, their incorporation impacts the network design, adding complexity and challenges. This article presents a systematic analysis of next generation LEO mega satellite constellations and outlines opportunities by virtue of the many benefits these constellations can provide and highlights the major challenges. Furthermore, it provides a synopsis of analytic models and underscores modern simulation approaches for next generation mega satellite constellations. This provides network designers with the necessary insights into satellite network performance.

cs.IT

On the Bound of Energy Consumption in Cellular IoT Networks

Billions of sensors are expected to be connected to the Internet through the emerging Internet of Things (IoT) technologies. Many of these sensors will primarily be connected using wireless technologies powered using batteries as their sole energy source which makes it paramount to optimize their energy consumption. In this paper, we provide an analytic framework of the energy-consumption profile and its lower bound for an IoT end device formulated based on Shannon capacity. We extend the study to model the average energy-consumption performance based on the random geometric distribution of IoT gateways by utilizing tools from stochastic geometry and real measurements of interference in the ISM-band. Experimental data, interference measurements and Monte-Carlo simulations are presented to validate the plausibility of the proposed analytic framework, where results demonstrate that the current network infrastructures performance is bounded between two extreme geometric models. This study considers interference seen by a gateway regardless of its source.

cs.IT

Stochastic Geometry Methods for Modelling Automotive Radar Interference

As the use of automotive radar increases, performance limitations associated with radar-to-radar interference will become more significant. In this paper we employ tools from stochastic geometry to characterize the statistics of radar interference. Specifically, using two different models for vehicle spacial distributions, namely, a Poisson point process and a Bernoulli lattice process, we calculate for each case the interference statistics and obtain analytical expressions for the probability of successful range estimation. Our study shows that the regularity of the geometrical model appears to have limited effect on the interference statistics, and so it is possible to obtain tractable tight bounds for worst case performance. A technique is proposed for designing the duty cycle for random spectrum access which optimizes the total performance. This analytical framework is verified using Monte-Carlo simulations.

cs.IT

Nearest Neighbour Distance Distribution in Hard-Core Point Processes

In this paper we present an analytic framework for formulating the statistical distribution of the nearest neighbour distance in hard-core point processes. We apply this framework to Matérn hard-core point process (MHC) to derive the cumulative distribution function of the contact distance in three cases. The first case is between a point in an MHC process and its nearest neighbour from the same process. The second case is between a point in an independent Poisson point process and the nearest neighbour from an MHC process. The third case is between a point in the complement of an MHC process and its sibling MHC process. We test the analytic results against Monte-Carlo simulations to verify their consistency.

cs.IT

Regularizing Random Points: Complementary Matérn Hard-Core Point Process

In this paper we present a tractable approach for regularizing randomly placed points, by splitting them into two subsets: the first is generated by means of the Matérn hard-core point process, while the remaining points constitute the complementary Matérn hard-core point process. We study the characteristics of these processes, deriving its pair-correlation functions, and the distribution of the distance to the nearest neighbour. The results have several applications in wireless communications, including the modeling of wireless sensor networks, where we investigate an example of regularizing such networks and illustrate its advantage in reducing the energy consumption of wireless nodes.

math.ST

On Modeling Coverage and Rate of Random Cellular Networks under Generic Channel Fading

In this paper we provide an analytic framework for computing the expected downlink coverage probability, and the associated data rate of cellular networks, where base stations are distributed in a random manner. The provided expressions are in computable integral forms that accommodate generic channel fading conditions. We develop these expressions by modelling the cellular interference using stochastic geometry analysis, then we employ them for comparing the coverage resulting from various channel fading conditions namely Rayleigh and Rician fading, in addition to the fading-less channel. Furthermore, we expand the work to accommodate the effects of random frequency reuse on the cellular coverage and rate. Monte-Carlo simulations are conducted to validate the theoretical analysis, where the results show a very close match.

cs.IT

Designing and Implementing Future Aerial Communication Networks

Providing "connectivity from the sky" is the new innovative trend in wireless communications. High and low altitude platforms, drones, aircrafts and airships are being considered as the candidates for deploying wireless communications complementing the terrestrial communication infrastructure. In this article, we report the detailed account of the design and implementation challenges of an aerial network consisting of LTE Advanced (LTE-A) base stations. In particular, we review achievements and innovations harnessed by an aerial network composed of Helikite platforms. Helikites can be raised in the sky to bring Internet access during special events and in the aftermath of an emergency. The trial phase of the system mounting LTE-A technology onboard Helikites to serve users on the ground showed not only to be very encouraging but that such a system could offer even a longer lasting solution provided that inefficiency in powering the radio frequency equipment in the Helikite can be overcome.

