Ranked 39th and 49th in Popular Articles of IEEE WCL

石橋准教授の論文がIEEE Wireless Communications Letters誌の 2016年1月のPopular Articlesで39位、49位にそれぞれランクインしました。

Two of our papers are ranked as Popular Articles (No. 39 and No. 40) in IEEE Communications Letters (Jan. 2016).

Popular Articles

39. Diversity-Multiplexing Tradeoff of Dynamic Harvest-and-Forward Cooperation

49. Effects of Antenna Switching on Band-Limited Spatial Modulation

IEEE WCL Exemplary Reviewer


Prof. Ishibashi has been selected as IEEE Wireless Communications Letters (WCL) Exemplary Reviewer for his contributions to timely and high-quality reviews.


Recent News

Prof. Ishibashi gave a requested talk about graph-based communication theory at IEICE RCS in Osaka, Japan.

12541160_1107297995971803_2768628039167653061_n12439488_1107298002638469_7976287270056296048_nAlso, our member, Shun and Hiroki, presented their new results respectively about frameless ALOHA and opportunistic relaying at IEICE SR in Nagasaki, Japan.




IEEE Distinguished Lecturer Program

IMG_0014Dr. Fan Bai (IEEE fellow, General Motors Corporation) gave a exciting lecture as IEEE Distinguished Lecturer at our research center, which was supported by IEEE VTS Japan Chapter.

Title : Information Centric Networking on Wheels (IC NoW) –  Architecture and Protocols
Abstract : Recent developments in the automotive industry point to a new emerging domain of vehicular wireless networks, in which vehicles equipped with radios can communicate a wide range of information to each other and the wider Internet, including traffic and safety updates as well as infotainment content.  In this talk, I will discuss how to develop a hybrid network architecture for such vehicular networks which combines both the existing cellular infrastructure as well as new vehicle-to-vehicle (V2V) communication capabilities. The hypothesis is that such a hybrid network architecture will improve cost, capacity and robustness, compared to either a purely centralized cellular-based approach or a purely distributed V2V approach. Under a hybrid architecture, we aim to design information-centric protocols for information dissemination, aggregation, and storage that can exploit the spatio-temporally localized nature of vehicular applications.

Presentation at SITA 2015

Hiroki Kawabata and Shun Ogata, who are 2nd grade master students, gave presentations at The 38th Symposium on Information Theory and its Applications (SITA2015) at Okayama, Japan on Nov. 25th, 2015. Titles are as follows:

H. Kawabata, K. Ishibashi, S. Vuppala, and G. Abreu, “Design and Analysis of Energy Harvesting Relay Selection Using Channel Distribution Information.”

S. Ogata, K. Ishibashi, and G. Abreu, “Analysis of Packet Decoding Probability for Frameless ALOHA with Multiple Base Stations.”


川畑大樹,石橋功至,ヴッパラ サティアナラヤナ,アブレウ ジュゼッペ,”チャネル分布情報を用いたエナジーハーベスティング中継端末選択手法の 設計と解析”

尾形駿,石橋功至,アブレウ ジュゼッペ,”複数ベースステーション存在下におけるフレームレス ALOHA の パケット復号確率解析法に関する一検討”


Prof. Shin visited our laboratory

Prof. Won-Yong Shin from Dankook University visited our laboratory who is an ex-colleague of Prof. Ishibashi at Harvard university. He gave us an exciting and impressive talk and shared his recent results with us. The title and abstract of his talk were as follows:

Title : Huge Challenges on Twitter Analytics Using Geolocation
Abstract : Research in the field of online social networks (OSN) has grown dramatically with the evolution of technologies while harvesting Big Data. Twitter is one of the most popular micro-blogs (or social media). In this talk, I’m going to briefly explain how to perform data collection and processing from the Twitter network via Twitter Streaming API. Next, I’m going to show two recent results analyzed based on geo-tagged tweets. First, I characterize a newly discovered friendship degree according to geographic distance by introducing a new definition of “bidirectional friendship”. The study demonstrates the fact that  the number of friends according to distance follows a double power-law (i.e., double Pareto law) distribution. Second, I introduce a low-complexity algorithm that detects a “point-of-interest (POI)” boundary. Detected boundaries are shown along with a variety of POI types, and it is verified that the runtime complexity scales linearly with the input size.