ARTIFICIAL INTELLIGENCE ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
CMP4323 | Wireless and Mobile Networks | Spring |
3 | 0 | 3 | 6 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
Course Level: | Bachelor’s Degree (First Cycle) |
Mode of Delivery: | Face to face |
Course Coordinator : | MEHMET ŞÜKRÜ KURAN |
Recommended Optional Program Components: | None |
Course Objectives: | This course covers wireless and mobile networking concepts and protocols with real-world examples. This course aims to prvide students with a basic understanding about the wireless and mobile networks and related problem solving discipline using mathematics / engineering principles. |
The students who have succeeded in this course; I. An ability to design algorithms for wireless communication problems II. An ability to develop test and monitoring programs for wireless networks III. An ability to design packet size optimization techniques for wireless networks IV. An ability to analyze and evaluate the performance of wireless networks V. An ability to design communication solutions for vehicular networks VI. An ability to organize and document program code following the principles of software engineering and to professional prepare project reports. |
This course covers wireless and mobile networking concepts and protocols with real-world examples. After completing the course, students will get a basic understanding about the wireless and mobile networks and related problem solving discipline using mathematics / engineering principles. 1st Week: An overview of wireless networks 2nd Week: Broadband Communication Technologies 3rd Week: 3G Communication Technologies 4th Week: 4G and Beyond 5th Week: Wireless Local Area Networks 6th Week: Midterm Exam-I 7th Week: Near Field Communications 8th Week: RFID 9th Week: Ad Hoc Networks 10th Week: Wireless Sensor Networks 11th Week: Midterm Exam-II 12th Week: Packet Size Optimization in Wireless Networks 13th Week: Underwater Acoustic and Underground Communications 14th Week: Vehicular Networks and Review |
Week | Subject | Related Preparation |
1) | 1st Week: An overview of wireless networks | |
2) | 2nd Week: Broadband Communication Technologies | |
3) | 3rd Week: 3G Communication Technologies | |
4) | 4th Week: 4G and Beyond | |
5) | 5th Week: Wireless Local Area Networks | |
6) | 6th Week: Midterm Exam-I | |
7) | 7th Week: Near Field Communications | |
8) | 8th Week: RFID | |
9) | 9th Week: Ad Hoc Networks | |
10) | 10th Week: Wireless Sensor Networks | |
11) | 11th Week: Midterm Exam-II | |
12) | 12th Week: Packet Size Optimization in Wireless Networks | |
13) | 13th Week: Underwater Acoustic and Underground Communications | |
14) | 14th Week: Vehicular Networks |
Course Notes / Textbooks: | 1. W. Stallings, “Data and Computer Communications,” Prentice Hall, 8th edition, 2007. |
References: | 2. I.F. Akyildiz and M.C. Vuran, ''Wireless Sensor Networks,'' John Wiley & Sons, 2010. |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | 10 | % 5 |
Project | 1 | % 25 |
Midterms | 2 | % 40 |
Final | 1 | % 30 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 45 | |
PERCENTAGE OF FINAL WORK | % 55 | |
Total | % 100 |
Activities | Number of Activities | Workload |
Course Hours | 14 | 42 |
Study Hours Out of Class | 14 | 82 |
Midterms | 2 | 6 |
Final | 1 | 3 |
Total Workload | 133 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Have sufficient background in mathematics, science and artificial intelligence engineering. | |
2) | Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions. | |
3) | Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose. | |
4) | Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction. | |
5) | Select and use modern techniques and tools necessary for engineering applications. | |
6) | Design and conduct experiments, collect data, and analyse and interpret results. | |
7) | Work effectively both as an individual and as a multi-disciplinary team member. | |
8) | Access information via conducting literature research, using databases and other resources | |
9) | Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning. | |
10) | Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field. | |
11) | Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level. | |
12) | Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age. | |
13) | Have a sense of professional and ethical responsibility. | |
14) | Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices. |