황강욱 교수

As a promising solution for handling super dense wireless networks, wireless local area networks (WLANs) have been intensively considered due to their wide availability. However, the contention-based MAC protocol in WLANs should be modified because of its inefficiency. To this end, we consider a recently proposed novel MAC protocol called the renewal access protocol (RAP). With the RAP, we analyze two strategies for resolving collisions efficiently and achieving optimal throughput performance in

We propose a distance-based inter-cell interference coordination (ICIC) scheme in small cell networks (SCNs). While most of the previous works focus on a randomly selected user called a typical user, we focus on an edge user because the main purpose of ICIC is to improve the performance of an edge user. Since there are many inactive small cell base stations (SBSs) in SCNs, a simple criterion for an edge user such as being located near a cell boundary is not appropriate for SCNs. To accurately de

OFDMA is the basis of future broadband access, due to its many inherent advantages such as scalability and fine granularity for multi-user access. OFDMA-Aloha combines the flexibility of OFDMA with basic Aloha's collision resolution mechanism over sub-carriers, in an attempt to reduce packet collisions and achieve faster retransmission. However, this comes at the expense of a larger slot size, due to lower channel rates per subcarrier. The above gives rise to a fundamental question: whether to u

We consider a simple MAC protocol, called the renewal access protocol (RAP), that adopts all of the legacy 802.11 standard but the backoff stage feature. To meet two objectives in the design of the RAP—optimal throughput and high short-term fairness—we develop a mathematical model of the RAP and rigorously analyze the performance of the RAP. First, we show that the throughput performance of the RAP depends only on the expectation of the selection distribution where the backoff counter is selecte

Traffic prediction facilitates intelligent networking maintenance by enabling efficient network resource allocation. With the development of machine learning algorithms, traffic prediction has attracted increasing attention and has been widely used in resource allocation and traffic management. In this paper, we consider an input traffic with a quality of service (QoS) requirement, such as the overflow probability, and propose an adaptive bandwidth allocation method based on the Gaussian process

For beyond the fifth-generation (5G) and future wireless communications, spatial consistency that represents the correlation between propagation channel characteristics in close proximity has become one of the major issues in channel modeling to describe channels more realistically in emerging scenarios, such as device-to-device (D2D). In this study, we propose a novel path loss model based on multi-dimensional Gaussian process regression (GPR) that provides spatial consistency to channels in pr

The current contention mechanism of the IEEE 802.11 distributed coordination function (DCF) is known to have some drawbacks, e.g., collisions and low short-term fairness induced by minimizing the backoff stage after every successful transmission. To solve the drawbacks we propose an adaptive contention window control scheme which uses a single backoff stage while maintaining the advantages of the current IEEE 802.11 DCF such as simplicity and distributivity. We first introduce the key concept ca

The use of multi-interfaced devices has been steadily increasing due to the popularity of multihomed streaming services in heterogeneous wireless access networks. However, running multiple interfaces simultaneously in a mobile terminal (MT) may cause serious battery drain even when interfaces employ sleep modes. In addition, sleep modes may result in significant degradation of the quality of service (QoS) in terms of packet delay or jitter. This paper examines multihomed MTs and the use of data

We consider a distributed random channel access policy in a cognitive radio network where multiple secondary users (SUs) contend for spectrum usage over available multiple primary user (PU) channels. In the random channel access policy each SU stochastically determines whether to access a channel based on the access probability (AP) which is adapted to the sensing results. It is then important to obtain the optimal AP values from the SUs' throughput performance perspective. In our analysis, we a

This work seeks to develop an analytical model for the per-node throughput analysis of IEEE 802.11 WLAN networks with hidden nodes by extending the Bianchi's model. With the analytic model we derive the per-node throughput of each node and quantify the impact of hidden nodes on per-node throughput. Through our analysis, we find that nodes having more hidden nodes are likely to have worse throughput performance than nodes having less hidden nodes, so resulting in unfairness in per-node throughput

We present Color Sommelier, an interactive color recommendation system based on community-generated color palettes that helps users to choose harmonious colors on the fly. We used an item-based collaborative filtering technique with Adobe Color CC palettes in order to take advantage of their ratings that reflect the general public?s color harmony preferences. Every time a user chooses a color(s), Color Sommelier calculates how harmonious each of the remaining colors is with the chosen color(s).

Rainfall is considered as one of the most crucial atmospheric elements that cause attenuation in signal propagation, especially in high-frequency range for fifth-generation (5G) and beyond wireless networks. To unveil the complex relationships between rain attenuation and other factors including rainfall rate, we propose a new rain attenuation prediction model for terrestrial line-of-sight (LoS) propagation using Gaussian Process Regression (GPR). In the proposed model the Recommendation ITU-R P