Ke, Bingwen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 52-54). / Abstracts in Chinese and English. / Abstract --- p.3 / Acknowledgement --- p.5 / Content --- p.6 / Table of Figures --- p.8 / Chapter Chapter 1 --- Introduction --- p.9 / Chapter 1.1 --- Motivations and Contributions --- p.9 / Chapter 1.2 --- Organization of the Thesis --- p.11 / Chapter Chapter 2 --- Background --- p.12 / Chapter 2.1 --- Multiple-Input-Multiple-Output (MIMO) System --- p.12 / Chapter 2.1.1 --- Basic MIMO Structure --- p.12 / Chapter 2.1.2 --- Multiple User Detection (MUD) in MIMO Networks --- p.14 / Chapter 2.2 --- IEEE 802.11 --- p.16 / Chapter 2.2.1 --- CSMA/CA in 802.11 --- p.16 / Chapter 2.2.2 --- CSMA/CA(k) in 802.1 In --- p.18 / Chapter 2.2.3 --- Co-channel Transmission in MIMO WLAN --- p.19 / Chapter Chapter 3 --- Channel Correlation in MIMO Ad Hoc Networks --- p.20 / Chapter 3.1 --- Introduction of Channel Correlation --- p.20 / Chapter 3.2 --- Channel Correlation Threshold --- p.25 / Chapter Chapter 4 --- MAC with SINR Threshold --- p.28 / Chapter Chapter 5 --- Performance Evaluation of MWST in Fully-Connected Networks --- p.33 / Chapter Chapter 6 --- MAC with SINR Threshold (MWST) in Partially-Connected Networks --- p.38 / Chapter 6.1 --- Hidden Link Problem in Partially-Connected Networks --- p.38 / Chapter Chapter 7 --- Performance Evaluation in Partially-Connected Networks --- p.42 / Chapter 7.1 --- Fairness Issues in CSMA/CA(k) --- p.42 / Chapter 7.2 --- Fairness Performance of MWST --- p.45 / Conclusion --- p.50 / References --- p.52

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Multiple-input multiple-output (MIMO) wireless technology is an emerging cost- effective approach to offer multiple-fold capacity improvement relative to the conven- tional single-antenna systems. To achieve the capacities of MIMO channels, MIMO bit-interleaved-coded-modulation (BICM) systems with iterative detection and decod- ing (IDD) are studied in this thesis. The research for this dissertation is conducted based on the iterative receivers with convolutional codes and turbo codes. A variety of MIMO detectors, such as a maximum a posteriori probability (MAP) detector, a list sphere detector (LSD) and a parallel interference canceller (PIC) together with a decision statistic combiner (DSC), are studied. The performance of these iterative receivers is investigated via bounding techniques or Monte-Carlos simulations. Moreover, the computational complexities of the components are quantified and compared. The convergence behaviors of the iterative receivers are analyzed via variance trans- fer (VTR) functions and variance exchange graphs (VEGs). The analysis of conver- gence behavior facilitates the finding of components with good matching. For a fast fading channel, we show that the &quotwaterfall region&quot of an iterative receiver can be predicted by VEG. For a slow fading channel, it is shown that the performance of an iterative receiver is essentially limited by the early interception ratio (ECR) which is obtained via simulations. After the transfer properties of the detectors are unveiled, a detection switching (DSW) methodology is proposed and the switching criterion based on cross entropy (CE) is derived. By employing DSW, the performance of an iterative receiver with a list sphere detector (LSD) of a small list size is considerably improved. It is shown that the iterative receiver achieves a performance very close to that with a maximum a posteriori probability (MAP) detector but with a significantly reduced complexity. For an iterative receiver with more than two components, various iteration sched- ules are explored. The schedules are applied in an iterative receiver with PIC-DSC. It is shown that the iterative receiver with a periodic scheduling outperforms that with the conventional scheduling at the same level of complexity.

