研究生课程开设申请表

开课院（系、所）：信息科学与工程学院

课程申请开设类型： 新开  重开□     更名□ （ 请在 □ 内打勾，下同 ）

课程 名称

中文

凸优化理论方法

英文

Convex Optimization Theory and Methods

待分配课程编号

DB 004225

课程适用学位级别

博士



硕士



总学时

32

课内学时

32

学分

2

实践环节

无

用机小时

无

课程类别

□ 公共基础 □ 专业基础 □ 专业必修  专业选修

开课院 ( 系 )

信息科学与工程学院

开课学期

秋季

考核方式

A. □ 笔试（ □ 开卷 □ 闭卷） B. □ 口试 C. □ 笔试与口试结合 D.  其他 研究报告

课程负责人

教师 姓名

王家恒

职称

教授

e-mail

[email protected]

网页地址

授课语言

双语（中 / 英）

课件地址

适用学科范围

通信与信息工程

所属一级学科名称

信息与通信工程 - 通信与信息系统

实验 ( 案例 ) 个数

0

先修课程

高等数学、线性代数

教学用书

教材名称

教材编者

出版社

出版年月

版次

主要教材

Convex Optimizaiton ( 凸优化 )

S. Boyd, L. Vandenberghe

Cambridge University Press

2004

主要参考书

Convex Optimizaiton Theory

D. P. Bertsekas

Athena Scientific

2009

Convex Optimization in Signal Processing and Communications

D. P. Palomar, Y. C. Eldar

Cambridge University Press

2009

一、课程介绍（含教学目标、教学要求等） （ 300 字以内）

近二十年来，随着凸优化理论趋于成熟、高效优化算法不断涌现及各种信息设备计算能力大幅度提升，凸优化理论及方法已成为包括无线 / 有线通信、信号处理、电路设计、自动控制、金融工程、交通、物流等几乎所有工程领域最重要的数学工具之一。本课程主要面向（但不限于）通信与信息工程专业的硕士研究生和博士研究生，系统的介绍凸优化理论方法及其应用。课程的主要内容包括背景及基础知识、凸优化基础理论与算法以及凸优化在通信和信号处理方面的应用几个部分。本课程将培养研究生运用凸优化理论与算法解决相关领域科研问题的能力。

二、教学大纲（含章节目录）： （可附页）

本课程包括三个主要部分：

1. 背景及基础知识

   • 课程介绍及相关基础知识：背景知识介绍及线性代数、概率知识补充

2. 凸优化基础理论与算法

   • 凸集合与凸函数：凸集合与凸函数定义及保持凸特性运算

   • 凸优化问题：凸优化问题定义， LP 、 SOCP 、 SDP 等凸问题，问题等价变换

   • 拉格朗日对偶及 KKT 条件：最小准则、拉格朗日、对偶问题、 KKT 条件

   • 凸优化算法及软件：梯度算法、牛顿算法、内点算法及 CVX 软件

3. 凸优化应用

   • 窄带及宽带（ OFDM ）通信系统优化：窄带及宽带接收机设计与功率分配

   • 单用户 MIMO 通信系统优化： MIMO 接收机设计，收发机联合优化

   • 多用户 MIMO 通信系统优化：多用户上行、下行收发机设计

   • 半正定规划及其应用： SDP 及其在波束成形与检测方面应用

   • 鲁棒性优化：最坏情况鲁棒性优化与统计鲁棒性优化及其应用

   • 分解算法及其应用：基于凸优化的 d ual/primal 分解算法及其应用

   • 非凸优化问题及 SCA 与 MM 算法：连续凸逼近（ SCA ）与 Majorization-Minimization 算法

三、教学周历

周次	教学内容	教学方式
1	课程介绍及相关基础知识	讲课
2	凸集合与凸函数	讲课
3	凸优化问题	讲课
4	拉格朗日对偶及 KKT 条件	讲课
5	凸优化算法及软件	讲课
6	窄带及宽带（ OFDM ）通信系统优化	讲课
7	单用户 MIMO 通信系统优化	讲课
8	多用户 MIMO 通信系统优化	讲课
9	半正定规划及其应用	讲课
10	鲁棒性优化	讲课
11	分解算法及其应用	讲课
12	非凸优化问题及 SCA 与 MM 算法	讲课
13	（注：每周 3 节课，共 12 周， 3 2 学时）
14
15
16
17
18

