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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 55  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
IE, MVE, CQ, IMQ
(Joint) [detail]
2024-03-15
15:50
Okinawa Okinawa Sangyo Shien Center
(Primary: On-site, Secondary: Online)
Towarods Similarity-Preserving Post-Training Quantization for Lightweight Maize Disease Detection
Carlos Victorino Padeiro, Tse-Wei Chen, Takahiro Komamizu, Ichiro IDE (Nagoya University) IMQ2023-90 IE2023-145 MVE2023-119
The traditional crop disease diagnosis process, relying on expert visual observation, is costly, time-consuming, and pro... [more] IMQ2023-90 IE2023-145 MVE2023-119
pp.414-419
RCS, SAT
(Joint)
2023-08-31
10:30
Nagano Naganoken Nokyo Building, and online
(Primary: On-site, Secondary: Online)
Enhancing CSI Feedback in FDD Massive MIMO Systems using Dropout-based Deep Neural Network
Junjie Gao, Mondher Bouazizi, Tomoaki Ohtsuki (Keio Univ.), Guan Gui (NJUPT) RCS2023-101
Accessing precise downlink channel state information (CSI) is crucial in maximizing the
benefits of frequency division ... [more]
RCS2023-101
pp.1-4
RCS 2023-06-16
10:40
Hokkaido Hokkaido University, and online
(Primary: On-site, Secondary: Online)
Key Reconciliation in a Wireless Physical Layer Secret Key Agreement Using Adaptive Quantization Codewords
Seiju Yoshida, Hideichi Sasaoka, Hisato Iwai, Shinsuke Ibi (Doshisha) RCS2023-70
In wireless physical layer secret key agreement, key reconciliation methods and their efficiency improvement are importa... [more] RCS2023-70
pp.247-252
RCS, SR, SRW
(Joint)
2023-03-01
10:25
Tokyo Tokyo Institute of Technology, and Online
(Primary: On-site, Secondary: Online)
A Novel DNN-based CSI Feedback with Quantization for FDD Massive MIMO Systems
Junjie Gao, Mondher Bouazizi, Tomoaki Ohtsuki (Keio Univ.), Gui Guan (NJUPT) RCS2022-252
Accessing the accurate downlink channel state information
(CSI) is essential to take full advantage of frequency
divis... [more]
RCS2022-252
pp.31-35
AP 2022-10-19
12:20
Gifu GIFU CITY CULTURE CENTER
(Primary: On-site, Secondary: Online)
[Poster Presentation] Study on key reconciliation for secret key agreement based on radio propagation characteristic
Seiju Yoshida, Hideichi Sasaoka, Hisato Iwai, Shinsuke Ibi (Doshisha Univ.) AP2022-130
One of the secret key agreement based on radio propagation characteristics is to generate a quantized codeword by quanti... [more] AP2022-130
pp.154-155
MIKA
(3rd)
2022-10-14
10:40
Niigata Niigata Citizens Plaza
(Primary: On-site, Secondary: Online)
[Poster Presentation] A New CSI Feedback with Quantization Based on Adaptive DNN for FDD Massive MIMO Systems
Junjie Gao, Mondher Bouazizi, Tomoaki Ohtsuki (Keio Univ.), Guan Gui (NJUPT)
Accessing the accurate downlink channel state information (CSI) is essential to take full advantage of frequency divisio... [more]
RCS 2021-06-25
10:20
Online Online A Study on Deep Unfolding-Aided Quantized AMP for High-Dimensional Signal Detection
Atsunori Shimamura, Takumi Takahashi (Osaka Univ), Shinsuke Ibi (Doshisha Univ), Seiichi Sampei (Osaka Univ) RCS2021-68
We consider a look-up table (LUT)-based multi-user detection (MUD) via quantized approximate message passing (AMP) in la... [more] RCS2021-68
pp.226-231
NLP, MSS
(Joint)
2021-03-16
10:45
Online Online Approximate formula of the mean square quantization error of golden ratio encoders
Yoshikatsu Kashiwabara, Yutaka Jitsumatsu (Kyushu Univ.) NLP2020-63
The Golden Ratio Encoder (GRE) is a type of analog-to-digital (A/D) conversion method. GRE expands the input analog valu... [more] NLP2020-63
pp.47-52
IT, SIP, RCS 2020-01-23
16:15
Hiroshima Hiroshima City Youth Center [Invited Talk] Design of Δ∑ modulators matched to their connected systems
Shuichi Ohno (Hiroshima Univ.) IT2019-58 SIP2019-71 RCS2019-288
Quantization maps a large set of input values onto a smaller set of output values, which is fundamental for digital proc... [more] IT2019-58 SIP2019-71 RCS2019-288
p.131
SIS 2019-12-12
14:55
Okayama Okayama University of Science Machine learning algorithms with quantized images and their influence
Takayuki Osakabe, Yuma Kinoshita, Hitoshi Kiya (Tokyo Metro.Univ.) SIS2019-27
Recently, appling quantized images to machine learning algorithms
