Channel Estimation Algorithms for OFDM-IDMA: Complexity and Performance
Author
Summary, in English
Abstract in Undetermined
In this paper, a number of channel estimation algorithms for iterative receivers are compared for the case of an up-link orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) system. Both pilot based algorithms, used to obtain an initial estimate, as well as semi-blind decision-directed algorithms working as a component of the iterative receiver are considered. Algorithms performing either joint minimum mean square error (MMSE) channel estimation, or iterative estimation using space-alternating expectation maximization (SAGE), are evaluated. The considered algorithms differ in terms of complexity, as well as performance. The main contribution of this paper is to give an overview of different channel estimation approaches for OFDM-IDMA, where the complexity versus performance tradeoff is at the focal point. There is no single channel estimator providing the best tradeoff and our analysis shows how the system load (number of users) and the SNR influence the estimator choice.
In this paper, a number of channel estimation algorithms for iterative receivers are compared for the case of an up-link orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) system. Both pilot based algorithms, used to obtain an initial estimate, as well as semi-blind decision-directed algorithms working as a component of the iterative receiver are considered. Algorithms performing either joint minimum mean square error (MMSE) channel estimation, or iterative estimation using space-alternating expectation maximization (SAGE), are evaluated. The considered algorithms differ in terms of complexity, as well as performance. The main contribution of this paper is to give an overview of different channel estimation approaches for OFDM-IDMA, where the complexity versus performance tradeoff is at the focal point. There is no single channel estimator providing the best tradeoff and our analysis shows how the system load (number of users) and the SNR influence the estimator choice.
Department/s
Publishing year
2012
Language
English
Pages
1722-1732
Publication/Series
IEEE Transactions on Wireless Communications
Volume
11
Issue
5
Document type
Journal article
Publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
Topic
- Electrical Engineering, Electronic Engineering, Information Engineering
Keywords
- discrete prolate spheroidal (DPS) sequences
- SAGE
- maximization (EM)
- expectation
- algorithm complexity
- Channel estimation
- OFDM-IDMA
Status
Published
Research group
- Telecommunication Theory
- Radio Systems
ISBN/ISSN/Other
- ISSN: 1536-1276