arXiv subjects

Song-Nam Hong

Publications and source records attributed to Song-Nam Hong.

At least 37 records · Page 2Linked to original sources

arXiv2017

Revealing the stability and efficiency enhancement in mixed halide perovskites MAPb(I$_{1-x}$Cl$_x$)$_3$ with ab initio calculations

A little addition of Cl to \ce{MAPbI3} has been reported to improve the material stability as well as light harvesting and carrier conducting properties of organometal trihalide perovskites, the key component of perovskite solar cell (PSC). However, the mechanism of performance enhancement of PSC by Cl addition is still unclear. Here, we apply the efficient virtual crystal approximation method to revealing the effects of Cl addition on the structural, electronic, optical properties and material stability of \ce{MAPb(I_{1-x}Cl_x)3}. Our {\it ab initio} calculations present that as the increase of Cl content cubic lattice constants and static dielectric constants decrease linearly, while band gaps and exciton binding energies increase quadratically. Moreover, we find the minimum of exciton binding energy at the Cl content of 7\%, at which the chemical decomposition reaction changes coincidentally to be from exothermic to endothermic. Interactions among constituents of compound and electronic charge transferring during formation are carefully discussed. This reveals new prospects for understanding and designing of stable, high efficiency PSCs.

cond-mat.mtrl-sci↗

arXiv2017

Ab initio thermodynamic study of SnO$_2$(110) surface in an O$_2$ and NO environment: a fundamental understanding of gas sensing mechanism for NO and NO$_2$

For the purpose of elucidating the gas sensing mechanism of SnO$_2$ for NO and NO$_2$ gases, we calculate the phase diagram of SnO$_2$(110) surface in contact with an O$_2$ and NO gas environment by means of {\it ab initio} thermodynamic method. Firstly we build a range of surface slab models of oxygen pre-adsorbed SnO$_2$(110) surfaces using (1$\times$1) and (2$\times$1) surface unit cells and calculate their Gibbs free energies considering only oxygen chemical potential. The fully reduced surface containing the bridging and in-plane oxygen vacancies in the oxygen-poor condition, while the fully oxidized surface containing the bridging oxygen and oxygen dimer in the oxygen-rich condition, and the stoichiometric surface in between, were proved to be most stable. Using the selected plausible NO-adsorbed surfaces, we then determine the surface phase diagram of SnO$_2$(110) surfaces in ($Δμ_\text{O}$, $Δμ_\text{NO}$) space. In the NO-rich condition, the most stable surfaces were those formed by NO adsorption on the most stable surfaces in contact with only oxygen gas. Through the analysis of electronic charge transferring and density of states during NO$_x$ adsorption on the surface, we provide a meaningful understanding about the gas sensing mechanism.

cond-mat.mtrl-sci↗

arXiv2017

First-principles study of ternary graphite compounds cointercalated with alkali atoms (Li, Na, and K) and alkylamines towards alkali ion battery applications

Using density functional theory calculations, we have investigated the structural, energetic, and electronic properties of ternary graphite intercalation compounds (GICs) containing alkali atoms (AM) and normal alkylamine molecules (nC$x$), denoted as AM-nC$x$-GICs (AM=Li, Na, K, $x$=1, 2, 3, 4). The orthorhombic unit cells have been used to build the models for crystalline stage-I AM-nC$x$-GICs. By performing the variable cell relaxations and the analysis of results, we have found that with the increase in the atomic number of alkali atoms the layer separations decreases in contrast to AM-GICs, while the bond lengths of alkali atoms with graphene layer and nitrogen atom of alkylamine decreases. The formation and interlayer binding energies of AM-nC3-GICs have been calculated, indicating the increase in stability from Li to K. The calculated energy barriers for migration of alkali atoms suggest that alkali cation with larger ionic radius diffuses in graphite more smoothly, being similar to AM-GICs. The analysis of density of states, electronic density differences, and atomic populations illustrates a mechanism how the insertion of especially Na among alkali atoms into graphite with first stage can be made easy by cointercalation with alkylamine, more extent of electronic charge transfer is occurred from more electropositive alkali atom to carbon ring of graphene layer, while alkylamine molecules interact strongly with graphene layer through the hybridization of valence electron orbitals.

cond-mat.mtrl-sci↗

arXiv2017

Uplink Multiuser Massive MIMO Systems with Low-Resolution ADCs: A Coding-Theoretic Approach

