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Closed-loop multiple antenna aided wireless communications using limited feedback

Yang, Du (2010) Closed-loop multiple antenna aided wireless communications using limited feedback University of Southampton, School of Electronics and Computer Science, Doctoral Thesis , 191pp.

Record type: Thesis (Doctoral)

Abstract

The aim of this thesis is to study the design of closed-loop multiple antenna aided wireless communications relying on limited feedback. Multiple antennas may be employed either/both at the transmitter or/and at the receiver, here the latter periodically feeds back some information about the time-varying wireless channel using a limited number of bits. Furthermore, the transmitter then pre-processes the signals to be transmitted according to the received feedback information. This closed-loop multiple antenna
aided communication scheme is capable of significantly improving the attainable system performance in terms of increasing the transmission rate or enhancing the transmission integrity.

The goal of our research is the efficient acquisition and exploitation of the Channel State Information at the Transmitter (CSIT), with the aid of different transmit preprocessing algorithms. The transmission schemes investigated in this thesis include the Transmit Matched Filter (TxMF), the Transmit Eigen-Beamformer (TxEBF), the linear Multi-User Transmitter (MUT) and a recently proposed MIMO scheme called Spatial Modulation (SM).

The entire process of CSIT acquisition is investigated in this thesis, which includes pilot assisted CSI estimation, CSI quantisation at the receiver, as well as CSI reconstruction at the transmitter. A number of novel designs are proposed in order to increase the CSI acquisition efficiency. A range of different CSI quantisers are detailed in Chapter 2, and their performances are evaluated throughout Chapter 3 to Chapter 6. Moreover, a pilot overhead reduction scheme is proposed for pilot assisted CSI estimation in Chapter 3 for rapidly fading channels. A pilot symbol assisted rateless code is also proposed in Chapter 3, which exploits the available pilot symbols not only for channel estimation but also for channel
decoding. Furthermore, an Extrinsic Information Transfer (EXIT) Chart optimised Channel Impulse Response (CIR) Quantizer is proposed in Chapter 5, which assists the system in maintaining the lowest possible CSI feedback overhead, while ensuring that an open EXIT-tunnel is still attainable for the sake of achieving an infinitesimally low BER. A soft decoding assisted MIMO CIR recovery scheme is proposed in Chapter 5, which minimises the CIRs’ reconstruction error at the transmitter for noise contaminated feedback. Last but not least, a CSI feedback scheme using channel prediction and predictive vector
quantization is also proposed in Chapter 5 for delayed feedback channels.

Given feedback CSIT, a number of algorithms are proposed in order to efficiently exploit it. In Chapter 4 a novel Linear Dispersion Code (LDC) aided TxEBF scheme is proposed, which is capable of striking the required trade-off between the maximum attainable diversity gain and the capacity for an arbitrary number of transmit and receive antennas. In the same chapter, an application example using a novel scheme referred to as a TxEBF aided video transmission scheme is proposed, where the encoded video source bits are transmitted through different eigen-beams according to their error sensitivity, so as to improve the decoded video quality at the receiver by employing unequal error protection. Moreover, a feedback-aided phase rotation and a feedback-aided power allocation scheme are proposed in Chapter 6,which achieves beneficial transmit diversity and enhances the robustness of a SM aided MIMO system.

By examining the various schemes investigated throughout Chapter 3 to Chapter 6, our five-step guidelines conceived for the design of closed-loop MIMO systems using limited feedback are summarised as follows. The first step is to design appropriate transmit preprocessing schemes under the
assumption of having perfect CSIT. Then, the second step is to determine the specific type of the required feedback information, whose entropy has to be as low as possible. Next we design an efficient quantiser based on the statistical properties of the required feedback information. The distortion metric of the quantiser may be the conventional MSE metric, but the employment of a direct data-link-performance related metric is preferable. Moreover, the fourth step is to improve the efficiency and robustness of the quantiser by employing conventional source compression. Finally, the fifth step is the joint optimisation of the data transmission link and the CSI feedback link based on the ultimate target performance metric.

This thesis is concentrated on a Frequency Division Duplex (FDD) cellular communication scenario using digitalized feedback information, where theMobile Terminals (MTs) estimate the Down-Link (DL) channel, quantise and feed back the required information to the Base Station (BS) using a bandwidth-limited feedback link, and the BS reconstructs the received CSI feedback information for the sake of
throughput or integrity improving the DL transmission. Moreover, the wireless channels are assumed to be slow frequency-flat/narrow-band Rayleigh fading channels. They are mostly assumed to be spatially independent. The scenario of having spatial correlation and Line Of Sight (LOS) transmissions are also considered. Furthermore, both the achievable capacity and the BER performance are evaluated. Iterative decoding is employed in conjunction with channel coding in order to approach the achievable capacity and improve the BER performance.

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More information

Published date: 16 August 2010
Organisations: University of Southampton

Identifiers

Local EPrints ID: 162675
URI: http://eprints.soton.ac.uk/id/eprint/162675
PURE UUID: 38d6a58a-6af9-496d-b926-44712be5aae3
ORCID for Lieliang Yang: ORCID iD orcid.org/0000-0002-2032-9327

Catalogue record

Date deposited: 13 Sep 2010 15:59
Last modified: 18 Jul 2017 12:31

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Contributors

Author: Du Yang
Thesis advisor: Lajos Hanzo
Thesis advisor: Lieliang Yang ORCID iD

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