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As presented in [23 26], the iterative channel estimation methods are combined with equalization, data detection, decoding, or even interference cancellation.
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QAM and adaptive equalization permitted data transmission of 9.6 kilobits per second over four-wire circuits.
At the end of the training phase, the receiving node has imperfect CSI for channel equalization and data detection.
The speaker's own computer will interpret the sound bits as well as all sorts of equalization and filtering data.
At the receiver, after equalization the original data can be reconstructed by inverting the applied mapping.
The upcoming data equalization is performed by multiplying the inverse of the channel estimation matrix obtained in the first step with the received data symbol.
The channel equalization and payload data detection/decoding is then based on inferred complex channel gains at the payload symbol locations.
The equalizers work in training mode when the training symbols are received and then switch to the equalization mode when data symbols are received.
During this process, the pilot symbols are inserted in parallel and at the receiving end they are used for calculating H matrix which consists of channel estimates for different subcarrier positions and is later used for data equalization.
The estimated CIR is then, translated into the frequency domain by means of FFT which results in an estimation of the CFR that can be used for data equalization process.
In this paper, we propose a new equalization scheme for high data rate single carrier MIMO UWA channels.
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