Multiple-Input Multiple-Output (MIMO) communications systems using multiantenna arrays simultaneously during transmission and reception have generated significant interest in recent years. Theoretical work in the mid 1990?s showed the potential for significant capacity increases in wireless channels via spatial multiplexing with sparse antenna arrays and rich scattering environments. However, in reality the capacity is significantly reduced when the antennas are placed close together, or the scattering environment is sparse, causing the signals received by different antennas to become correlated, corresponding to a reduction of the effective number of sub-channels between transmit and receive antennas. By introducing the previously ignored spatial aspects, namely the antenna array geometry and the scattering environment, into a novel channel model new bounds and fundamental limitations to MIMO capacity are derived for spatially constrained, or spatially selective, channels. A theoretically derived capacity saturation point is shown to exist for spatially selective MIMO channels, at which there is no capacity growth with increasing numbers of antennas. Furthermore, it is shown that this saturation point is dependent on the shape, size and orientation of the spatial volumes containing the antenna arrays along with the properties of the scattering environment. This result leads to the definition of an intrinsic capacity between separate spatial volumes in a continuous scattering environment, which is an upper limit to communication between the volumes that can not be increased with increasing numbers of antennas within. It is shown that there exists a fundamental limit to the information theoretic capacity between two continuous volumes in space, where using antenna arrays is simply one choice of implementation of a more general spatial signal processing underlying all wireless communication systems.

Thesis (Ph. D.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2006. / Includes bibliographical references (p. 97-101).

Thesis (Ph.D.)--McMaster University, 2006. / Supervisor: Timothy N. Davidson. Includes bibliographical references (p. 163-172).

Thesis (Ph.D.)--University of Delaware, 2007. / Principal faculty advisor: Leonard J. Cimini, Jr., Electrical and Computer Engineering. Includes bibliographical references.

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

We consider the uplink of a multicell multiuser single-input multiple-output system where the channel experiences both small and large-scale fading. The data detection is done by using the linear zero-forcing technique, assuming the base station (BS) has perfect channel state information of all users in its cell. We derive  new, exact analytical expressions for the uplink rate, symbol error rate, and outage probability per user, as well as alower bound on the achievable rate. This bound is very tight and becomes exact in the large-number-of-antennas limit. We further study the asymptotic system performance in the regimes of high signal-to-noise ratio (SNR), large number of antennas, and large number of users per cell. We show that at high SNRs, the system is interference-limited and hence, we cannot improve the system performance by increasing the transmit power of each user. Instead, by increasing the number of BS antennas, the effects of interference and noise can be reduced, thereby improving the system performance. We demonstrate that, with very large antenna arrays at the BS, the transmit power of each user can be made inversely proportional to the number of BS antennas while maintaining a desired quality-of-service. Numerical results are presented to verify our analysis.

Multiple-Input Multiple-Output (MIMO) systems are viewed as the last available supply for the ever-growing demand on higher data rates in modern wireless communication systems. Smart exploitation of the traditional wireless resources (time-slots or bandwidth under the same transmit power level) has reached its saturation point. By making better use of the free space between the radio links, based on the multipath radio wave propagation, MIMO systems have shown significant capacity improvement with the same traditional wireless resources. In this multi-disciplinary research, we are exploring the link between the electromagnetic propagation and the information theory. Unlike the majority of recent research work, we model the propagation channel matrix between the transmit/receive elements in a deterministic manner under the Maxwellian framework. Having included the environment properties and the characteristics of the radiating elements, the deterministic approach provides a realistic assessment of the MIMO system performance in specific scenarios. The problem addressed in this research is the evaluation of the multi-antenna systems degrees of freedom (DOF) by employing all the available electromagnetic diversity resources (spatial, pattern and polarization). Based on a developed well-defined power independent dimensionality (PID) metric, we start by investigating the information-bearing potential of the collocated multi-polarization MIMO system. We study the hexapole system (exploiting both electric and magnetic fields in conveying independent information) and compare it to the tripole systems (exploiting the vectorial polarization diversity of one field only). We present numerical results for 3 deterministic scenarios: a canonical free-space (near and far field exact solution), a canonical perfect electric conductor (PEC) corridor using rigorous modal analysis, and a lossy-wall corridor using image ray tracing (IRT). Next, we provide deterministic results for the more interesting sampling problem of the electromagnetic vector fields: given a specific MIMO array size, what is the optimum number of packed multi-polarization antennas (i.e. multi-polarization 1D, 2D or 3D sampling) that yields the largest PID for a given environment and what is the estimate of this PID? Using a canonical case of multi-polarized arrays inside a multipath-rich PEC corridor, we show that the spatial frequency spectrum of the electromagnetic field governs the optimum PID of the site-specific scenario. The problem is analogous to the DOF determination of an essentially time-limited-band-limited 1D scalar function using the framework of the prolate spheroidal wave functions. We also present simulation results for the same sampling problem in a lossy-wall indoor environment using IRT.