注： 1. 以上一、二、三项内容将作为中文教学大纲，在研究生院中文网页上公布，四、五内容将保存在研究生院。 2. 开课学期为：春季、秋季或春秋季。 3. 授课语言为：汉语、英语或双语教学。 4. 适用学科范围为：公共，一级，二级，三级。 5. 实践环节为：实验、调研、研究报告等。 6. 教学方式为：讲课、讨论、实验等。 7. 学位课程考试必须是笔试。 8. 课件地址指在网络上已经有的课程课件地址。 9. 主讲教师简介主要为基本信息（出生年月、性别、学历学位、专业职称等）、研究方向、教学与科研成果，以 100 至 500 字为宜。

四、主讲教师简介：

王家恒，洪堡（高级）学者， IEEE 高级会员，教授，博士生导师。 2001 年和 2006 年于东南大学无线电工程系获得学士和硕士学位， 2010 年于香港科技大学电子与计算机工程系获得博士学位， 2010 年至 2011 年期间在瑞典皇家工学院信号处理实验室从事博士后研究工作，自 2011 年任教于东南大学移动通信国家重点实验。长期从事无线通信和信号处理系统优化设计方面工作，研究方向包括： 5G/6G 移动通信系统、 MIMO/ 大规模 MIMO 传输、密集异构网络、无线光通信、毫米波通信、区块链技术、机器学习、边缘计算、鲁棒性设计、分布式算法设计、绿色通信、协作通信、认知无线电等。发表学术论文 140 余篇，包括 IEEE 、 OSA 等国际权威期刊（ SCI ）论文 90 余篇。

五、任课教师信息（包括主讲教师）：

任课 教师	学科 （专业）	办公 电话	住宅 电话	手机	电子邮件	通讯地址	邮政 编码
王家恒	通信与信息系统				[email protected]	无线谷 A1 楼 1 221

六、课程开设审批意见

所在院（系） 审 批 意 见	负责人： 日 期：
所在学位评定分 委员会审批意见	分委员会主席： 日 期：
研究生院审批意见	负责人： 日 期：
备 注

说明： 1 ．研究生课程重开、更名申请也采用此表。表格下载： http: /seu g s.seu.edu.cn/ down / 1.asp

2 ．此表一式三份，交研究生院、院（系）和自留各一份，同时提交电子文档交研究生院。

Application Form For Opening Graduate Courses

School (Department/Institute ) ：

Course Type: New Open  Reopen □   Rename □ （ Please tick in □, the same below ）

Course Name

Chinese

凸优化理论方法

English

Convex Optimization Theory and Methods

Course Number

DB 004225

Type of Degree

Ph. D



Master



Total Credit Hours

32

In Class Credit Hours

32

Credit

2

Practice

Computer-using Hours

Course Type

□Public Fundamental □ Major Fundamental □ Major Compulsory  Major Elective

School (Department)

Information School

Term

Fall

Examination

A. □ Paper （ □ Open-book □ Closed-book ） B. □ Oral C. □ Paper-oral Combination                       D. □ Others research report

Chief Lecturer

Name

Wang, Jiaheng

Professional Title

Professor

E-mail

[email protected]

Website

Teaching Language used in Course

Chinese and English

Teaching Material Website

Applicable Range of Discipline

Communications and Information engineering

Name of First-Class Discipline

Communications and Information system

Number of Experiment

Preliminary Courses

advanced mathematics, linear algebra

Teaching Books

Textbook Title

Author

Publisher

Year of Publication

Edition Number

Main Textbook

Convex Optimizaiton

S. Boyd, L. Vandenberghe

Cambridge University Press

2004

Main Reference Books

Convex Optimizaiton Theory

D. P. Bertsekas

Athena Scientific

2009

Convex Optimization in Signal Processing and Communications

D. P. Palomar, Y. C. Eldar

Cambridge University Press

2009

1. Course Introduction (including teaching g oals and requirements) within 300 words :

During the recent two decades, with the development of convex optimization theory and methods as well as enhanced computational capacity of various information devices, convex optimization has become one of the most important mathematical tools in almost all engineering areas such as wireless/wireline communications, signal processing, circuit designs, automatic control, finance engineering, traffic engineering, logistics and etc. This course aims to systematically introduce convex optimization theory and methods to doctor and master graduate students majoring in (but not limited) communications and information engineering. The course is composed several parts including the background and preliminary knowledge, fundamental theory and methods of convex optimization, and advanced applications of convex optimization. Through this course, the capability of the students to address research problems using convex optimization will be trained.

