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Won-Yong Shin

Publications and source records attributed to Won-Yong Shin.

At least 73 records · Page 4Linked to original sources

On the Effects of Subpacketization in Content-Centric Mobile Networks

A large-scale content-centric mobile ad hoc network employing subpacketization is studied in which each mobile node having finite-size cache moves according to the reshuffling mobility model and requests a content object from the library independently at random according to the Zipf popularity distribution. Instead of assuming that one content object is transferred in a single time slot, we consider a more challenging scenario where the size of each content object is considerably large and thus only a subpacket of a file can be delivered during one time slot, which is motivated by a fast mobility scenario. Under our mobility model, we consider a single-hop-based content delivery and characterize the fundamental trade-offs between throughput and delay. The order-optimal throughput-delay trade-off is analyzed by presenting the following two content reception strategies: the sequential reception for uncoded caching and the random reception for maximum distance separable (MDS)-coded caching. We also perform numerical evaluation to validate our analytical results. In particular, we conduct performance comparisons between the uncoded caching and the MDS-coded caching strategies by identifying the regimes in which the performance difference between the two caching strategies becomes prominent with respect to system parameters such as the Zipf exponent and the number of subpackets. In addition, we extend our study to the random walk mobility scenario and show that our main results are essentially the same as those in the reshuffling mobility model.

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Wireless Power Transfer for Distributed Estimation in Sensor Networks

This paper studies power allocation for distributed estimation of an unknown scalar random source in sensor networks with a multiple-antenna fusion center (FC), where wireless sensors are equipped with radio-frequency based energy harvesting technology. The sensors' observation is locally processed by using an uncoded amplify-and-forward scheme. The processed signals are then sent to the FC, and are coherently combined at the FC, at which the best linear unbiased estimator (BLUE) is adopted for reliable estimation. We aim to solve the following two power allocation problems: 1) minimizing distortion under various power constraints; and 2) minimizing total transmit power under distortion constraints, where the distortion is measured in terms of mean-squared error of the BLUE. Two iterative algorithms are developed to solve the non-convex problems, which converge at least to a local optimum. In particular, the above algorithms are designed to jointly optimize the amplification coefficients, energy beamforming, and receive filtering. For each problem, a suboptimal design, a single-antenna FC scenario, and a common harvester deployment for colocated sensors, are also studied. Using the powerful semidefinite relaxation framework, our result is shown to be valid for any number of sensors, each with different noise power, and for an arbitrarily number of antennas at the FC.

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Opportunistic Downlink Interference Alignment for Multi-Cell MIMO Networks

In this paper, we propose an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs) but also eliminates intra-cell interference among spatial streams in the same cell. We show that the minimum number of users required to achieve a target degrees-of-freedom (DoF) can be fundamentally reduced, i.e., the fundamental user scaling law can be improved by using the ODIA, compared with the existing downlink IA schemes. In addition, we adopt a limited feedback strategy in the ODIA framework, and then analyze the number of feedback bits required for the system with limited feedback to achieve the same user scaling law of the ODIA as the system with perfect CSI. We also modify the original ODIA in order to further improve sum-rate, which achieves the optimal multiuser diversity gain, i.e., $\log\log N$, per spatial stream even in the presence of downlink inter-cell interference, where $N$ denotes the number of users in a cell. Simulation results show that the ODIA significantly outperforms existing interference management techniques in terms of sum-rate in realistic cellular environments. Note that the ODIA operates in a non-collaborative and decoupled manner, i.e., it requires no information exchange among BSs and no iterative beamformer optimization between BSs and users, thus leading to an easier implementation.

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Opportunistic Network Decoupling With Virtual Full-Duplex Operation in Multi-Source Interfering Relay Networks

We introduce a new achievability scheme, termed opportunistic network decoupling (OND), operating in virtual full-duplex mode. In the scheme, a novel relay scheduling strategy is utilized in the $K\times N\times K$ channel with interfering relays, consisting of $K$ source--destination pairs and $N$ half-duplex relays in-between them. A subset of relays using alternate relaying is opportunistically selected in terms of producing the minimum total interference level, thereby resulting in network decoupling. As our main result, it is shown that under a certain relay scaling condition, the OND protocol achieves $K$ degrees of freedom even in the presence of interfering links among relays. Numerical evaluation is also shown to validate the performance of the proposed OND. Our protocol basically operates in a fully distributed fashion along with local channel state information, thereby resulting in a relatively easy implementation.

