Textbook reading seminar 2022

Zoom Meeting

• ML https://zoom.us/j/95100622133 (14:40, Wed)
• CM https://zoom.us/j/95330856753 (16:25, Fri)

Channel Modeling (CM)

• 電気電子工学文献詳読I（M1)・II（M2）
• Time: 16:25-17:55, Wed
• Lecturers (M2/M1): Calist, Tsukada, Shibata, Suzuki, Takahashi
• Articles (Spring, 2022)
  1. Channel Investigation of Outdoor Millimeter-Wave Access Links, Richard Jürgen Weiler, Doctral Dissertation, TU Berlin.
  2. S. Ju, Y. Xing, O. Kanhere and T. S. Rappaport, “Millimeter Wave and Sub-Terahertz Spatial Statistical Channel Model for an Indoor Office Building,” in IEEE Journal on Selected Areas in Communications, vol. 39, no. 6, pp. 1561-1575, June 2021, doi: 10.1109/JSAC.2021.3071844.
  3. P. Zhang, C. Yi and H. Wang, “Machine-Learning-Assisted Modeling of Millimeter-Wave Channels,” 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI), 2021, pp. 233-234, doi: 10.1109/APS/URSI47566.2021.9704405.
     
  4. T. Zhou, Y. Qiao, S. Salous, L. Liu and C. Tao, “Machine Learning Based Multipath Components Clustering and Cluster Characteristics Analysis in High-Speed Railway Scenarios,” in IEEE Transactions on Antennas and Propagation, doi: 10.1109/TAP.2021.3137417.
  5. A. Hughes et al., “Measuring the Impact of Beamwidth on the Correlation Distance of 60 GHz Indoor and Outdoor Channels,” in IEEE Open Journal of Vehicular Technology, vol. 2, pp. 180-193, 2021, doi: 10.1109/OJVT.2021.3067673.
  6. X. Zhao, S. Li, Q. Wang, M. Wang, S. Sun and W. Hong, “Channel Measurements, Modeling, Simulation and Validation at 32 GHz in Outdoor Microcells for 5G Radio Systems,” in IEEE Access, vol. 5, pp. 1062-1072, 2017, doi: 10.1109/ACCESS.2017.2650261
  7. Riviello, D.G.; Di Stasio, F.; Tuninato, R. Performance Analysis of Multi-User MIMO Schemes under Realistic 3GPP 3-D Channel Model for 5G mmWave Cellular Networks. Electronics 2022, 11, 330.

Date	Topic	Charge
6/10	Article 1 (4.1-4.3: 3 papers)	Tsukada
6/17	Article 1 (4.5: 1 paper)	Suzuki
6/24	Article 2	Shibata
7/1	Article 3, 4	Calist
7/8 7/15	Article 5	Takahashi
7/15 7/20 (Wed, 4th)	Article 7	Tsukada

• Articles (Fall, 2022)
  1. Ibrahim Yildirim, Ertugrul Basar, “Channel Modeling in RIS-Empowered Wireless Communications,” unpublished.
  2. William Sloane, et. al, “Analysing the 3GPP Spatial Consistency Procedure Through Channel Measurements,” IEEE PIMRC, 2021
  3. Haiyang Miao, “Sub-6 GHz to mmWave for 5G-Advanced and Beyond: Channel Measurements, Characteristics and Impact on System Performance,” IEEE JSAC (unpublished yet).
  4. TBD
  5. Y. Ogawa, et. al, “Sub-Terahertz MIMO Spatial Multiplexing in Indoor Propagation Environments,” IEICE Trans. Commun., Vol.E105-B, No.10, pp.1130-1138, Oct. 2022.

Date	Topic	Charge
10/14 (Fri, 5th)	Article 1	Shibata
11/9 (Wed, 5th)	Article 2	Suzuki
12/7 (Wed, 5th)	Article 3	Tsukada
12/16 1/11 (Wed, 5th)	Article 4	Calist
12/21 1/11 (Wed, 5th)	Article 5	Takahashi

Machine Learning (ML)

• 電気電子工学文献詳読I（M1)・II（M2）
• Textbook (Articles)
  • Python 機械学習プログラミング（第2版）
  • Python Machine Learning Second Edition
    

• Time: 16:25-17:55, Fri
• Lecturers (M2/M1): Li, Pula, Ikegami, Wako, Wang
• Members (B4):
• Schedule

Date	Topic	Charge
6/8	1: Chapter 1, Chapter 2 (ADALINE)	Li
6/15	2: Chapter 3 (Logistic Regression, SVM, DT, KNN)	Pula
6/22	3: Chapter 3 (SVM)	Ikegami
6/29 7/8 (Fri, 5th)	4: Chapter 3 (DT, KNN )	Wako
7/6 7/13	5: Chapter 4 (Preprocessing)	Wang
7/13 7/22 (Fri, 5th)	6: Chapter 5 (Reduction)	Li

Date	Topic	Charge
10/21 (Fri. 5th)	1: Chapter 6 (Tuning)	Wako
11/11 (Fri. 5th)	2: Chapter 7 (Ensemble)	Pula
11/18 (Fri. 5th)	3: Chapter 10 (Regression)	Ikegami
12/9 1/13 (Fri. 5th)	4: Chapter 11 (Clustering)	Wang
12/23 1/13 TBD (Fri. 5th)	5: Chapter 12 (Neural Network)	Koularp

Python 環境構築

既にgitとかpythonをインストール済みの人がやると面倒なことになるかもしれないので気をつけてください．
パワーシェルを立ち上げてPSVersionを確認する．

PS> $PSVersionTable

PSVersionが5.0以上だったらScoopをインストールする．（PSVersionが5.0未満だったらパワーシェルの最新版をインストールしてから行うこと．）

PS> Set-ExecutionPolicy RemoteSigned -scope CurrentUser
PS> iex (new-object net.webclient).downloadstring('https://get.scoop.sh')

成功したら，gitのインストール

PS> scoop install git

次に，Pythonのインストール（Anacondaを使用）

PS> scoop bucket add extras
PS> scoop install anaconda3

最後に任意のディレクトリに教科書のソースコードをクローン

PS> mkdir Work    # 任意のディレクトリ作成（不必要なら無視）
PS> cd Work    # 任意のディレクトリに移動
PS> git clone https://github.com/rasbt/python-machine-learning-book.git    # クローン

エラーとか出たら聞いてください．環境構築まだの人は↑を参考に各自やっておいてください．
・pythonがつかえる
・ソースコードをダウンロード（クローン）済み
になっている人はOKです．あと教科書（日本語版（第1版））は，「\\133.35.167.28\kimlab\users\lab\勉強会資料\ML\教科書」に置いたので各自見てください．
一応，自分で使う目的以外には使用しないでください．