2. Teaching Syllabus (including the content of chapters and sections . A sheet can be attached):

This course contains three main parts:

1. background and preliminary knowledge

   • Course introduction and preliminary knowledge: introduce some background and preliminary knowledge such as linear algebra and probabilities.

2. Fundamental theory and methods of convex optimization

   • Convex sets and convex functions: the definitions of convex sets and functions and related operations.

   • Convex optimization problems: the definition of convex problems , LP , SOCP , SDP formulations , equivalent transformations.

   • Lagrange duality and KKT conditions: minimum principle, Lagrange, dual problems, and KKT conditions.

   • Convex optimization algorithms and software: gradient algorithms, Newton algorithm, interior-point algorithm and CVX.

3. Advanced applications of convex optimization

   • Narrow-band and broad-band (OFDM) communication system optimization : receiver designs and power allocation.

   • Single-user MIMO communication system optimization: MIMO receiver designs and t ransceiver designs.

   • Multi-user MIMO communication system optimization: multi-user uplink and downlink transceiver designs.

   • Semidefinite programing and its applications: SDP and its applications in beamforming and detection.

   • Robust optimization: worst-case robust and statistically robust optimization and their applications.

   • Decomposition algorithms and their applications: dual/primal decomposition algorithms and their applications.

   • Nonconvex optimization problems via SCA and MM algorithms: Successive convex approximation and majorization-minimization algorithms.

3. Teaching Schedule:

Week	Course Content	Teaching Method
1	Course introduction and preliminary knowledge	lecture
2	Convex sets and convex functions	lecture
3	Convex optimization problems	lecture
4	Lagrange duality and KKT conditions	lecture
5	Convex optimization algorithms and software	lecture
6	Narrow-band and broad-band (OFDM) communication system optimization	lecture
7	Single-user MIMO communication system optimization	lecture
8	Multiple-user MIMO communication system optimization	lecture
9	Semidefinite programing and its applications	lecture
10	Robust optimization	lecture
11	Decomposition algorithms and their applications	lecture
12	Nonconvex optimization problems via SCA and MM algorithms	lecture
13
14
15
16
17
18

Note: 1. Above one, two, and three item s are used as teaching Syllabus in Chinese and announce d on the Chinese website of G raduate S chool . The f our and five item s are preserve d in G raduate S chool.

2. Course term s : Spring, Autumn , and Spring-Autumn term .

3. The teaching language s for courses : Chinese, English or Chinese-English .

4. Applicable range of discipline: public, first-class discipline, second-class discipline, and third -class discipline.

5. Practice includes : experiment , investigation, research report , etc .

6. Teaching method s: lecture, seminar, practice , etc .

7. E xamination for degree courses must be in paper.

8. Teaching material website s are those which have already been announc ed.

9. Brief introduction of chief lecturer should include: personal information (date of birth, gender, degree achieved, professional title), research direction , teaching and research achievement s . (within 100 - 500 words )

4. Brief Introduction of Chief lecturer:

Jiaheng Wang received the Ph.D. degree in electronic and computer engineering from the Hong Kong University of Science and Technology, Kowloon, Hong Kong, in 2010, and the B.E. and M.S. degrees from the Southeast University, Nanjing, China, in 2001 and 2006, respectively.

He is currently a Full Professor at the National Mobile Communications Research Laboratory (NCRL), Southeast University, Nanjing, China. From 2010 to 2011, he was with the Signal Processing Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden. He also held visiting positions at the Friedrich Alexander University Erlangen-Nürnberg, Nürnberg, Germany , and the University of Macau, Macau. His research interests include optimization in signal processing and wireless communications.

Dr. Wang has published more than 140 articles on international journals and conferences. From 2014 to 2018, he served as an Associate Editor for the IEEE Signal Processing Letters. From 2018, he serves as a Senior Area Editor for the IEEE Signal Processing Letters. He was a recipient of the Humboldt Fellowship for Experienced Researchers and the best paper awards of IEEE GLOBECOM 2019, ADHOCNETS 2019, and WCSP 2014.

5. Lecturer I nformation (include chief lecturer)

Lecturer	Discipline (major)	Office Phone Number	Home Phone Number	Mobile Phone Number	Email	Address	Postcode
Wang, Jiaheng	Communications and information				[email protected]