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020 ▼a 9780438099296
035 ▼a (MiAaPQ)AAI10901991
035 ▼a (MiAaPQ)OhioLINK:osu1503062069085737
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 621.3
1001 ▼a Chen, Fangzhou.
24510 ▼a Wireless Communication Under Imperfect Source/Channel Information.
260 ▼a [S.l.] : ▼b The Ohio State University., ▼c 2017
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2017
300 ▼a 133 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
500 ▼a Adviser: Can Koksal.
5021 ▼a Thesis (Ph.D.)--The Ohio State University, 2017.
520 ▼a The rapid development of demand for wireless data has lead to the development of numerous new applications, which the existing networks were not designed to handle. Different applications may have substantially different quality of service (QoS)
520 ▼a First, we focus on wireless communication under imperfect source information problem. We consider a system in which two nodes take correlated measurements of a random source with time-varying and unknown statistics. The observations of the sourc
520 ▼a Second, we shift our focus on addressing wireless communication under imperfect knowledge of channel information problems, faced in power control for cellular networks. Coordinated Multipoint (CoMP) promised substantial throughput gain for next-
520 ▼a Lastly, we focus on adaptive modulation and coding (AMC). In this dissertation, we propose a new rate adaptation method that consists of two parts: a data-guided physical layer abstraction model and a recursive SINR estimation and AMC control al
590 ▼a School code: 0168.
650 4 ▼a Electrical engineering.
690 ▼a 0544
71020 ▼a The Ohio State University. ▼b Electrical and Computer Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-11B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0168
791 ▼a Ph.D.
792 ▼a 2017
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000349 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자