Semi-blind simplified mean value channel estimator for MC-IDMA systems. (October 2016)

• Record Type: Journal Article
• Authors: Adisa, Adeola; Mneney, Stanley H.; Oyerinde, Olutayo O.
• Is Part Of: Computers & electrical engineering. Volume 55(2016)
• Page Start: 1
• Page End: 11
• Publication Date: 2016-10
• Subjects: Channel state information -- MC-IDMA -- Linear estimation -- Semi-blind channel estimation -- Eigenvalue -- Eigenvector decomposition; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.08.024
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Channel estimation schemes for multi-carrier interleave division multiple access (MC-IDMA) wireless communication systems. Structured correlation and the eigenvector decomposition (EVD) techniques for simplification of the minimum mean square error (MMSE) algorithm. Development of simplified mean value estimator (SMVE)-based semi-blind channel estimator. Abstract: The Multi-Carrier Interleave Division Multiple Access (MC-IDMA) scheme combines Orthogonal Frequency Division Multiplexing and IDMA. The scheme combats both Inter-Symbol Interference (ISI) and Multiple Access Interference (MAI). For coherent detection of the transmitted signals at the receiver, Channel State Information (CSI) is crucial. There are several schemes that can be used to obtain CSI at the receiver, such as pilot-based schemes and decision directed scheme, semi-blind and as blind channel estimation schemes. This paper focuses on developing semi-blind channel estimation scheme for the MC-IDMA systems. The developed scheme is based on Minimum Mean Square Error (MMSE) algorithm. The estimator employs applications of the eigenvalue and eigenvector decomposition (EVD) techniques to simplify the MMSE algorithm, and is named Simplified Mean Value Estimator (SMVE). Simulation results show that the proposed SMVE-based estimator outperforms Least Mean Square (LMS) algorithm-based estimator, Modified Minimized Mean Value Estimator (MMMVE), and the Minimized Mean Value-MMSE Estimator (MMVE). Graphical abstract: Semi-Blind Simplified Mean Value Estimator (SMVE) compared with LMS-based channel estimator and "known channel scenario" in a Multi-Carrier Interleave Division Multiple Access (MC-IDMA) system over a fast fading channel.