Song‐Nam Hong
Hanyang University · Computer Science
About the Lab
Professor Song-Nam Hong's research lab specializes in advanced wireless communication systems, with a focus on signal processing, network information theory, and efficient digital transmission in constrained environments. Key research directions include distributed antenna systems, massive MIMO with low-resolution ADCs, compute-and-forward relaying, and capacity-achieving channel coding techniques such as polar codes. The lab also explores decentralized machine learning for networked systems, particularly in online and federated learning frameworks with provable performance guarantees. These efforts are driven by practical implementation challenges such as finite fronthaul capacity, hardware quantization, and energy efficiency.
Research Overview
Research Output Trend
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Selected Papers
15We 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 R0, and serve K user terminals (UTs). This model has been widely investigated both for the uplink (UTs to CP) and for the downlink (CP to UTs), which are instances of the general multiple-access relay and broadcast relay networks. We contribute to the subject in the following ways: 1) For the uplink, we consider the recently proposed “com
This paper considers an uplink multiuser multiple-input-multiple-output (MIMO) system with low-resolution analog-to-digital converters (ADCs), in which K users equipped with a single-antenna communicate with one base station (BS) with N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> antennas. In this system, we present a novel multiuser MIMO detection framework inspired by coding theory. The key idea of the proposed framework is to create a
We consider virtual full-duplex relaying by means of half-duplex relays. In this configuration, each relay stage in a multihop 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 vari
A method of constructing rate-compatible polar codes that are capacity achieving at multiple code rates with low-complexity sequential decoders is presented. The underlying idea of the construction exploits certain common characteristics of polar codes that are optimized for a sequence of successively degraded channels. The proposed code consists of parallel concatenation of multiple polar codes with information-bit divider at the input of each polar encoder. Thus, it is referred to as parallel
We consider the problem of learning a nonlinear function over a network of learners in a fully decentralized fashion. Online learning is additionally assumed, where every learner receives continuous streaming data locally. This learning model is called a fully distributed online learning (or a fully decentralized online federated learning). For this model, we propose a novel learning framework with multiple kernels, which is named DOMKL. The proposed DOMKL is devised by harnessing the principles
We consider 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 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> , and serve K user terminals (UTs). This system model has been widely investigated both for the uplink and the downlink, which are instances of the general multiple-access relay and broadcast relay networks. In this work we focus on
We consider an uplink multiuser multiple-input multiple-output (MU-MIMO) system with one-bit analog-to-digital converters (ADCs). In this system, numerous symbol detectors, such as maximum-likelihood, zero-forcing, and supervised-learning-based detectors, have been proposed by using one-bit quantized channel outputs. The limitation of these hard-decision detectors cannot generate soft outputs from one-bit quantized channel observations, which considerably degrades the performance of a following
Online federated learning (OFL) is a promising framework to learn a sequence of global functions from distributed sequential data at local devices. In this framework, we first introduce a single kernel-based OFL (termed S-KOFL) by incorporating random-feature (RF) approximation, online gradient descent (OGD), and federated averaging (FedAvg). As manifested in the centralized counterpart, an extension to multi-kernel method is necessary. Harnessing the extension principle in the centralized metho
We consider a low-complexity version of the Compute and Forward scheme that involves only scaling, offset (dithering removal) and scalar quantization at the relays. The proposed scheme is suited for the uplink of a distributed antenna system where the antenna elements must be very simple and are connected to a joint processor via orthogonal perfect links of given rate R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> . We consider the design
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 held F(p <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> ) (scalar mth extension held models), m x m diagonal matrices over F <sub xmlns:mml="http://www.w3.org/1998/Math/Ma
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 certain common characteristics of polar codes that are optimized for a sequence of degraded channels. The proposed approach allows for an optimized polar code to be used at every transmission th
Online multiple kernel learning (OMKL) has provided an attractive performance in nonlinear function learning tasks. Leveraging a random feature (RF) approximation, the major drawback of OMKL, known as the curse of dimensionality, has been recently alleviated. These advantages enable RF-based OMKL to be considered in practice. In this article, we introduce a new research problem, named stream-based active MKL (AMKL), in which a learner is allowed to label some selected data from an oracle accordi
The reaction of Co deposited at 350 °C on epitaxial CoSi2 is investigated by means of low-energy electron diffraction, core-level and angle-resolved valence-band photoemission, and ion scattering spectroscopy. Co is deposited onto ∼100-Å-thick CoSi2(111) films epitaxially grown on Si(111) which exhibit a Si-rich surface. For one Co monolayer equivalent, the Si-rich surface labeled CoSi2(111)–Si is converted into a bulklike terminated one, labeled CoSi2(111). The latter is characterized by a spec
Research Areas
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