arXiv subjects

Sae-Young Chung

Publications and source records attributed to Sae-Young Chung.

43 records · Page 3Linked to original sources

arXiv2009

Deterministic Relay Networks with State Information

Motivated by fading channels and erasure channels, the problem of reliable communication over deterministic relay networks is studied, in which relay nodes receive a function of the incoming signals and a random network state. An achievable rate is characterized for the case in which destination nodes have full knowledge of the state information. If the relay nodes receive a linear function of the incoming signals and the state in a finite field, then the achievable rate is shown to be optimal, meeting the cut-set upper bound on the capacity. This result generalizes on a unified framework the work of Avestimehr, Diggavi, and Tse on the deterministic networks with state dependency, the work of Dana, Gowaikar, Palanki, Hassibi, and Effros on linear erasure networks with interference, and the work of Smith and Vishwanath on linear erasure networks with broadcast.

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arXiv2009

On the Separability of Parallel Gaussian Interference Channels

The separability in parallel Gaussian interference channels (PGICs) is studied in this paper. We generalize the separability results in one-sided PGICs (OPGICs) by Sung \emph{et al.} to two-sided PGICs (TPGICs). Specifically, for strong and mixed TPGICs, we show necessary and sufficient conditions for the separability. For this, we show diagonal covariance matrices are sum-rate optimal for strong and mixed TPGICs.

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arXiv2009

Sum capacity of multi-source linear finite-field relay networks with fading

We study a fading linear finite-field relay network having multiple source-destination pairs. Because of the interference created by different unicast sessions, the problem of finding its capacity region is in general difficult. We observe that, since channels are time-varying, relays can deliver their received signals by waiting for appropriate channel realizations such that the destinations can decode their messages without interference. We propose a block Markov encoding and relaying scheme that exploits such channel variations. By deriving a general cut-set upper bound and an achievable rate region, we characterize the sum capacity for some classes of channel distributions and network topologies. For example, when the channels are uniformly distributed, the sum capacity is given by the minimum average rank of the channel matrices constructed by all cuts that separate the entire sources and destinations. We also describe other cases where the capacity is characterized.

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arXiv2009

Capacity of the Gaussian Two-way Relay Channel to within 1/2 Bit

In this paper, a Gaussian two-way relay channel, where two source nodes exchange messages with each other through a relay, is considered. We assume that all nodes operate in full-duplex mode and there is no direct channel between the source nodes. We propose an achievable scheme composed of nested lattice codes for the uplink and structured binning for the downlink. We show that the scheme achieves within 1/2 bit from the cut-set bound for all channel parameters and becomes asymptotically optimal as the signal to noise ratios increase.

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arXiv2009

Nested Lattice Codes for Gaussian Relay Networks with Interference

In this paper, a class of relay networks is considered. We assume that, at a node, outgoing channels to its neighbors are orthogonal, while incoming signals from neighbors can interfere with each other. We are interested in the multicast capacity of these networks. As a subclass, we first focus on Gaussian relay networks with interference and find an achievable rate using a lattice coding scheme. It is shown that there is a constant gap between our achievable rate and the information theoretic cut-set bound. This is similar to the recent result by Avestimehr, Diggavi, and Tse, who showed such an approximate characterization of the capacity of general Gaussian relay networks. However, our achievability uses a structured code instead of a random one. Using the same idea used in the Gaussian case, we also consider linear finite-field symmetric networks with interference and characterize the capacity using a linear coding scheme.

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arXiv2009

Capacity Scaling of Single-source Wireless Networks: Effect of Multiple Antennas

We consider a wireless network in which a single source node located at the center of a unit area having $m$ antennas transmits messages to $n$ randomly located destination nodes in the same area having a single antenna each. To achieve the sum-rate proportional to $m$ by transmit beamforming, channel state information (CSI) is essentially required at the transmitter (CSIT), which is hard to obtain in practice because of the time-varying nature of the channels and feedback overhead. We show that, even without CSIT, the achievable sum-rate scales as $Θ(m\log m)$ if a cooperation between receivers is allowed. By deriving the cut-set upper bound, we also show that $Θ(m\log m)$ scaling is optimal. Specifically, for $n=ω(m^2)$, the simple TDMA-based quantize-and-forward is enough to achieve the capacity scaling. For $n=ω(m)$ and $n=\operatorname{O}(m^2)$, on the other hand, we apply the hierarchical cooperation to achieve the capacity scaling.

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arXiv2008

On the Multiplexing Gain of K-user Partially Connected Interference Channel

The multiplexing gain (MUXG) of $K$-user interference channel (IC) with partially connected interfering links is analyzed. The motivation for the partially connected IC comes from the fact that not all interferences are equally strong in practice. The MUXG is characterized as a function of the number ($K$) of users and the number ($N \geq 1$) of interfering links. Our analysis is mainly based on the interference alignment (IA) technique to mitigate interference. Our main results are as follows: One may expect that higher MUXG can be attained when some of interfering links do not exist. However, when $N$ is odd and $K=N+2$, the MUXG is not increased beyond the optimal MUXG of fully connected IC, which is $\frac{KM}{2}$. The number of interfering links has no influence on the achievable MUXG using IA, but affects the efficiency in terms of the number of required channel realizations: When N=1 or 2, the optimal MUXG of the fully connected IC is achievable with a finite number of channel realizations. In case of $N \geq 3$, however, the MUXG of $\frac{KM}{2}$ can be achieved asymptotically as the number of channel realizations tends to infinity.

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