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Chan-Byoung Chae

Publications and source records attributed to Chan-Byoung Chae.

190 records · Page 11Linked to original sources

3-D Channel Characteristics for Molecular Communications with an Absorbing Receiver

Within the domain of molecular communications, researchers mimic the techniques in nature to come up with alternative communication methods for collaborating nanomachines. This work investigates the channel transfer function for molecular communication via diffusion. In nature, information-carrying molecules are generally absorbed by the target node via receptors. Using the concentration function, without considering the absorption process, as the channel transfer function implicitly assumes that the receiver node does not affect the system. In this letter, we propose a solid analytical formulation and analyze the signal metrics (attenuation and propagation delay) for molecular communication via diffusion channel with an absorbing receiver in a 3-D environment. The proposed model and the formulation match well with the simulations without any normalization.

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Scaling laws for molecular communication

In this paper, we investigate information-theoretic scaling laws, independent from communication strategies, for point-to-point molecular communication, where it sends/receives information-encoded molecules between nanomachines. Since the Shannon capacity for this is still an open problem, we first derive an asymptotic order in a single coordinate, i.e., i) scaling time with constant number of molecules $m$ and ii) scaling molecules with constant time $t$. For a single coordinate case, we show that the asymptotic scaling is logarithmic in either coordinate, i.e., $Θ(\log t)$ and $Θ(\log m)$, respectively. We also study asymptotic behavior of scaling in both time and molecules and show that, if molecules and time are proportional to each other, then the asymptotic scaling is linear, i.e., $Θ(t)=Θ(m)$.

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Effect of ISI Mitigation on Modulation Techniques in Communication via Diffusion

Communication via diffusion (CvD) is an effective and energy efficient method for transmitting information in nanonetworks. In this work, we focus on a diffusion-based communication system where the reception process is an absorption via receptors. Whenever a molecule hits to the receiver it is removed from the environment. This kind of reception process is called first passage process and it is more complicated compared to diffusion process only. In 3-D environments, obtaining analytical solution for hitting time distribution for realistic cases is complicated, hence we develop an end-to-end simulator for he diffusion-based communication system that sends consecutive symbols. In CvD, each symbol is modulated and demodulated in a time slot called symbol duration, however the long tail distribution of hitting time is the main challenge that affects the symbol detection error. The molecules arriving in the following slots become an interference source when detection takes place. End-to-end simulator enables us to analyze the effect of inter symbol interference (ISI) without making any assumptions on the ISI. We propose an ISI cancellation technique that utilizes decision feedback for compensating the effect of previously demodulated symbol. Three different modulation types are considered with pulse, square, and cosine carrier waves. In case of constraints on transmitter or receiver node it may not be possible to use pulse as a carrier, and peak-to-average messenger molecule metric is defined for this purpose. Results show that, the proposed ISI mitigation technique improves the symbol detection performance and the amplitude-based modulations are improved more than frequency-based modulations.

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Channel and Noise Models for Nonlinear Molecular Communication Systems

Recently, a tabletop molecular communication platform has been developed for transmitting short text messages across a room. The end-to-end system impulse response for this platform does not follow previously published theoretical works because of imperfect receiver, transmitter, and turbulent flows. Moreover, it is observed that this platform resembles a nonlinear system, which makes the rich body of theoretical work that has been developed by communication engineers not applicable to this platform. In this work, we first introduce corrections to the previous theoretical models of the end-to-end system impulse response based on the observed data from experimentation. Using the corrected impulse response models, we then formulate the nonlinearity of the system as noise and show that through simplifying assumptions it can be represented as Gaussian noise. Through formulating the system's nonlinearity as the output a linear system corrupted by noise, the rich toolbox of mathematical models of communication systems, most of which are based on linearity assumption, can be applied to this platform.