This paper considers an uplink multiuser massive multiple-input-multiple-output (MIMO) system with low-resolution analog-to-digital converters (ADCs), in which K users with a single-antenna communicate with one base station (BS) with Nr antennas. In this system, we present a novel multiuser MIMO detection framework that is inspired by coding theory. The key idea of the proposed framework is to create a code C of length 2Nr over a spatial domain. This code is constructed by a so-called auto-encoding function that is not designable but is completely described by a channel transformation followed by a quantization function of the ADCs. From this point of view, we convert a multiuser MIMO detection problem into an equivalent channel coding problem, in which a codeword of C corresponding to users' messages is sent over 2Nr parallel channels, each with different channel reliability. To the resulting problem, we propose a novel weighted minimum distance decoding (wMDD) that appropriately exploits the unequal channel reliabilities. It is shown that the proposed wMDD yields a non-trivial gain over the conventional minimum distance decoding (MDD). From coding-theoretic viewpoint, we identify that bit-error-rate (BER) exponentially decreases with the minimum distance of the code C, which plays a similar role with a condition number in conventional MIMO systems. Furthermore, we develop the communication method that uses the wMDD for practical scenarios where the BS has no knowledge of channel state information. Finally, numerical results are provided to verify the superiority of the proposed method.

cs.IT↗

arXiv2017

Capacity-Achieving Rate-Compatible Polar Codes for General Channels

We present a rate-compatible polar coding scheme that achieves the capacity of any family of channels. Our solution generalizes the previous results [1], [2] that provide capacity-achieving rate-compatible polar codes for a degraded family of channels. The motivation for our extension comes from the fact that in many practical scenarios, e.g., MIMO systems and non-Gaussian interference, the channels cannot be ordered by degradation. The main technical contribution of this paper consists in removing the degradation condition. To do so, we exploit the ideas coming from the construction of universal polar codes. Our scheme possesses the usual attractive features of polar codes: low complexity code construction, encoding, and decoding; super-polynomial scaling of the error probability with the block length; and absence of error floors. On the negative side, the scaling of the gap to capacity with the block length is slower than in standard polar codes, and we prove an upper bound on the scaling exponent.

cs.IT↗

arXiv2016

MIMO Systems With Low-Resolution ADCs: Linear Coding Approach

This paper considers a multiple-input multiple-output (MIMO) system with low-resolution analog-to-digital converters (ADCs). In this system, the paper presents a new MIMO detection approach using coding theory. The principal idea of the proposed approach is to transform a non-linear MIMO channel to a linear MIMO channel by leveraging both a $p$-level quantizer and a lattice code where $p\geq 2$. After transforming to the linear MIMO channel with the sets of finite input and output elements, efficient MIMO detection methods are proposed to attain both diversity and multiplexing gains by using algebraic coding theory. In particular, using the proposed methods, the analytical characterizations of achievable rates are derived for different MIMO configurations. One major observation is that the proposed approach is particularly useful for a large MIMO system with the ADCs that use a few bits.

cs.IT↗

arXiv2016

Capacity-Achieving Rate-Compatible Polar Codes

We present a method of constructing rate-compatible polar codes that are capacity-achieving with low-complexity sequential decoders. The proposed code construction allows for incremental retransmissions at different rates in order to adapt to channel conditions. The main idea of the construction exploits the common characteristics of polar codes optimized for a sequence of successively degraded channels. The proposed approach allows for an optimized polar code to be used at every transmission thereby achieving capacity.

cs.IT↗

arXiv2016

Coded Compressive Sensing: A Compute-and-Recover Approach

In this paper, we propose \textit{coded compressive sensing} that recovers an $n$-dimensional integer sparse signal vector from a noisy and quantized measurement vector whose dimension $m$ is far-fewer than $n$. The core idea of coded compressive sensing is to construct a linear sensing matrix whose columns consist of lattice codes. We present a two-stage decoding method named \textit{compute-and-recover} to detect the sparse signal from the noisy and quantized measurements. In the first stage, we transform such measurements into noiseless finite-field measurements using the linearity of lattice codewords. In the second stage, syndrome decoding is applied over the finite-field to reconstruct the sparse signal vector. A sufficient condition of a perfect recovery is derived. Our theoretical result demonstrates an interplay among the quantization level $p$, the sparsity level $k$, the signal dimension $n$, and the number of measurements $m$ for the perfect recovery. Considering 1-bit compressive sensing as a special case, we show that the proposed algorithm empirically outperforms an existing greedy recovery algorithm.

