arXiv subjects

Kiseon Kim

Publications and source records attributed to Kiseon Kim.

At least 19 recordsLinked to original sources

arXiv2024

Multi-population Differential Evolution for RSS based Cooperative Localization in Wireless Sensor Networks with Limited Communication Range

This paper presents a novel approach to deal with the cooperative localization problem in wireless sensor networks based on received signal strength measurements. In cooperative scenarios, the cost function of the localization problem becomes increasingly nonlinear and nonconvex due to the heightened interaction between sensor nodes, making the estimation of the positions of the target nodes more challenging. Although most of existing cooperative localization algorithms assure acceptable localization accuracy, their computational complexity increases dramatically, which may restrict their applicability. To reduce the computational complexity and provide competitive localization accuracy at the same time, we propose a localization algorithm based on the differential evolution with multiple populations, opposite-based learning, redirection, and anchoring. In this work, the cooperative localization cost function is split into several simpler cost functions, each of which accounts only for one individual target node. Then, each cost function is solved by a dedicated population of the proposed algorithm. In addition, an enhanced version of the proposed algorithm which incorporates the population midpoint scheme for further improvement in the localization accuracy is devised. Simulation results demonstrate that the proposed algorithms provide comparative localization accuracy with much lower computational complexity compared with the state-of-the-art algorithms.

eess.SP↗

arXiv2020

Deterministic Models in Epidemiology: From Modeling to Implementation

The abrupt outbreak and transmission of biological diseases has always been a long-time concern of humankind. For long, mathematical modeling has served as a simple and yet efficient tool to investigate, predict, and control spread of communicable diseases through individuals. A myriad of works on epidemic models and their variants have been reported in the literature. For better prediction of the dynamics of a particular disease, it is important to adopt the most suitable model. In this paper, we study some of the widely-appreciated deterministic epidemic models in which the population is divided into compartments based on the health status of each individual. In particular, we provide a demographic classification of such models and study each of them in terms of mathematical formulation, near equilibrium point stability properties, and disease outbreak threshold conditions (basic reproduction ratio). Furthermore, we discuss the various influential factors that need to be considered during epidemic modeling. The main objective of this article is to provide a basic understanding of the mathematical complexity incurred in deterministic epidemic models with the aid of graphical illustrations obtained through implementation.

q-bio.PE↗

arXiv2019

Design of Anti-Jamming Waveforms for Time-Hopping Spread Spectrum Systems in Tone Jamming Environments

We consider the problem of designing waveforms for mitigating single tone jamming (STJ) signals with an estimated jamming frequency in time-hopping spread spectrum (TH SS) systems. The proposed design of waveforms optimizes the anti-jamming (AJ) performance of TH SS systems by minimizing the correlation between the template and STJ signals, in which the problem of waveform optimization is simplified by employing a finite number of rectangular pulses. The simplification eventually makes the design of waveforms be converted into a problem of finding eigenvalues and eigenvectors of a matrix. Simulation results show that the waveforms designed by the proposed scheme provide us with performance superior not only to the conventional waveforms but also to the clipper receiver in the mitigation of STJ. The waveforms from the proposed design also exhibit a desirable AJ capability even when the estimated frequency of the STJ is not perfect.

eess.SP↗

arXiv2018

Designing Anti-Jamming Receivers for NR-DCSK Systems Utilizing ICA, WPD, and VMD Methods

In this work, we consider an advanced noise reduction differential chaotic shift keying (NR-DCSK) system in which a single antenna source communicates with a single antenna destination under the attack of a single antenna jammer. We devote our efforts to design a novel anti-jamming (AJ) receiver for the considered system. Particularly, we propose a variational mode decomposition-independent component analysis-wavelet packet decomposition-based (VMD-ICA-WPD-based) structure, in which the VMD method is firstly exploited to generate multiple signals from the single received one. Secondly, the ICA method is applied to coarsely separate chaotic and jamming signals. After that, the WPD method is used to finely estimate and mitigate jamming signals that exist on all outputs of the ICA method. Finally, an inverse ICA procedure is carried out, followed by a summation, and the outcome is passed through the conventional correlation-based receiver for recovering the transmitted information. Simulation results show that the proposed receiver provides significant system performance enhancement compared to that given by the conventional correlation-based receiver with WPD, i.e. 8 dB gain at BER =0.03 and Eb/N0 = 20 dB.

eess.SP↗

arXiv2018

Doppler Spectrum Analysis of a Roadside Scatterer Model for Vehicle-to-Vehicle Channels: An Indirect Method