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Capacity of Three-Dimensional Erasure Networks

In this paper, we introduce a large-scale three-dimensional (3D) erasure network, where $n$ wireless nodes are randomly distributed in a cuboid of $n^λ\times n^μ\times n^ν$ with $λ+μ+ν=1$ for $λ,μ,ν>0$, and completely characterize its capacity scaling laws. Two fundamental path-loss attenuation models (i.e., exponential and polynomial power-law models) are used to suitably model an erasure probability for packet transmission. Then, under the two erasure models, we introduce a routing protocol using percolation highway in 3D space, and then analyze its achievable throughput scaling laws. It is shown that, under the two erasure models, the aggregate throughput scaling $n^{\min\{1-λ,1-μ,1-ν\}}$ can be achieved in the 3D erasure network. This implies that the aggregate throughput scaling $n^{2/3}$ can be achieved in 3D cubic erasure networks while $\sqrt{n}$ can be achieved in two-dimensional (2D) square erasure networks. The gain comes from the fact that, compared to 2D space, more geographic diversity can be exploited via 3D space, which means that generating more simultaneous percolation highways is possible. In addition, cut-set upper bounds on the capacity scaling are derived to verify that the achievable scheme based on the 3D percolation highway is order-optimal within a polylogarithmic factor under certain practical operating regimes on the decay parameters.

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On the Degrees-of-Freedom of the Large-Scale Interfering Two-Way Relay Network

Achievable degrees-of-freedom (DoF) of the large-scale interfering two-way relay network is investigated. The network consists of $K$ pairs of communication nodes (CNs) and $N$ relay nodes (RNs). It is assumed that $K\ll N$ and each pair of CNs communicates with each other through one of the $N$ relay nodes without a direct link between them. Interference among RNs is also considered. Assuming local channel state information (CSI) at each RN, a distributed and opportunistic RN selection technique is proposed for the following three promising relaying protocols: amplify--forward, decode--forward, and compute--forward. As a main result, the asymptotically achievable DoF is characterized as $N$ increases for the three relaying protocols. In particular, a sufficient condition on $N$ required to achieve the certain DoF of the network is analyzed. Through extensive simulations, it is shown that the proposed RN selection techniques outperform conventional schemes in terms of achievable rate even in practical communication scenarios. Note that the proposed technique operates with a distributed manner and requires only local CSI, leading to easy implementation for practical wireless systems.

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Group Communication Over LTE : A Radio Access Perspective

Long Term Evolution (LTE), which has its root on commercial mobile communications, recently becomes an influential solution to future public safety communications. To verify the feasibility of LTE for public safety, it is essential to investigate whether an LTE system optimized for one-to-one communications is capable of providing group communication, which is one of the most important service concepts in public safety. In general, a number of first responders for public safety need to form a group for communicating with each other or sharing the common data for collaboration on their mission. In this article, we analyze how the current LTE system can support group communication in a radio access aspect. Based on the requirements for group communication, we validate whether each LTE-enabled radio access method can efficiently support group communication. In addition, we propose a new multicast transmission scheme, termed index-coded Hybrid Automatic Retransmission reQuest (HARQ). By applying the index coding concept to HARQ operations, we show that the LTE system can provide group communication more sophisticatedly in terms of radio resource efficiency and scalability. We finally evaluate the performance of LTE-enabled group communication using several radio access methods and show how the proposed transmission scheme brings the performance enhancement via system level simulations.

