Long-range prediction of wireless channels and transmit preprocessing techniques
Long-range prediction of wireless channels and transmit preprocessing techniques
The advanced channel quality-aware adaptive modulation and coding techniques employed in both existing and future wireless communication systems are capable of substantially improving the achievable system performance. Furthermore, other novel techniques employed by the base-station (BS), such as transmit preprocessing, pre-equalization and so on can be used for simplifying the design of the receiver. All these techniques require accurate channel state information (CSI) at the transmitter side, which necessitate the channel prediction.
Both minimum mean square error (MMSE) channel predictors and Kalman-filtering assisted channel predictors are investigated in the context of narrowband channels. Then, for wideband channel, two-dimensional (2D) channel estimation and prediction was considered, which was capable of predicting both the frequency-domain (FD) and time-domain (TD) fluctuation of wideband channels.
An eigenmode transmission based single-user multiple input multiple output (MIMO) system was also investigated, which requires the computation of the singular vectors. These can be determined from the singular value decomposition (SVD) of the channel’s impulse response (CIR) matrix, which has to be carried out at the regular instants and hence imposes a high computational complexity. However, instead of the periodic estimation of the CIR matrix and its regular SVD, it is possible to directly track the output of the SVD, namely the singular vectors without performing the above-mentioned channel estimation and SVD.
As far as MIMO aided multi-user systems are concerned, both zero-forcing and MMSE BS pre-processing techniques were investigated, which aim for simplifying the design of the mobile station’s (MS) receiver. Again, channel prediction was invoked for acquiring the CSI required for transmit preprocessing.
Furthermore, a SVD based transmit preprocessing algorithm was proposed for both uplink (UL) and downlink (DL) transmissions in the context of a MIMO system supporting multiple users and different power allocation schemes are designed for both UL and DL transmissions Finally, the thesis was concluded with the investigation of recurrent neural network (RNN) based nonlinear channel prediction.
University of Southampton
Liu, Wei
a14d7956-a55e-4e3c-aa61-2d368c7498a1
2007
Liu, Wei
a14d7956-a55e-4e3c-aa61-2d368c7498a1
Liu, Wei
(2007)
Long-range prediction of wireless channels and transmit preprocessing techniques.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
The advanced channel quality-aware adaptive modulation and coding techniques employed in both existing and future wireless communication systems are capable of substantially improving the achievable system performance. Furthermore, other novel techniques employed by the base-station (BS), such as transmit preprocessing, pre-equalization and so on can be used for simplifying the design of the receiver. All these techniques require accurate channel state information (CSI) at the transmitter side, which necessitate the channel prediction.
Both minimum mean square error (MMSE) channel predictors and Kalman-filtering assisted channel predictors are investigated in the context of narrowband channels. Then, for wideband channel, two-dimensional (2D) channel estimation and prediction was considered, which was capable of predicting both the frequency-domain (FD) and time-domain (TD) fluctuation of wideband channels.
An eigenmode transmission based single-user multiple input multiple output (MIMO) system was also investigated, which requires the computation of the singular vectors. These can be determined from the singular value decomposition (SVD) of the channel’s impulse response (CIR) matrix, which has to be carried out at the regular instants and hence imposes a high computational complexity. However, instead of the periodic estimation of the CIR matrix and its regular SVD, it is possible to directly track the output of the SVD, namely the singular vectors without performing the above-mentioned channel estimation and SVD.
As far as MIMO aided multi-user systems are concerned, both zero-forcing and MMSE BS pre-processing techniques were investigated, which aim for simplifying the design of the mobile station’s (MS) receiver. Again, channel prediction was invoked for acquiring the CSI required for transmit preprocessing.
Furthermore, a SVD based transmit preprocessing algorithm was proposed for both uplink (UL) and downlink (DL) transmissions in the context of a MIMO system supporting multiple users and different power allocation schemes are designed for both UL and DL transmissions Finally, the thesis was concluded with the investigation of recurrent neural network (RNN) based nonlinear channel prediction.
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Published date: 2007
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Local EPrints ID: 466337
URI: http://eprints.soton.ac.uk/id/eprint/466337
PURE UUID: 95c9e547-429d-4c21-a7ee-68c9fee33408
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Date deposited: 05 Jul 2022 05:11
Last modified: 16 Mar 2024 20:38
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Author:
Wei Liu
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