Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2004. / Includes bibliographical references (p. 53-54).

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2004. / Thesis advisor(s): Frank Kragh. Includes bibliographical references (p. 93-94). Also available online.

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The shortage of radio spectrum has become the bottleneck of achieving broadband wire-less access. Overcoming this bottleneck in next-generation wireless networks hinges on successful implementation of multiple-input-multiple-output (MIMO) technologies, which use antenna arrays rather than additional bandwidth for multiplying data rates. The most efficient MIMO techniques require channel state information (CSI). In practice, such information is usually inaccurate due to overhead constraints on CSI acquisition as well as mobility and delay. CSI inaccuracy can potentially reduce the performance gains provided by MIMO. This dissertation investigates the impact of CSI inaccuracy on the performance of increasing complex MIMO networks, starting with a point-to-point link, continuing to a multiuser MIMO system, and ending at a mobile ad hoc network. Furthermore, this dissertation contributes algorithms for efficient CSI acquisition, and its integration with beamforming and scheduling in multiuser MIMO, and with interference cancelation in ad hoc networks. First, this dissertation presents a design of a finite-rate CSI feedback link for point-to-point beamforming over a temporally correlated channel. We address various important design issues omitted in prior work, including the feedback delay, protocol, bit rate, and compression in time. System parameters such as the feedback bit rate are derived as functions of channel coherence time based on Markov chain theory. In particular, the capacity gain due to beamforming is proved to decrease with feedback delay at least at an exponential rate, which depends on channel coherence time. This work provides an efficient way of implementing beamforming in practice for increasing transmission range and throughput. Second, several algorithms for multiuser MIMO systems are proposed, including CSI quantization, joint beamforming and scheduling, and distributed feedback scheduling. These algorithms enable spatial multiple access and multiuser diversity in a cellular system under the practical constraint of finite-rate multiuser CSI feedback. Moreover, this dissertation shows analytically that the throughput of the MIMO uplink and downlink using the proposed algorithms scales optimally as the number of users increases. Finally, the transmission capacity of a MIMO ad hoc network is analyzed for the case where spatial interference cancelation is applied at receivers. Most important, this dissertation shows that this MIMO technique contributes significant network capacity gains even if the required CSI is inaccurate. In addition, opportunistic CSI estimation is shown to provide a tradeoff between channel training overhead and CSI accuracy. / text

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This thesis work presents a study on the impact of mutual coupling among antenna arrays on the performance of the multipath simulator (MPS) system. In MIMO systems, it is a wellknown fact that the mutual coupling significantly affects their system performance. The impact of mutual coupling on MIMO system performance is an important consideration for compact antenna arrays. Hence, it is very important to investigate the impact of mutual coupling on the accuracy of measurements in a MPS system. In this project, the impact of coupling within the MPS array antennas is addressed by performing simulations based on the proposed MPS scattering model which fulfills the far-field (Fraunhoferdistance) boundary conditions. The coupling phenomenon within the MPS array antennas is studied by designing a uniform circular array (UCA) of radius,R consisting of NMPS antennas with single device under test (DUT) antenna at the center. The elements of the array are matched half-wave dipole antennas and the phase of the array elements is kept constant throughout. In this work it is assumed that all the elements in the array are identical and located in the far-field region. This study is carried out by performing MPS simulations in HFSS at the LTE-A band of 2.6GHz. The approach used to model the entire system is by comparing the S-parameters (S21: Forward transmission coefficient parameter) between various array configuration. The simulation results suggest that the impact of mutual coupling increases with the number of MPS antennas and decreases with the radius of the MPS ring. Theradiated power is also measured with and without mutual coupling. Finally, it is concluded that the impact of coupling within the MPS antennas is best countered by designing a large MPS system (preferably R = 10λ or greater), despite the higher incurred costs.