In vehicle-to-vehicle (V2V) channels, such roadside scatterers (RSSs) as houses, buildings, trees, and many more, play a crucial role in the determination of the Doppler power spectral density (DPSD) characteristics. However, the relevant research results are scarce due to the lack of computationally tractable analytic DPSD solutions. To fill this gap, we investigate an indirect method for the DPSD analysis of a generic two-dimensional (2D) RSS model for V2V channels. The indirect method, based on the Hoeher's theorem, employs successive transformations of random variables to obtain the DPSD. Compared to the conventional methods, leading to impractical multiple integral solutions, our method yields a single integral-form, more useful for analytic studies, model validation/parameter estimation, and fading simulator design. Using the new DPSD solution, the impact of different RSS layouts on the DPSD characteristics is further investigated, and several new insights are provided. The joint probability density function (PDF) of angle-of-departure and angle-of-arrival (AoA) and the joint Doppler-AoA PDF are newly presented in closed-forms and analyzed with respect to the DPSD shape. Comparisons with the DPSDs measured in highway and \FB{urban canyon} environments demonstrate not only the validity of the generic 2D RSS model, but also the significant contribution of RSSs to V2V channels.

cs.IT↗

arXiv2018

Analysis and Optimization for Weighted Sum Rate in Energy Harvesting Cooperative NOMA Systems

We consider a cooperative non-orthogonal multiple access system with radio frequency energy harvesting, in which a user with good channel harvests energy from its received signal and serves as a decode-and-forward relay for enhancing the performance of a user with poor channel. We here aim at maximizing the weighted sum rate of the system by optimizing the power allocation coefficient used at the source and the power splitting coefficient used at the user with good channel. By exploiting the specific structure of the considered problem, we propose a low-complexity one-dimensional search algorithm which can provide optimal solution to the problem. As a benchmark comparison, we derive analytic expressions and simple high signal-to-noise ratio (SNR) approximations of the ergodic rates achieved at two users and their weighted sum with fixed values of the power allocation and the power splitting coefficients, from which the scaling of the weighted sum in the high SNR region is revealed. Finally, we provided numerical results to demonstrate the validity of the optimized scheme. Index Terms-Cooperative NOMA, RF-energy harvesting, weighted sum rate analysis and optimization.

cs.IT↗

arXiv2018

An iALM-ICA-based Anti-Jamming DS-CDMA Receiver for LMS Systems

We consider a land mobile satellite communication system using spread spectrum techniques where the uplink is exposed to MT jamming attacks, and the downlink is corrupted by multi-path fading channels. We proposes an anti-jamming receiver, which exploits inherent low-dimensionality of the received signal model, by formulating a robust principal component analysis (Robust PCA)-based recovery problem. Simulation results verify that the proposed receiver outperforms the conventional receiver for a reasonable rank of the jamming signal.

cs.IT↗

arXiv2017

Performance Analysis of a Cognitive Radio Network with an Energy Harvesting Secondary Transmitter under Nakagami-m Fading

In this paper, we consider an overlay cognitive radio network, in which a secondary transmitter (ST) is willing to relay the information of a primary transmitter toward a primary receiver. In return, ST can access the licensed band to send its own information superimposed with the primary signal to a secondary receiver. The power-limited ST uses a power splitting protocol to harvest energy from its received signal to increase its transmit power. We analyze the performance of the primary and the secondary systems under independent Nakagami-m fading by deriving their corresponding outage probabilities in integral-based expressions. In addition, by considering the high signal-to-noise ratio, we obtain very tight closed-form approximations of the outage probabilities. Thereafter, by further analyzing the approximations, we reveal novel insights on the diversity orders and coding gains of the two systems. Our analytical results are validated through extensive Monte-Carlo simulations.

cs.IT↗

arXiv2017

Physical Layer Security Schemes for Full-Duplex Cooperative Systems: State of the Art and Beyond

Due to the broadcast nature of wireless medium, wireless communication is highly vulnerable to eavesdropping attack. Traditionally, secure wireless data transmission has relied on cryptographic techniques at the network layer which incur high computational power and complexity. As an alternative, physical layer security (PLS) is emerging as a promising paradigm to protect wireless systems by exploiting the physical characteristics of the wireless channels. Among various PLS approaches, the one based on cooperative communication is favorable and has got a lot of interest from the research community. Although PLS schemes with half-duplex relays have been extensively discovered, the issue of PLS in cooperative systems with full-duplex (FD) relays is far from being comprehensively understood. In this paper, we first present the state of the art on PLS approaches proposed for FD cooperative systems. We then provide a case study in which a source-based jamming scheme is proposed to enhance the secrecy performance of a cooperative system with an untrusted FD relay. Finally, we outline several interesting yet challenging future research problems in this topic.