cs.IT↗

arXiv2015

Wireless Multihop Device-to-Device Caching Networks

We consider a wireless device-to-device (D2D) network where $n$ nodes are uniformly distributed at random over the network area. We let each node with storage capacity $M$ cache files from a library of size $m \geq M$. Each node in the network requests a file from the library independently at random, according to a popularity distribution, and is served by other nodes having the requested file in their local cache via (possibly) multihop transmissions. Under the classical "protocol model" of wireless networks, we characterize the optimal per-node capacity scaling law for a broad class of heavy-tailed popularity distributions including Zipf distributions with exponent less than one. In the parameter regimes of interest, we show that a decentralized random caching strategy with uniform probability over the library yields the optimal per-node capacity scaling of $Θ(\sqrt{M/m})$, which is constant with $n$, thus yielding throughput scalability with the network size. Furthermore, the multihop capacity scaling can be significantly better than for the case of single-hop caching networks, for which the per-node capacity is $Θ(M/m)$. The multihop capacity scaling law can be further improved for a Zipf distribution with exponent larger than some threshold $> 1$, by using a decentralized random caching uniformly across a subset of most popular files in the library. Namely, ignoring a subset of less popular files (i.e., effectively reducing the size of the library) can significantly improve the throughput scaling while guaranteeing that all nodes will be served with high probability as $n$ increases.

cs.IT↗

arXiv2015

A Novel Cooperative Strategy for Wireless Multihop Backhaul Networks

The 5G wireless network architecture will bring dense deployments of base stations called {\em small cells} for both outdoors and indoors traffic. The feasibility of their dense deployments depends on the existence of a high data-rate transport network that can provide high-data backhaul from an aggregation node where data traffic originates and terminates, to every such small cell. Due to the limited range of radio signals in the high frequency bands, multihop wireless connection may need to be established between each access node and an aggregation node. In this paper, we present a novel transmission scheme for wireless multihop backhaul for 5G networks. The scheme consists of 1) {\em group successive relaying} that established a relay schedule to efficiently exploit half-duplex relays and 2) an optimized quantize-map-and-forward (QMF) coding scheme that improves the performance of QMF and reduces the decoding complexity and the delay. We derive an achievable rate region of the proposed scheme and attain a closed-form expression in the asymptotic case for several network models of interests. It is shown that the proposed scheme provides a significant gain over multihop routing (based on decode-and-forward), which is a solution currently proposed for wireless multihop backhaul network. Furthermore, the performance gap increases as a network becomes denser. For the proposed scheme, we then develop energy-efficient routing that determines {\em groups} of participating relays for every hop. To reflect the metric used in the routing algorithm, we refer to it as {\em interference-harnessing} routing. By turning interference into a useful signal, each relay requires a lower transmission power to achieve a desired performance compared to other routing schemes. Finally, we present a low-complexity successive decoder, which makes it feasible to use the proposed scheme in practice.

cs.IT↗

arXiv2015

On the Performance of Optimized Dense Device-to-Device Wireless Networks

We consider a D2D wireless network where $n$ users are densely deployed in a squared planar region and communicate with each other without the help of a wired infrastructure. For this network, we examine the 3-phase hierarchical cooperation (HC) scheme and the 2-phase improved HC scheme based on the concept of {\em network multiple access}. Exploiting recent results on the optimality of treating interference as noise in Gaussian interference channels, we optimize the achievable average per-link rate and not just its scaling law. In addition, we provide further improvements on both the previously proposed hierarchical cooperation schemes by a more efficient use of TDMA and spatial reuse. Thanks to our explicit achievable rate expressions, we can compare HC scheme with multihop routing (MR), where the latter can be regarded as the current practice of D2D wireless networks. Our results show that the improved and optimized HC schemes yield very significant rate gains over MR in realistic conditions of channel propagation exponents, signal to noise ratio, and number of users. This sheds light on the long-standing question about the real advantage of HC scheme over MR beyond the well-known scaling laws analysis. In contrast, we also show that our rate optimization is non-trivial, since when HC is applied with off-the-shelf choice of the system parameters, no significant rate gain with respect to MR is achieved. We also show that for large pathloss exponent the sum rate is a nearly linear function of the number of users $n$ in the range of networks of practical size. This also sheds light on a long-standing dispute on the effective achievability of linear sum rate scaling with HC. Finally, we notice that the achievable sum rate for large $α$ is much larger than for small $α$. This suggests that HC scheme may be a very effective approach for networks operating at mm-waves.