Multiple-Input Multiple-Output (MIMO) systems have gained an enormous amount of attention as one of the most promising research areas in wireless communications. However, while MIMO systems have been extensively explored over the past decade, few schemes acknowledge the nonlinearity caused by the use of high power amplifiers (HPAs) in the communication chain. When HPAs operate near their saturation points, nonlinear distortions are introduced in the transmitted signals, and the resulting MIMO channel will be nonlinear. The nonlinear distortion is further exacerbated by the fading caused by the propagation channel. The goal of this thesis is: 1) to use neural networks (NNs) to model and identify nonlinear MIMO channels; and 2) to employ the proposed NN model in designing efficient detection techniques for these types of MIMO channels. In the first part of the thesis, we follow a previous work on modeling and identification of nonlinear MIMO channels, where it has been shown that a proposed block-oriented NN scheme allows not only good identification of the overall MIMO input-output transfer function but also good characterization of each component of the system. The proposed scheme employs an ordinary gradient descent based algorithm to update the NN weights during the learning process and it assumes only real-valued inputs. In this thesis, natural gradient (NG) descent is used for training the NN. Moreover, we derive an improved variation of the previously proposed NN scheme to avoid the input type restriction and allow for complex modulated inputs as well. We also investigate the scheme tracking capabilities of time-varying nonlinear MIMO channels. Simulation results show that NG descent learning significantly outperforms the ordinary gradient descent in terms of convergence speed, mean squared error (MSE) performance, and nonlinearity approximation. Moreover, the NG descent based NN provides better tracking capabilities than the previously proposed NN. The second part of the thesis focuses on signal detection. We propose a receiver that employs the neural network channel estimator (NNCE) proposed in part one, and uses the Zero-Forcing Vertical Bell Laboratories Layered Space-Time (ZF V-BLAST) detection algorithm to retrieve the transmitted signals. Computer simulations show that in slow time-varying environments the performance of our receiver is close to the ideal V-BLAST receiver in which the channel is perfectly known. We also present a NN based linearization technique for HPAs, which takes advantage of the channel information provided by the NNCE. Such linearization technique can be used for adaptive data predistortion at the transmitter side or adaptive nonlinear equalization at the receiver side. Simulation results show that, when higher modulation schemes (>16-QAM) are used, the nonlinear distortion caused by the use of HPAs is greatly minimized by our proposed NN predistorter and the performance of the communication system is significantly improved. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2007-08-08 14:55:50.489

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The demand for high data rate wireless communication systems is evident today as indicated by the rapid growth in wireless subscribers and services. High data rate systems are bandwidth intensive but bandwidth is an expensive and scarce commodity. The ability of future wireless systems to efficiently utilise the available bandwidth is therefore integral to their progress and development. The wireless communications channel is a harsh environment where time varying multipath fading, noise and interference from other users and systems all contribute to the corruption of the received signal. It is difficult to overcome these problems and achieve the high data rates required using single antenna technology. Multiple-input-multipleoutput (MIMO) systems have recently emerged as a promising technique for achieving very large bandwidth efficiencies in wireless channels. Such a system employs multiple antennas at both the transmitter and the receiver. These systems exploit the spatial dimension of the wireless channel to achieve significant gains in terms of capacity and reliability over single antenna systems and consequently achieve high data rates. MIMO systems are currently being considered for 3rd generations cellular systems. The performance of MIMO systems is heavily dependent on the environment in which the system is utilised. For this reason a realistic channel model is essential for understanding the performance of these systems. Recent studies on the capacity of MIMO channels have focused on the effect of spatial correlation but the joint effect of spatial and temporal correlation has not been well studied. The first part of this thesis proposes a new spatially and temporally correlated MIMO channel model which considers motion of the receiver and nonisotropic scattering at both ends of the radio link. The outage capacity of this channel is examined where the effects of antenna spacing, array angle, degree of scattering and receiver motion are investigated. It is shown that the channel capacity still increases linearly with the number of transmit and receive antennas, despite the presence of both spatial and temporal correlation. The capacity of MIMO channels is generally investigated by simulation. Where analytical expressions have been considered for spatially correlated channels, only bounds or approximations have been used. In this thesis closed form analytical expressions are derived for the ergodic capacity of MIMO channels for the cases of spatial correlation at one end and both ends of the radio link. The latter does not lend itself to numerical integration but the former is shown to be accurate by comparison with simulation results. The proposed analysis is also very general as it is based on the transmit and receive antenna correlation matrices. Low-density parity-check (LDPC) codes have recently been rediscovered and have been shown to approach the Shannon limit and even outperform turbo codes for long block lengths. Non-binary LDPC codes have demonstrated improved performance over binary LDPC codes in the AWGN channel. Methods to optimise non-binary LDPC codes have not been well developed where only simulation based approaches have been employed, which are not very efficient. For this reason, a new approach is proposed which is based on extrinsic information transfer (EXIT) charts. It is demonstrated that by performing curve matching on the EXIT chart, good non-binary LDPC codes can be designed for the AWGN channel. In order to approach the theoretical capacity of MIMO channels, many space-time coded, multiple antenna (MA) systems have been considered in the literature. These systems merge channel coding and antenna diversity and exploit the benefits of both. Binary LDPC codes have demonstrated good performance in MA systems but nonbinary LDPC codes have not been considered. Therefore, the application of non-binary LDPC codes to MA systems is investigated where the codes are optimised for the system of interest, using a simulation and EXIT chart based design approach. It is shown that non-binary LDPC codes achieve a small gain in performance over binary LDPC codes in MA systems. / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2005.