cs.IT↗

arXiv2017

On the Anti-Jamming Performance of the NR-DCSK System

This paper investigates the anti-jamming performance of the NR-DCSK system. We consider several practical jamming environments including broad-band jamming (BBJ), partial-time jamming (PTJ), tone jamming (TJ) consisting of both single-tone and multi-tone, and sweep jamming (SWJ). We first analytically derived the bit error rates of the considered system under the BBJ and the PTJ environments in closed-form expressions. Our derived results show that the system performances under these two jamming environments are enhanced as $P$ increases, where $P$ is the parameter of the NR-DCSK modulation scheme denoting the number of times a chaotic sample is repeated. In addition, our results demonstrate that for the PTJ, the optimal value of the jamming factor is close to zero when the jamming power is small, however, it increases and approaches one as the jamming power enlarges. We then investigate the performance of the considered system under the TJ and the SWJ environments via Monte-Carlo simulations. Our simulations show that single-tone jamming causes a more significant performance degradation than that provided by multi-tone jamming counterparts. Moreover, we point out that the system performance is significantly degraded when the starting frequency of the sweep jammer is close to the carrier frequency of the transmitted chaotic signals, the sweep bandwidth is small, and the sweep time is half of the transmitted bit duration.

cs.IT↗

arXiv2016

Overlay Secondary Spectrum Sharing with Independent Re-attempts in Cognitive Radios

Opportunistic spectrum access (OSA) is a promising reform paradigm envisioned to address the issue of spectrum scarcity in cognitive radio networks (CRNs). While current models consider various aspects of the OSA scheme, the impact of retrial phenomenon in multi-channel CRNs has not yet been analyzed. In this work, we present a continuous-time Markov chain (CTMC) model in which the blocked/preempted secondary users (SUs) enter a finite retrial group (or orbit) and re-attempt independently for service in an exponentially distributed random manner. Taking into account the inherent retrial tendency of SUs, we numerically assess the performance of the proposed scheme in terms of dropping probability and throughput of SUs.

cs.PF↗

arXiv2016

Transient Analysis of a Resource-limited Recovery Policy for Epidemics: a Retrial Queueing Approach

Knowledge on the dynamics of standard epidemic models and their variants over complex networks has been well-established primarily in the stationary regime, with relatively little light shed on their transient behavior. In this paper, we analyze the transient characteristics of the classical susceptible-infected (SI) process with a recovery policy modeled as a state-dependent retrial queueing system in which arriving infected nodes, upon finding all the limited number of recovery units busy, join a virtual buffer and try persistently for service in order to regain susceptibility. In particular, we formulate the stochastic SI epidemic model with added retrial phenomenon as a finite continuous-time Markov chain (CTMC) and derive the Laplace transforms of the underlying transient state probability distributions and corresponding moments for a closed population of size $N$ driven by homogeneous and heterogeneous contacts. Our numerical results reveal the strong influence of infection heterogeneity and retrial frequency on the transient behavior of the model for various performance measures.

eess.SY↗

arXiv2016

Profit-aware Online Vehicle-to-Grid Decentralized Scheduling under Multiple Charging Stations

Fluctuations in electricity tariffs induced by the sporadic nature of demand loads on power grids has initiated immense efforts to find optimal scheduling solutions for charging and discharging plug-in electric vehicles (PEVs) subject to different objective sets. In this paper, we consider vehicle-to-grid (V2G) scheduling at a geographically large scale in which PEVs have the flexibility of charging/discharging at multiple smart stations coordinated by individual aggregators. We first formulate the objective of maximizing the overall profit of both, demand and supply entities, by defining a weighting parameter. We then propose an online decentralized greedy algorithm for the formulated mixed integer non-linear programming (MINLP) problem, which incorporates efficient heuristics to practically guide each incoming vehicle to the most appropriate charging station (CS). The better performance of the presented algorithm compared to an alternative allocation strategy is demonstrated through simulations in terms of the overall achievable profit and flatness of the final electricity load. Moreover, the results of simulations reveal the existence of optimal number of deployed stations at which the overall profit can be maximized.

eess.SY↗

arXiv2016

Circular Sphere Decoding: A Low Complexity Detection for MIMO Systems with General Two-dimensional Signal Constellations