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GreenInfra: Capacity of Large-Scale Hybrid Networks With Cost-Effective Infrastructure

The cost-effective impact and fundamental limits of infrastructure support with rate-limited wired backhaul links (i.e., GreenInfra support), directly connecting base stations (BSs), are analyzed in a large-scale hybrid network of unit node density, where multi-antenna BSs are deployed. We consider a general scenario such that the rate of each BS-to-BS link scales at an arbitrary rate relative to the number of randomly located wireless nodes, $n$. For the operating regimes with respect to the number of BSs and the number of antennas at each BS, we first analyze the minimum rate of each backhaul link, $C_{\textrm{BS}}$, required to guarantee the same throughput scaling as in the infinite-capacity backhaul link case. We then identify the operating regimes in which the required rate $C_{\textrm{BS}}$ scales slower than $n^ε$ for an arbitrarily small $ε>0$ (i.e., the regimes where $C_{\textrm{BS}}$ does not need to be infinitely large). We also show the case where our network with GreenInfra is fundamentally in the infrastructure-limited regime, in which the performance is limited by the rate of backhaul links. In addition, we derive a generalized throughput scaling law including the case where the rate of each backhaul link scales slower than $C_{\textrm{BS}}$. To validate the throughput scaling law for finite values of system parameters, numerical evaluation is also shown via computer simulations.

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Clarifying the Role of Distance in Friendships on Twitter: Discovery of a Double Power-Law Relationship

This study analyzes friendships in online social networks involving geographic distance with a geo-referenced Twitter dataset, which provides the exact distance between corresponding users. We start by introducing a strong definition of "friend" on Twitter, requiring bidirectional communication. Next, by utilizing geo-tagged mentions delivered by users to determine their locations, we introduce a two-stage distance estimation algorithm. As our main contribution, our study provides the following newly-discovered friendship degree related to the issue of space: The number of friends according to distance follows a double power-law (i.e., a double Pareto law) distribution, indicating that the probability of befriending a particular Twitter user is significantly reduced beyond a certain geographic distance between users, termed the separation point. Our analysis provides much more fine-grained social ties in space, compared to the conventional results showing a homogeneous power-law with distance.

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A New Understanding of Friendships in Space: Complex Networks Meet Twitter

Studies on friendships in online social networks involving geographic distance have so far relied on the city location provided in users' profiles. Consequently, most of the research on friendships have provided accuracy at the city level, at best, to designate a user's location. This study analyzes a Twitter dataset because it provides the exact geographic distance between corresponding users. We start by introducing a strong definition of "friend" on Twitter (i.e., a definition of bidirectional friendship), requiring bidirectional communication. Next, we utilize geo-tagged mentions delivered by users to determine their locations, where "@username" is contained anywhere in the body of tweets. To provide analysis results, we first introduce a friend counting algorithm. From the fact that Twitter users are likely to post consecutive tweets in the static mode, we also introduce a two-stage distance estimation algorithm. As the first of our main contributions, we verify that the number of friends of a particular Twitter user follows a well-known power-law distribution (i.e., a Zipf's distribution or a Pareto distribution). Our study also provides the following newly-discovered friendship degree related to the issue of space: The number of friends according to distance follows a double power-law (i.e., a double Pareto law) distribution, indicating that the probability of befriending a particular Twitter user is significantly reduced beyond a certain geographic distance between users, termed the separation point. Our analysis provides concrete evidence that Twitter can be a useful platform for assigning a more accurate scalar value to the degree of friendship between two users.

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Elastic Routing in Wireless Ad Hoc Networks With Directional Antennas

Throughput scaling laws of an ad hoc network equipping directional antennas at each node are analyzed. More specifically, this paper considers a general framework in which the beam width of each node can scale at an arbitrary rate relative to the number of nodes. We introduce an elastic routing protocol, which enables to increase per-hop distance elastically according to the beam width, while maintaining an average signal-to-interference-and-noise ratio at each receiver as a constant. We then identify fundamental operating regimes characterized according to the beam width scaling and analyze throughput scaling laws for each of the regimes. The elastic routing is shown to achieve a much better throughput scaling law than that of the conventional nearest-neighbor multihop for all operating regimes. The gain comes from the fact that more source--destination pairs can be simultaneously activated as the beam width becomes narrower, which eventually leads to a linear throughput scaling law. In addition, our framework is applied to a hybrid network consisting of both wireless ad hoc nodes and infrastructure nodes. As a result, in the hybrid network, we analyze a further improved throughput scaling law and identify the operating regime where the use of directional antennas is beneficial.