cs.NI

Aerial-Terrestrial Communications: Terrestrial Cooperation and Energy-Efficient Transmissions to Aerial-Base Stations

Hybrid aerial-terrestrial communication networks based on Low Altitude Platforms (LAPs) are expected to optimally meet the urgent communication needs of emergency relief and recovery operations for tackling large scale natural disasters. The energy-efficient operation of such networks is important given the fact that the entire network infrastructure, including the battery operated ground terminals, exhibits requirements to operate under power-constrained situations. In this paper, we discuss the design and evaluation of an adaptive cooperative scheme intended to extend the survivability of the battery operated aerial-terrestrial communication links. We propose and evaluate a real-time adaptive cooperative transmission strategy for dynamic selection between direct and cooperative links based on the channel conditions for improved energy efficiency. We show that the cooperation between mobile terrestrial terminals on the ground could improve the energy efficiency in the uplink depending on the temporal behavior of the terrestrial and the aerial uplink channels. The corresponding delay in having cooperative (relay-based) communications with relay selection is also addressed. The simulation analysis corroborates that the adaptive transmission technique improves the overall energy efficiency of the network whilst maintaining low latency enabling real time applications.

cs.NI

Airborne Base Stations for Emergency and Temporary Events

This paper introduces a rapidly deployable wireless network based on Low Altitude Platforms and portable land units to support disaster-relief activities, and to extend capacity during temporary mass events. The system integrates an amalgam of radio technologies such as LTE, WLAN and TETRA to provide heterogeneous communications in the deployment location. Cognitive radio is used for autonomous network configuration. Sensor networks monitor the environment in real-time during relief activities and provide distributed spectrum sensing capacities. Finally, remote communications are supported via S-band satellite links.

cs.NI

Adaptive Energy Efficient Communications for Hybrid Aerial-Terrestrial Systems

Aerial telecommunications networks based on Low Altitude Platforms (LAPs) are expected to optimally meet the urgent needs of emergency relief and recovery operations for tackling large scale natural disasters. The energy efficient operation of such networks is important given the fact that the entire network infrastructure including the battery operated ground terminals, exhibit requirements to operate under power constrained situations. In this paper, we propose and evaluate a real-time adaptive transmission strategy for dynamic selection of direct and cooperative links based on the channel conditions for improved energy efficiency. We show that the cooperation between mobile terrestrial terminals on the ground could improve the energy efficiency in the uplink depending on the temporal behavior of the terrestrial and the aerial uplink channels. The simulation analysis corroborates that the adaptive transmission technique improves the overall energy efficiency of the network.

cs.NI

Energy Aware Routing in Heterogeneous Multi-Hop Wireless Networks

Heterogeneous wireless networks with wireless devices supporting multitude of radio access technologies are witnessing increasing interest from network providers and consumers alike. Energy efficiency in such networks has become an important design consideration due to the limited battery life of mobile terminals on one side, and the ever increasing operational expenses pertaining to energy expenditure on the other. In this paper, we present a routing protocol for multi-radio multi-hop wireless networks, which aims to achieve a trade-off between energy consumption in the network and routing delay, considering both the energy consumption at the devices and the link energy costs. We also present optimum route-path selection strategies by defining a utility function to minimize the energy consumption in the network while maximizing the network lifetime. Using simulations, we verify the utility of the route-path selection strategies and the efficiency of the energy aware routing algorithm. It turns out that the proposed protocol is energy efficient in terms of path selection, with a slight compromise in the end-to-end delay.

cs.NI

An Integrated Aerial Telecommunications Network that Supports Emergency Traffic

This paper outlines how an aerial telecommunications network can optimally meet the stringent needs of emergency relief and recovery operations. We propose a novel architecture, made of an integrated and highly dynamic multi-purpose aerial telecommunications infrastructure that can be contextually extended with fast-deploying high or low altitude platforms. In particular, we analyze the interest and challenges of adapting core concepts from substitution networks and controlled mobility mechanisms, so that a base network can be seamlessly augmented, both in terms of capacity and functions. We give an estimation of the emergency traffic supported by the lower altitude platforms in an example scenario and discuss the challenges posed by this architecture, notably in terms of disaster resilience and ability to efficiently provide sustained first responder communications.

cs.NI