Maximum likelihood algorithms for joint estimation of synchronisation impairments and channel in multiple input multiple output–orthogonal frequency division multiplexing system. Issue 15 (1st October 2013)

• Record Type: Journal Article
• Authors: Jose, Renu; Hari, K.V.S.
• Is Part Of: IET communications. Volume 7:Issue 15(2013)
• Page Start: 1567
• Page End: 1579
• Publication Date: 2013-10-01
• Subjects: channel estimation -- maximum likelihood estimation -- MIMO communication -- numerical analysis -- OFDM modulation -- search problems; modified maximum likelihood algorithms -- synchronisation channel estimation -- synchronisation impairment estimation -- multiple input multiple output‐orthogonal frequency division multiplexing system -- ML algorithms -- MIMO‐OFDM system -- carrier frequency offset effects -- sampling frequency offset effects -- symbol timing error -- channel impulse response -- Cramér‐Rao lower bounds -- MML algorithm -- joint grid search complexity reduction -- stage‐wise ML algorithm -- SML algorithm -- multiple one‐dimensional searches -- numerical simulations; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2012.0667
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Maximum likelihood (ML) algorithms, for the joint estimation of synchronisation impairments and channel in multiple input multiple output–orthogonal frequency division multiplexing (MIMO–OFDM) system, are investigated in this work. A system model that takes into account the effects of carrier frequency offset, sampling frequency offset, symbol timing error and channel impulse response is formulated. Cramér–Rao lower bounds for the estimation of continuous parameters are derived, which show the coupling effect among different impairments and the significance of the joint estimation. The authors propose an ML algorithm for the estimation of synchronisation impairments and channel together, using the grid search method. To reduce the complexity of the joint grid search in the ML algorithm, a modified ML (MML) algorithm with multiple one‐dimensional searches is also proposed. Further, a stage‐wise ML (SML) algorithm using existing algorithms, which estimate less number of parameters, is also proposed. Performance of the estimation algorithms is studied through numerical simulations and it is found that the proposed ML and MML algorithms exhibit better performance than SML algorithm.