We propose a low complexity complex valued Sphere Decoding (CV-SD) algorithm, referred to as Circular Sphere Decoding (CSD) which is applicable to multiple-input multiple-output (MIMO) systems with arbitrary two dimensional (2D) constellations. CSD provides a new constraint test. This constraint test is carefully designed so that the element-wise dependency is removed in the metric computation for the test. As a result, the constraint test becomes simple to perform without restriction on its constellation structure. By additionally employing this simple test as a prescreening test, CSD reduces the complexity of the CV-SD search. We show that the complexity reduction is significant while its maximum-likelihood (ML) performance is not compromised. We also provide a powerful tool to estimate the pruning capacity of any particular search tree. Using this tool, we propose the Predict-And-Change strategy which leads to a further complexity reduction in CSD. Extension of the proposed methods to soft output SD is also presented.

cs.IT↗

arXiv2015

Performance Analysis of an Unreliable $M/G/1$ Retrial Queue with Two-way Communication

Efficient use of call center operators through technological innovations more often come at the expense of added operation management issues. In this paper, the stationary characteristics of an $M/G/1$ retrial queue is investigated where the single server, subject to active failures, primarily attends incoming calls and directs outgoing calls only when idle. The incoming calls arriving at the server follow a Poisson arrival process, while outgoing calls are made in an exponentially distributed time. On finding the server unavailable (either busy or temporarily broken down), incoming calls intrinsically join the virtual orbit from which they re-attempt for service at exponentially distributed time intervals. The system stability condition along with probability generating functions for the joint queue length distribution of the number of calls in the orbit and the state of the server are derived and evaluated numerically in the context of mean system size, server availability, failure frequency and orbit waiting time.

cs.NI↗

arXiv2015

Bernoulli-Gaussian Approximate Message-Passing Algorithm for Compressed Sensing with 1D-Finite-Difference Sparsity

This paper proposes a fast approximate message-passing (AMP) algorithm for solving compressed sensing (CS) recovery problems with 1D-finite-difference sparsity in term of MMSE estimation. The proposed algorithm, named ssAMP-BGFD, is low-computational with its fast convergence and cheap per-iteration cost, providing phase transition nearly approaching to the state-of-the-art. The proposed algorithm is originated from a sum-product message-passing rule, applying a Bernoulli-Gaussian (BG) prior, seeking an MMSE solution. The algorithm construction includes not only the conventional AMP technique for the measurement fidelity, but also suggests a simplified message-passing method to promote the signal sparsity in finite-difference. Furthermore, we provide an EM-tuning methodology to learn the BG prior parameters, suggesting how to use some practical measurement matrices satisfying the RIP requirement under the ssAMP-BGFD recovery. Extensive empirical results confirms performance of the proposed algorithm, in phase transition, convergence speed, and CPU runtime, compared to the recent algorithms.

cs.IT↗

arXiv2015

Fast Signal Separation of 2D Sparse Mixture via Approximate Message-Passing

Approximate message-passing (AMP) method is a simple and efficient framework for the linear inverse problems. In this letter, we propose a faster AMP to solve the \emph{$L_1$-Split-Analysis} for the 2D sparsity separation, which is referred to as \emph{MixAMP}. We develop the MixAMP based on the factor graphical modeling and the min-sum message-passing. Then, we examine MixAMP for two types of the sparsity separation: separation of the direct-and-group sparsity, and that of the direct-and-finite-difference sparsity. This case study shows that the MixAMP method offers computational advantages over the conventional first-order method, TFOCS.

cs.IT↗

arXiv2015

Bayesian Hypothesis Test using Nonparametric Belief Propagation for Noisy Sparse Recovery

This paper proposes a low-computational Bayesian algorithm for noisy sparse recovery (NSR), called BHT-BP. In this framework, we consider an LDPC-like measurement matrices which has a tree-structured property, and additive white Gaussian noise. BHT-BP has a joint detection-and-estimation structure consisting of a sparse support detector and a nonzero estimator. The support detector is designed under the criterion of the minimum detection error probability using a nonparametric belief propagation (nBP) and composite binary hypothesis tests. The nonzeros are estimated in the sense of linear MMSE, where the support detection result is utilized. BHT-BP has its strength in noise robust support detection, effectively removing quantization errors caused by the uniform sampling-based nBP. Therefore, in the NSR problems, BHT-BP has advantages over CS-BP which is an existing nBP algorithm, being comparable to other recent CS solvers, in several aspects. In addition, we examine impact of the minimum nonzero value of sparse signals via BHT-BP, on the basis of the results of the recent literature. Our empirical result shows that variation of x_min is reflected to recovery performance in the form of SNR shift.

cs.IT↗