cs.IT↗

arXiv2015

On the Achievable Rates of Multihop Virtual Full-Duplex Relay Channels

We study a multihop "virtual" full-duplex relay channel as a special case of a general multiple multicast relay network. For such channel, quantize-map-and-forward (QMF) (or noisy network coding (NNC)) achieves the cut-set upper bound within a constant gap where the gap grows {\em linearly} with the number of relay stages $K$. However, this gap may not be negligible for the systems with multihop transmissions (i.e., a wireless backhaul operating at higher frequencies). We have recently attained an improved result to the capacity scaling where the gap grows {\em logarithmically} as $\log{K}$, by using an optimal quantization at relays and by exploiting relays' messages (decoded in the previous time slot) as side-information. In this paper, we further improve the performance of this network by presenting a mixed scheme where each relay can perform either decode-and-forward (DF) or QMF with possibly rate-splitting. We derive the achievable rate and show that the proposed scheme outperforms the QMF-optimized scheme. Furthermore, we demonstrate that this performance improvement increases with $K$.

cs.IT↗

arXiv2014

Structured Lattice Codes for Some Two-User Gaussian Networks with Cognition, Coordination and Two Hops

We study a number of two-user interference networks with multiple-antenna transmitters/receivers, transmitter side information in the form of linear combinations (over finite-field) of the information messages, and two-hop relaying. We start with a Cognitive Interference Channel (CIC) where one of the transmitters (non-cognitive) has knowledge of a rank-1 linear combination of the two information messages, while the other transmitter (cognitive) has access to a rank-2 linear combination of the same messages. This is referred to as the Network-Coded CIC, since such linear combination may be the result of some random linear network coding scheme implemented in the backbone wired network. For such channel we develop an achievable region based on a few novel concepts: Precoded Compute and Forward (PCoF) with Channel Integer Alignment (CIA), combined with standard Dirty-Paper Coding. We also develop a capacity region outer bound and find the sum symmetric GDoF of the Network-Coded CIC. Through the GDoF characterization, we show that knowing "mixed data" (linear combinations of the information messages) provides an unbounded spectral efficiency gain over the classical CIC counterpart, if the ratio of SNR to INR is larger than certain threshold. Then, we consider a Gaussian relay network having the two-user MIMO IC as the main building block. We use PCoF with CIA to convert the MIMO IC into a deterministic finite-field IC. Then, we use a linear precoding scheme over the finite-field to eliminate interference in the finite-field domain. Using this unified approach, we characterize the symmetric sum rate of the two-user MIMO IC with coordination, cognition, and two-hops. We also provide finite-SNR results which show that the proposed coding schemes are competitive against state of the art interference avoidance based on orthogonal access, for Rayleigh fading channels.

cs.IT↗

arXiv2014

Demystifying the Scaling Laws of Dense Wireless Networks: No Linear Scaling in Practice

We optimize the hierarchical cooperation protocol of Ozgur, Leveque and Tse, which is supposed to yield almost linear scaling of the capacity of a dense wireless network with the number of users $n$. Exploiting recent results on the optimality of "treating interference as noise" in Gaussian interference channels, we are able to optimize the achievable average per-link rate and not just its scaling law. Our optimized hierarchical cooperation protocol significantly outperforms the originally proposed scheme. On the negative side, we show that even for very large $n$, the rate scaling is far from linear, and the optimal number of stages $t$ is less than 4, instead of $t \rightarrow \infty$ as required for almost linear scaling. Combining our results and the fact that, beyond a certain user density, the network capacity is fundamentally limited by Maxwell laws, as shown by Francheschetti, Migliore and Minero, we argue that there is indeed no intermediate regime of linear scaling for dense networks in practice.

cs.IT↗

arXiv2013

Full-Duplex Relaying with Half-Duplex Relays

We consider "virtual" full-duplex relaying by means of half-duplex relays. In this configuration, each relay stage in a multi-hop relaying network is formed by at least two relays, used alternatively in transmit and receive modes, such that while one relay transmits its signal to the next stage, the other relay receives a signal from the previous stage. With such a pipelined scheme, the source is active and sends a new information message in each time slot. We consider the achievable rates for different coding schemes and compare them with a cut-set upper bound, which is tight in certain conditions. In particular, we show that both lattice-based Compute and Forward (CoF) and Quantize reMap and Forward (QMF) yield attractive performance and can be easily implemented. In particular, QMF in this context does not require "long" messages and joint (non-unique) decoding, if the quantization mean-square distortion at the relays is chosen appropriately. Also, in the multi-hop case the gap of QMF from the cut-set upper bound grows logarithmically with the number of stages, and not linearly as in the case of "noise level" quantization. Furthermore, we show that CoF is particularly attractive in the case of multi-hop relaying, when the channel gains have fluctuations not larger than 3dB, yielding a rate that does not depend on the number of relaying stages. In particular, we argue that such architecture may be useful for a wireless backhaul with line-of-sight propagation between the relays.