is expected to enhance robustness against adversarial... [more]
SIS2019-27
pp.23-28
EMCJ, IEE-SPC
(Joint)
2019-11-15
15:50
Tokyo Kikai-Shinko-Kaikan Bldg. Measurement of an Effect of Resolution of Side Channel Waveform on Acquisition of Secret Key
Kohei Utsumi (Tohoku Univ), Yu-ichi Hayashi (NAIST), Takaaki Mizuki, Hideaki Sone (Tohoku Univ) EMCJ2019-73
A side-channel attack is known as a serious threat which can obtain a secret key by analyzing physical information leaka... [more] EMCJ2019-73
pp.13-16
RCS 2019-10-25
14:10
Kanagawa Yokosuka Research Park [Invited Lecture] Digital RoHR for Distributed Collaborative MIMO Reception
Daisuke Umehara (Kyoto Inst. of Tech.) RCS2019-198
We apply the Lloyd-Max quantization to a distributed collaborative interference canceller (DCIC) with digital higher-fre... [more] RCS2019-198
pp.109-114
SIS 2019-03-07
12:15
Tokyo Tokyo Univ. Science, Katsushika Campus A Color Quantization Method Preserving Infrequent Salient Colors for Image Enlargement
Yukiya Fukuda, Hideaki Misawa (NIT, UC), Hakaru Tamukoh (KIT), Ryosuke Kubota (NIT, UC), Byungki Cha, Takashi Aso (KIIT) SIS2018-51
In this report, we propose an image enlargement algorithm with a color quantization considering infrequent salient color... [more] SIS2018-51
pp.75-80
RCS, SIP, IT 2019-01-31
09:25
Osaka Osaka University A Study on Replica Generation Using Multi-layer LUT based on Information Bottleneck for MF-GaBP in Massive MIMO Detection
Liwen Wang, Takumi Takahashi, Shinsuke Ibi, Seiichi Sampei (Osaka Univ.) IT2018-36 SIP2018-66 RCS2018-243
This paper proposes a symbol replica generation method using multi-layer look-up table (LUT) designed based on the infor... [more] IT2018-36 SIP2018-66 RCS2018-243
pp.7-12
EMM 2017-11-07
13:00
Kagoshima Kagoshima Univ. (Inamori Academy) A Study of DCT-OFDM-Based Watermarking Scheme Assisted by Error Correcting Code
Shogo Shigemoto, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.) EMM2017-64
There are two variants for the DCT-OFDM-based watermarking scheme that retains high robustness against various kinds of ... [more] EMM2017-64
pp.47-52
NS, ASN, RCC, RCS, SR
(Joint)
2017-07-19
16:00
Hokkaido Hokkaido Univ. Performance Evaluation of Collaborative Interference Canceller with Quantization Error and Spatial Correlation
Rieko Saiki, Daisuke Umehara (Kyoto Inst of Tech.), Hidekazu Murata (Kyoto Univ.), Satoshi Denno (Okayama Univ.) RCS2017-104
Collaborative Interference Canceller (CIC) has been proposed to enhance cellular networks. CIC enables us to a large sca... [more] RCS2017-104
pp.67-72
RCS 2017-06-23
10:20
Okinawa Ishigaki Shoukou Kaikan Effect of Quantization Noise of Iterative Digital Self-Interference Canceller for OFDM Using Full Duplex
Hiroki Yamada, Takahiro Ohtomo, Mamoru Sawahashi (Tokyo City Univ.), Keisuke Saito (NTT DOCOMO) RCS2017-82
This paper investigates the effect of quantization noise which is caused by the number of quantization bits of analod-to... [more] RCS2017-82
pp.191-196
RCC, MICT 2017-05-11
15:15
Tokyo Kikai-Shinko-Kaikan Bldg. Optimal Bit Allocation for Quantization of Observation Signals in Feedback Control
Kazuya Hanamoto, Shuichi Ohno (Hiroshima Univ.) RCC2017-1 MICT2017-1
An optimal bit allocation to observation signals
in digital feedback control systems is developed, where
each commun... [more]
RCC2017-1 MICT2017-1
pp.1-6
RCC, MICT 2017-05-11
16:05
Tokyo Kikai-Shinko-Kaikan Bldg. A coding scheme for state feedback communication using heterogeneous BER of QAM signals
Takashi Hosono (Kyoto Univ.), Kazunori Hayashi (Osaka City Univ.) RCC2017-3 MICT2017-3
In Networked Control Systems, whose main purpose is not communications, it is commonly hard to introduce advanced source... [more] RCC2017-3 MICT2017-3
pp.11-16
CAS, CS 2017-02-24
09:30
Shiga   Capacity of Collaborative Interference Canceller: Quantization Error and Spatial Correlation
Daisuke Umehara, Rieko Saiki (Kyoto Inst. of Tech.), Hidekazu Murata (Kyoto Univ.), Satoshi Denno (Okayama Univ.) CAS2016-125 CS2016-86
Let us assume that space division multiplexing (SDM) signal is transmitted at a base station (BS) with a number of anten... [more] CAS2016-125 CS2016-86
pp.63-68
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