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Departrment of Electrical Engineering King Fahd University of Petroleum and Minerals
| Content Provider | Semantic Scholar |
|---|---|
| Copyright Year | 2003 |
| Abstract | Signals when pass through a channel undergo various forms of distortion, most common of which is Inter-symbol-interference, so called ISI. Inter symbol interference induced errors can cause the receiver to misinterpret the received samples. Equalizers are an important part of receivers, which minimizes the linear distortion produced by the channel. If channel characteristics are known a priori, than optimum setting for equalizers can be computed. But in practical systems the channel characteristics are not known a priori, so adaptive equalizers are used. Adaptive equalizers adapt, or change the value of its taps as time progresses. There are two main types of adaptive equalizers, trained equalizers and blind equalizers. In trained equalizers there is a pseudo-random pattern of bits called training sequence known both to receiver and transmitter. But equalizers for which such a initial training period can be avoided are called BLIND EQUALIZERS. Blind equalizer as opposed to data trained equalizer, is able to compensate amplitude and delay distortion of a communication channel using only channel output sample and knowledge of basic statistical properties of the data symbol. Among some algorithms of blind equalizers like CMA, Stop and Go, GSA, SGA, SRCA etc., Stop and Go is one of the most important algorithms. One of the major disadvantage of Blind Equalizers is that all blind equalizers converge very slowly. However, one can reduce the convergence time by employing some other techniques. In this term paper, I simulate the various algorithms of Blind Equalization including: Sato’s Algorithm Godard Algorithm (Constant Modulus Algorithm) Stop and Go Algorithm (Picchi and Prati Algorithm) |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://faculty.kfupm.edu.sa/ee/akamran/EE514.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