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Ad Hoc Networking With Cost-Effective Infrastructure: Generalized Capacity Scaling

Capacity scaling of a large hybrid network with unit node density, consisting of $n$ wireless ad hoc nodes, base stations (BSs) equipped with multiple antennas, and one remote central processor (RCP), is analyzed when wired backhaul links between the BSs and the RCP are rate-limited. We deal with a general scenario where the number of BSs, the number of antennas at each BS, and the backhaul link rate can scale at arbitrary rates relative to $n$ (i.e., we introduce three scaling parameters). We first derive the minimum backhaul link rate required to achieve the same capacity scaling law as in the infinite-capacity backhaul link case. Assuming an arbitrary rate scaling of each backhaul link, a generalized achievable throughput scaling law is then analyzed in the network based on using one of pure multihop, hierarchical cooperation, and two infrastructure-supported routing protocols, and moreover, three-dimensional information-theoretic operating regimes are explicitly identified according to the three scaling parameters. In particular, we show the case where our network having a power limitation is also fundamentally in the degrees-of-freedom- or infrastructure-limited regime, or both. In addition, a generalized cut-set upper bound under the network model is derived by cutting not only the wireless connections but also the wired connections. It is shown that our upper bound matches the achievable throughput scaling even under realistic network conditions such that each backhaul link rate scales slower than the aforementioned minimum-required backhaul link rate.

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Opportunistic Downlink Interference Alignment

In this paper, we propose an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs) but also eliminates intra-cell interference among spatial streams in the same cell. We show that the minimum number of users required to achieve a target degrees-of-freedom (DoF) can be fundamentally reduced, i.e., the fundamental user scaling law can be improved by using the ODIA, compared with the existing downlink IA schemes. In addition, we adopt a limited feedback strategy in the ODIA framework, and then analyze the required number of feedback bits leading to the same performance as that of the ODIA assuming perfect feedback. We also modify the original ODIA in order to further improve sum-rate, which achieves the optimal multiuser diversity gain, i.e., $\log \log N$, per spatial stream even in the presence of downlink inter-cell interference, where $N$ denotes the number of users in a cell. Simulation results show that the ODIA significantly outperforms existing interference management techniques in terms of sum-rate in realistic cellular environments. Note that the ODIA operates in a distributed and decoupled manner, while requiring no information exchange among BSs and no iterative beamformer optimization between BSs and users, thus leading to an easier implementation.

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Codebook-Based Opportunistic Interference Alignment

Opportunistic interference alignment (OIA) asymptotically achieves the optimal degrees-of-freedom (DoF) in interfering multiple-access channels (IMACs) in a distributed fashion, as a certain user scaling condition is satisfied. For the multiple-input multiple-output IMAC, it was shown that the singular value decomposition (SVD)-based beamforming at the users fundamentally reduces the user scaling condition required to achieve any target DoF compared to that for the single-inputmultiple-output IMAC. In this paper, we tackle two practical challenges of the existing SVD-based OIA: 1) the need of full feedforward of the selected users' beamforming weight vectors and 2) a low rate achieved based on the exiting zero-forcing (ZF) receiver. We first propose a codebook-based OIA, in which the weight vectors are chosen from a pre-defined codebook with a finite size so that information of the weight vectors can be sent to the belonging BS with limited feedforward. We derive the codebook size required to achieve the same user scaling condition as the SVD-based OIA case for both Grassmannian and random codebooks. Surprisingly, it is shown that the derived codebook size is the same for the two considered codebook approaches. Second, we take into account an enhanced receiver at the base stations (BSs) in pursuit of improving the achievable rate based on the ZF receiver. Assuming no collaboration between the BSs, the interfering links between a BS and the selected users in neighboring cells are difficult to be acquired at the belonging BS. We propose the use of a simple minimum Euclidean distance receiver operating with no information of the interfering links. With the help of the OIA, we show that this new receiver asymptotically achieves the channel capacity as the number of users increases.

