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3 - Channel estimation for high-rate systems

from Part I - High-rate systems

Published online by Cambridge University Press:  01 June 2011

Zhongjun Wang
Affiliation:
Wipro Techno Centre, Singapore
Yan Xin
Affiliation:
NEC Laboratories America Inc., New Jersey, USA
Xiaodong Wang
Affiliation:
Columbia University, New York, USA
Ismail Guvenc
Affiliation:
DoCoMo Communications Laboratories USA, Inc.
Sinan Gezici
Affiliation:
Bilkent University, Ankara
Zafer Sahinoglu
Affiliation:
Mitsubishi Electric Research Laboratories, Cambridge, Massachusetts
Ulas C. Kozat
Affiliation:
DoCoMo Communications Laboratories USA, Inc.
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Summary

In this chapter, we consider the channel estimation issue in orthogonal frequency division multiplexing (OFDM)-based short-range high-rate wireless communication systems. Even though a number of channel estimation schemes have been proposed for various OFDM systems, few of them are practically suitable for use in the ECMA-368 ultrawideband (UWB) and 60 GHz millimeter-wave communication systems in which limitations on cost and reliability are generally stringent [1, 2]. The main goal of this chapter is to summarize and compare existing channel estimation techniques and to identify an efficient candidate for the practical implementation of low-cost and ultrareliable short-range wireless communication devices.

This chapter begins with an introduction of channel modelling in Section 3.1. Time-dispersive or frequency selective channel propagation characteristics are studied based on the clustering property of multipath components (MPCs). In Section 3.2, several existing channel estimation schemes are reviewed with the focus on those based on training sequences with a block-type structure. Least-squares (LS), linear minimum mean-squared error (LMMSE) and maximum-likelihood (ML)-based algorithms are highlighted followed by a detailed description of a multistage channel estimator. We compare these estimators in terms of their mean-squared error (MSE) performance and complexity for ECMA-368 UWB applications, and show that the multistage channel estimator strikes desirable performance–complexity tradeoffs. Section 3.3 is devoted to studying the impact of channel estimation errors on the system performance. Analysis and numerical examples show that, in terms of symbol error rate (SER) and frame error rate (FER), the multistage channel estimator substantially outperforms the conventional LS approach and it performs comparably to the ML estimator, under various highly noisy multipath channel conditions.

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Publisher: Cambridge University Press
Print publication year: 2011

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