Modulated Coding for Intersymbol Interference Channels
β Scribed by Xiang-Gen Xia
- Publisher
- M. Dekker
- Year
- 2001
- Tongue
- English
- Leaves
- 305
- Series
- Signal processing and communications 6
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Summarizes the latest research results for mitigating intersymbol interference, introducing a new technique called modulated coding. Considers three cases in MC encoding and decoding and reviews mitigation methods, detailing basic concepts related to modulated coding. DLC: Signal processing.
π SIMILAR VOLUMES
A study of modulated coding (MC), a technique for intersymbol interference (ISI) mitigation. It discusses MC when the ISI is known at both transmitter and receiver, and when only the receiver knows the ISI. It showcases polynomial antiquity resistant modulated coding, and provides an examination of
<p><em>Coded-Modulation Techniques for Fading Channels</em> provides the reader with a sound background for the application of bandwidth-efficient coded-modulation techniques in fading channels. The book systematically presents recent developments in the field, which has grown rapidly in recent year
<p><P>Coding for Optical Channels</P><P></P><P>Ivan Djordjevic</P><P>William Ryan</P><P>Bane Vasic</P><P></P><P></P><P>In order to adapt to the ever-increasing demands for high-speed transmission and distance-independent connectivity, todayβs network operators are implementing 100 Gb/s per dense wav
<p><span>In order to adapt to the ever-increasing demands of telecommunication needs, todayβs network operators are implementing 100 Gb/s per dense wavelength division multiplexing (DWDM) channel transmission. At those data rates, the performance of fiberoptic communication systems is degraded signi
Coding for Wireless Channels is an accessible introduction to the theoretical foundations of modern coding theory, with applications to wireless transmission systems. State-of-the-art coding theory is explained using soft (maximum-likelihood) decoding rather than algebraic decoding. Convolutional co