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Low Complexity MIMO Detection based on Belief Propagation over Pair-wise Graphs

This paper considers belief propagation algorithm over pair-wise graphical models to develop low complexity, iterative multiple-input multiple-output (MIMO) detectors. The pair-wise graphical model is a bipartite graph where a pair of variable nodes are related by an observation node represented by the bivariate Gaussian function obtained by marginalizing the posterior joint probability density under the Gaussian input assumption. Specifically, we consider two types of pair-wise models, the fully connected and ring-type. The pair-wise graphs are sparse, compared to the conventional graphical model in [18], insofar as the number of edges connected to an observation node (edge degree) is only two. Consequently the computations are much easier than those of maximum likelihood (ML) detection, which are similar to the belief propagation (BP) that is run over the fully connected bipartite graph. The link level performance for non-Gaussian input is evaluated via simulations, and the results show the validity of the proposed algorithms. We also customize the algorithm with Gaussian input assumption to obtain the Gaussian BP run over the two pair-wise graphical models and, for the ring-type, we prove its convergence in mean to the linear minimum mean square error (MMSE) estimates. Since the maximum a posterior (MAP) estimator for Gaussian input is equivalent to the linear MMSE estimator, it shows the optimality, in mean, of the scheme for Gaussian input.

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Network Massive MIMO for Cell-Boundary Users: From a Precoding Normalization Perspective

In this paper, we propose network massive multiple- input multiple-output (MIMO) systems, where three radio units (RUs) connected via one digital unit (DU) support multiple user equipments (UEs) at a cell-boundary through the same radio resource, i.e., the same frequency/time band. For precoding designs, zero-forcing (ZF) and matched filter (MF) with vector or matrix normalization are considered. We also derive the formulae of the lower and upper bounds of the achievable sum rate for each precoding. Based on our analytical results, we observe that vector normalization is better for ZF while matrix normalization is better for MF. Given antenna configurations, we also derive the optimal switching point as a function of the number of active users in a network. Numerical simulations confirm our analytical

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Novel Modulation Techniques using Isomers as Messenger Molecules for Nano Communication Networks via Diffusion

In this paper, we propose three novel modulation techniques, i.e., concentration-based, molecular-type-based, and molecular-ratio-based, using isomers as messenger molecules for nano communication networks via diffusion. To evaluate achievable rate performance, we compare the proposed tech- niques with conventional insulin based concepts under practical scenarios. Analytical and numerical results confirm that the proposed modulation techniques using isomers achieve higher data transmission rate performance (max 7.5 dB signal-to-noise ratio gain) than the insulin based concepts. We also investigate the tradeoff between messenger sizes and modulation orders and provide guidelines for selecting from among several possible candidates.

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Spectrum Leasing via Cooperation for Enhanced Physical-Layer Secrecy

Spectrum leasing via cooperation refers to the possibility of primary users leasing a portion of the spectral resources to secondary users in exchange for cooperation. In the presence of an eavesdropper, this correspondence proposes a novel application of this concept in which the secondary cooperation aims at improving secrecy of the primary network by creating more interference to the eavesdropper than to the primary receiver. To generate the interference in a positive way, this work studies an optimal design of a beamformer at the secondary transmitter with multiple antennas that maximizes a secrecy rate of the primary network while satisfying a required rate for the secondary network. Moreover, we investigate two scenarios depending upon the operation of the eavesdropper: i) the eavesdropper treats the interference by the secondary transmission as an additive noise (single-user decoding) and ii) the eavesdropper tries to decode and remove the secondary signal (joint decoding). Numerical results confirm that, for a wide range of required secondary rate constraints, the proposed spectrum-leasing strategy increases the secrecy rate of the primary network compared to the case of no spectrum leasing.

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Novel Modulation Techniques using Isomers as Messenger Molecules for Molecular Communication via Diffusion

In this paper, we propose novel modulation techniques using isomers as messenger molecules for nano communication via diffusion. To evaluate achievable rate performance, we compare the proposed techniques with concentration-based and molecular-type-based methods. Analytical and numerical results confirm that the proposed modulation techniques achieve higher data transmission rate performance than conventional insulin based concepts.

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A Lattice-Based MIMO Broadcast Precoder for Multi-Stream Transmission

Precoding with block diagonalization is an attractive scheme for approaching sum capacity in multiuser multiple input multiple output (MIMO) broadcast channels. This method requires either global channel state information at every receiver or an additional training phase, which demands additional system planning. In this paper we propose a lattice based multi-user precoder that uses block diagonalization combined with pre-equalization and perturbation for the multiuser MIMO broadcast channel. An achievable sum rate of the proposed scheme is derived and used to show that the proposed technique approaches the achievable sum rate of block diagonalization with water-filling but does not require the additional information at the receiver. Monte Carlo simulations with equal power allocation show that the proposed method provides better bit error rate and diversity performance than block diagonalization with a zero-forcing receiver. Additionally, the proposed method shows similar performance to the maximum likelihood receiver but with much lower receiver complexity.

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