cs.IT↗

arXiv2013

On Interference Networks over Finite Fields

We present a framework to study linear deterministic interference networks over finite fields. Unlike the popular linear deterministic models introduced to study Gaussian networks, we consider networks where the channel coefficients are general scalars over some extension field $\FF_{p^m}$ (scalar $m$-th extension-field models), $m \times m$ diagonal matrices over $\FF_p$ ($m$-symbol extension ground-field models), and $m \times m$ general non-singular matrices (MIMO ground field models). We use the companion matrix representation of the extension field to convert $m$-th extension scalar models into MIMO ground-field models where the channel matrices have special algebraic structure. For such models, we consider the $2 \times 2 \times 2$ topology (two-hops two-flow) and the 3-user interference network topology. We derive achievability results and feasibility conditions for certain schemes based on the Precoding-Based Network Alignment (PBNA) approach, where intermediate nodes use random linear network coding (i.e., propagate random linear combinations of their incoming messages) and non-trivial precoding/decoding is performed only at the network edges, at the sources and destinations. Furthermore, we apply this approach to the scalar $2\times 2\times 2$ complex Gaussian IC with fixed channel coefficients, and show two competitive schemes outperforming other known approaches at any SNR, where we combine finite-field linear precoding/decoding with lattice coding and the Compute and Forward approach at the signal level. As a side result, we also show significant advantages of vector linear network coding both in terms of feasibility probability (with random coding coefficients) and in terms of coding latency, with respect to standard scalar linear network coding, in PBNA schemes.

cs.IT↗

arXiv2013

Two-Unicast Two-Hop Interference Network: Finite-Field Model

In this paper we present a novel framework to convert the $K$-user multiple access channel (MAC) over $\FF_{p^m}$ into the $K$-user MAC over ground field $\FF_{p}$ with $m$ multiple inputs/outputs (MIMO). This framework makes it possible to develop coding schemes for MIMO channel as done in symbol extension for time-varying channel. Using aligned network diagonalization based on this framework, we show that the sum-rate of $(2m-1)\log{p}$ is achievable for a $2\times 2\times 2$ interference channel over $\FF_{p^m}$. We also provide some relation between field extension and symbol extension.

cs.IT↗

arXiv2013

Compute-and-Forward Strategies for Cooperative Distributed Antenna Systems

We study a distributed antenna system where $L$ antenna terminals (ATs) are connected to a Central Processor (CP) via digital error-free links of finite capacity $R_0$, and serve $K$ user terminals (UTs). We contribute to the subject in the following ways: 1) for the uplink, we apply the "Compute and Forward" (CoF) approach and examine the corresponding system optimization at finite SNR; 2) For the downlink, we propose a novel precoding scheme nicknamed "Reverse Compute and Forward" (RCoF); 3) In both cases, we present low-complexity versions of CoF and RCoF based on standard scalar quantization at the receivers, that lead to discrete-input discrete-output symmetric memoryless channel models for which near-optimal performance can be achieved by standard single-user linear coding; 4) For the case of large $R_0$, we propose a novel "Integer Forcing Beamforming" (IFB) scheme that generalizes the popular zero-forcing beamforming and achieves sum rate performance close to the optimal Gaussian Dirty-Paper Coding. The proposed uplink and downlink system optimization focuses specifically on the ATs and UTs selection problem. We present low-complexity ATs and UTs selection schemes and demonstrate, through Monte Carlo simulation in a realistic environment with fading and shadowing, that the proposed schemes essentially eliminate the problem of rank deficiency of the system matrix and greatly mitigate the non-integer penalty affecting CoF/RCoF at high SNR. Comparison with other state-of-the art information theoretic schemes, such as "Quantize reMap and Forward" for the uplink and "Compressed Dirty Paper Coding" for the downlink, show competitive performance of the proposed approaches with significantly lower complexity.

cs.IT↗