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Opportunistic Interference Alignment for MIMO Interfering Multiple-Access Channels

We consider the $K$-cell multiple-input multiple-output (MIMO) interfering multiple-access channel (IMAC) with time-invariant channel coefficients, where each cell consists of a base station (BS) with $M$ antennas and $N$ users having $L$ antennas each. In this paper, we propose two opportunistic interference alignment (OIA) techniques utilizing multiple transmit antennas at each user: antenna selection-based OIA and singular value decomposition (SVD)-based OIA. Their performance is analyzed in terms of \textit{user scaling law} required to achieve $KS$ degrees-of-freedom (DoF), where $S(\le M)$ denotes the number of simultaneously transmitting users per cell. We assume that each selected user transmits a single data stream at each time-slot. It is shown that the antenna selection-based OIA does not fundamentally change the user scaling condition if $L$ is fixed, compared with the single-input multiple-output (SIMO) IMAC case, which is given by $\text{SNR}^{(K 1)S}$, where SNR denotes the signal-to-noise ratio. In addition, we show that the SVD-based OIA can greatly reduce the user scaling condition to $\text{SNR}^{(K-1)S-L+1}$ through optimizing a weight vector at each user. Simulation results validate the derived scaling laws of the proposed OIA techniques. The sum-rate performance of the proposed OIA techniques is compared with the conventional techniques in MIMO IMAC channels and it is shown that the proposed OIA techniques outperform the conventional techniques.

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Can One Achieve Multiuser Diversity in Uplink Multi-Cell Networks?

We introduce a distributed opportunistic scheduling (DOS) strategy, based on two pre-determined thresholds, for uplink $K$-cell networks with time-invariant channel coefficients. Each base station (BS) opportunistically selects a mobile station (MS) who has a large signal strength of the desired channel link among a set of MSs generating a sufficiently small interference to other BSs. Then, performance on the achievable throughput scaling law is analyzed. As our main result, it is shown that the achievable sum-rate scales as $K\log(\text{SNR}\log N)$ in a high signal-to-noise ratio (SNR) regime, if the total number of users in a cell, $N$, scales faster than $\text{SNR}^{\frac{K-1}{1-ε}}$ for a constant $ε\in(0,1)$. This result indicates that the proposed scheme achieves the multiuser diversity gain as well as the degrees-of-freedom gain even under multi-cell environments. Simulation results show that the DOS provides a better sum-rate throughput over conventional schemes.

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Parallel Opportunistic Routing in Wireless Networks

We study benefits of opportunistic routing in a large wireless ad hoc network by examining how the power, delay, and total throughput scale as the number of source- destination pairs increases up to the operating maximum. Our opportunistic routing is novel in a sense that it is massively parallel, i.e., it is performed by many nodes simultaneously to maximize the opportunistic gain while controlling the inter-user interference. The scaling behavior of conventional multi-hop transmission that does not employ opportunistic routing is also examined for comparison. Our results indicate that our opportunistic routing can exhibit a net improvement in overall power--delay trade-off over the conventional routing by providing up to a logarithmic boost in the scaling law. Such a gain is possible since the receivers can tolerate more interference due to the increased received signal power provided by the multi-user diversity gain, which means that having more simultaneous transmissions is possible.

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Opportunistic Interference Mitigation Achieves Optimal Degrees-of-Freedom in Wireless Multi-cell Uplink Networks

We introduce an opportunistic interference mitigation (OIM) protocol, where a user scheduling strategy is utilized in $K$-cell uplink networks with time-invariant channel coefficients and base stations (BSs) having $M$ antennas. Each BS opportunistically selects a set of users who generate the minimum interference to the other BSs. Two OIM protocols are shown according to the number $S$ of simultaneously transmitting users per cell: opportunistic interference nulling (OIN) and opportunistic interference alignment (OIA). Then, their performance is analyzed in terms of degrees-of-freedom (DoFs). As our main result, it is shown that $KM$ DoFs are achievable under the OIN protocol with $M$ selected users per cell, if the total number $N$ of users in a cell scales at least as $\text{SNR}^{(K-1)M}$. Similarly, it turns out that the OIA scheme with $S$($<M$) selected users achieves $KS$ DoFs, if $N$ scales faster than $\text{SNR}^{(K-1)S}$. These results indicate that there exists a trade-off between the achievable DoFs and the minimum required $N$. By deriving the corresponding upper bound on the DoFs, it is shown that the OIN scheme is DoF optimal. Finally, numerical evaluation, a two-step scheduling method, and the extension to multi-carrier scenarios are shown.

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