In Chapter 1, a discussion of the characteristics of MC modulation techniques is presented. In addition, a review of MIMO signaling techniques, such as spatial multiplexing, is provided. In order to harness the spatial information that is
present in MIMO systems, antenna arrays, instead of multiple antenna elements, are of interest and so, the concept of antenna array signal processing is introduced. In Chapter 2, the concept of the array manifold vector is introduced. The ar- ray manifold vector enables the parametric modelling of the channel parameters. Based on the array manifold vector, space-time channel models are then intro- duced. The various space-time channel models are de…ned based on the structure of the input and output signals. The system architecture of the asynchronous array-based MC-CDMA MIMO systems that are considered in this thesis are then presented. In the receivers, a bank of TDLs is employed so as to equip the receiver with space-time processing capabilities. The system models presented herein provides a framework for the detailed investigations in the subsequent chapters.
The problem of space-time reception and channel estimation for a single user cyclic pre…x-free MC-CDMA arrayed MIMO system is then investigated in Chap- ter 3. A subspace-based receiver is developed based on the proposed system model. The proposed receiver seeks to null the ISI e¤ects in the received signal and it requires the same degree of information as the RAKE receiver. The perfor- mance of the proposed receiver is compared with the RAKE and MMSE and it is demonstrated that the proposed receiver has a similar performance as the MMSE receiver and is superior to the RAKE receiver. In addition, the performance of the cyclic pre…x-free MC-CDMA arrayed MIMO system is compared with an ex- isting MC-CDMA MIMO system (which is non-array based and makes use of cyclic pre…xes) and the proposed cyclic pre…x-free MC-CDMA arrayed MIMO system is shown to have a superior performance than the reference system. This is despite the presence of ISI in the proposed system whereas as the reference system is not susceptible to such e¤ects. Thus, system overheads are reduced without a loss in performance.
In order to obtain the estimates of the channel parameters, the channel esti- mation algorithm is developed based on the concept of the MC-STAR manifold vector. For a speci…c transmitter antenna whose space-time channel parameters are to be estimated, a delay-dependent preprocessor matrix is de…ned for each delay and the preprocessor matrix that is obtained is then used to transform the MC-STAR manifold vectors with the same delay for the speci…c transmitter an- tenna. The preprocessor is designed to null the MC-STAR manifold vectors which do not have the same delay for the transmitter antenna under consideration and these MC-STAR manifold vectors are removed from the signal subspace. At the same time, the MC-STAR manifold vectors arising from the co-channel interfer- ence (CCI), resulting from the remaining transmitter antenna elements, as well as the ISI are transformed by the preprocessor matrix. However, the transformation of the desired MC-STAR manifold vectors is di¤erent from the transformation of the CCI and ISI MC-STAR manifold vectors. The proposed algorithm thus exploits this property and makes use of a MUSIC-type cost function to obtain the estimates of the space-time channel parameters for the desired transmitter antenna. The proposed algorithm is demonstrated to be capable of identifying greater number of coherent multipaths than the number of antenna elements.
In Chapter 4, the point-source channel model for a cyclic pre…x-free MC- CDMA arrayed MIMO system is extended to a di¤used-source channel model which considers the e¤ects of localized scattering. As a result, the point-source MC-STAR manifold vector is extended to the di¤used MC-STAR manifold vector. The di¤used MC-STAR vector manifold is obtained from a …rst order Taylor series approximation of the array manifold vector about the nominal DOA. The di¤used MC-STAR manifold vector that is developed enables the spatially-di¤used mul- tipath channel characteristics to be completely captured in the received signal model. A subspace-based channel estimation algorithm, which also makes use of
the preprocessor matrix developed in Chapter 3, is then developed to obtain the estimates of the DOA, TOA and spatial spread. The proposed algorithm is not limited by the number of antennas and it allows the estimates of the parameters of more multipaths than the number of antenna elements to be obtained. More- over, it is shown that the proposed algorithm can has better performance than an algorithm which ignores the e¤ects of local scattering in the channel.
A decorrelating receiver is then developed for the di¤used channel and it is shown to have much better performance than a receiver which ignores the scattering present in the channel. The superior performance of the proposed receiver is also validated for the uplink of a multi-user cyclic pre…x-free MC- CDMA arrayed MIMO system in which near-far e¤ects are present.
The problem of joint transmitter-receiver beamforming in the downlink of a multi-user cyclic pre…x-free MC-CDMA arrayed MIMO system is next investi- gated in Chapter 5. The work is based on the assumption that channel informa- tion is available at the base station and the optimization objective is to minimize the overall MSE of the system subject to a transmit power constraint. In addi- tion, the link between the transmit power of each transmitter antenna and the PAPR (and consequently, the probability of clipping of the transmitted signal) is used to reduce the PAPR and hence, the probability of clipping, of the transmit- ted signals from each transmit antenna. The optimization problem is solved with the Lagrange Multiplier method and an iterative algorithm for the determination of the transmit and receive beamforming matrices is introduced. This is a result of the inter-dependence between the transmit and receive beamforming matrices. It is shown that the iterative process brings about a much performance than if the transmit and receive beamforming matrices were not optimized. In addition, it is demonstrated that the probability of clipping of the transmitted signal is indeed reduced by the per-antenna transmit power constraint.