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

International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California / The analysis of multiple-input multiple-output (MIMO) communication systems often assumes a static, or quasi-static, environment. Platform motion and changes in the environment makes this an unreasonable assumption for many telemetry applications. This paper uses computer simulations to characterize the time variation of MIMO channel parameters when there is relative motion between the transmitter and receiver. These simulation results yield explicit time intervals over which a MIMO channel can be considered static for a given relative velocity and propagation environment. These results can be used to predict the practical limitations of proposed MIMO system algorithms.

International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California / Multiple-input multiple-output (MIMO) communication systems are attracting attention because their channel capacity can exceed single-input single-output systems, with no increase in bandwidth. While MIMO systems offer substantial capacity improvements, it can be challenging to characterize and verify their channel models. This paper describes a software MIMO channel simulator with a graphical user interface that allows the user to easily investigate a number of MIMO channel characteristics for a channel recently proposed by the 3rd Generation Partnership Project (3GPP).

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / To correctly demodulate a signal sent through a multiple-input multiple-output (MIMO) channel, a receiver may use training to learn the channel parameters. The choice of training parameters can significantly impact system performance. Training too often yields low throughput while training infrequently produces poor channel estimates and increased transmission errors. Previous work on optimal training parameters has focused on the block fading Rayleigh model. This work examines a more general case; finding the training parameters that maximize throughput for a continuously varying channel. Training parameters that maximize a lower bound on channel capacity are determined via simulation, and general guidelines are presented for selecting optimal training parameters.

ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / This paper addresses the air-to-ground communication problem, where multiple transmit antennas are used on the aircraft to combat multi-path interference. The channel is assumed to have a line-of-sight component and a single ground reflection. Multiple input multiple output (MIMO) techniques can be used in this situation, to increase the reliability and data rate. In this paper we discuss how the MIMO channel capacity changes, with the aircraft antenna configuration, altitude, velocity, range, and a number of other parameters. For comparison, the MIMO results are compared to systems which have single antennas at the transmitter, at the receiver, or at both ends.

This thesis studies some fundamental aspects of wireless systems with partial channel state information at the transmitter (CSIT), with a special emphasis on the high signal-to-noise ratio (SNR) regime. The first contribution is a study on multi-layer variable-rate communication systems with quantized feedback, where the expected rate is chosen as the performance measure. Iterative algorithms exploiting results in the literature of parallel broadcast channels are developed to design the system parameters. Necessary and sufficient conditions for single-layer coding to be optimal are derived. In contrast to the ergodic case, it is shown that a few bits of feedback information can improve the expected rate dramatically. The next part of the thesis is devoted to characterizing the tradeoff between diversity and multiplexing gains (D-M tradeoff) over slow fading channels with partial CSIT. In the multiple-input multiple-output (MIMO) case, we introduce the concept of minimum guaranteed multiplexing gain in the forward link and show that it influences the D-M tradeoff significantly. It is demonstrated that power control based on the feedback is instrumental in achieving the D-M tradeoff, and that rate adaptation is important in obtaining a high diversity gain even at high rates. Extending the D-M tradeoff analysis to decode-and-forward relay channels with quantized channel state feedback, we consider several different scenarios. In the relay-to-source feedback case, it is found that using just one bit of feedback to control the source transmit power is sufficient to achieve the multiantenna upper bound in a range of multiplexing gains. In the destination-to-source-and-relay feedback scenario, if the source-relay channel gain is unknown to the feedback quantizer at the destination, the diversity gain only grows linearly in the number of feedback levels, in sharp contrast to an exponential growth for MIMO channels. We also consider the achievable D-M tradeoff of a relay network with the compress-and-forward protocol when the relay is constrained to make use of standard source coding. Under a short-term power constraint at the relay, using source coding without side information results in a significant loss in terms of the D-M tradeoff. For a range of multiplexing gains, this loss can be fully compensated for by using power control at the relay. The final part of the thesis deals with the transmission of an analog Gaussian source over quasi-static fading channels with limited CSIT, taking the SNR exponent of the end-to-end average distortion as performance measure. Building upon results from the D-M tradeoff analysis, we develop novel upper bounds on the distortion exponents achieved with partial CSIT. We show that in order to achieve the optimal scaling, the CSIT feedback resolution must grow logarithmically with the bandwidth ratio for MIMO channels. The achievable distortion exponent of some hybrid schemes with heavily quantized feedback is also derived. As for the half-duplex fading relay channel, combining a simple feedback scheme with separate source and channel coding outperforms the best known no-feedback strategies even with only a few bits of feedback information. / QC 20100817

Space-time codes (STC) are a class of signaling techniques, offering coding and diversity gains along with improved spectral efficiency. These codes exploit both the spatial and the temporal diversity of the wireless link by combining the design of the error correction code, modulation scheme and array processing. STC are well suited for improving the downlink performance, which is the bottleneck in asymmetric applications such as downstream Internet. Three original contributions to the area of STC are presented in this dissertation. First, the development of analytic tools that determine the fundamental limits on the performance of STC in a variety of channel conditions. For trellis-type STC, transfer function based techniques are applied to derive performance bounds over Rayleigh, Rician and correlated fading environments. For block-type STC, an analytic framework that supports various complex orthogonal designs with arbitrary signal cardinalities and array configurations is developed. In the second part of the dissertation, the Virginia Tech Space-Time Advanced Radio (VT-STAR) is designed, introducing a multi-antenna hardware laboratory test bed, which facilitates characterization of the multiple-input multiple-output (MIMO) channel and validation of various space-time approaches. In the third part of the dissertation, two novel space-time architectures paired with iterative processing principles are proposed. The first extends the suitability of STC to outdoor wireless communications by employing iterative equalization/decoding for time dispersive channels and the second employs iterative interference cancellation/decoding to solve the error propagation problem of Bell-Labs Layered Space-Time Architecture (BLAST). Results show that remarkable energy and spectral efficiencies are achievable by combining concepts drawn from space-time coding, multiuser detection, array processing and iterative decoding. / Ph. D.

Wireless systems are rapidly developing to provide high speed voice, text and multimedia messaging services which were traditionally offered by wire line networks. To support these services, channels with large capacities are required. Information theoretic investigations have shown that Multiple Input Multiple Output (MIMO) channels can achieve very high capacities. Space-Time Block Coding (STBC) and Bell Labs Layered Space-Time Architecture (BLAST) are two potential schemes which utilize the diversity offered by MIMO channels to provide reliable high date rate wireless communication. This work studies the sensitivity of these two schemes to spatial correlation in MIMO channels. The first part of the thesis studies the effect of spatial correlation on the performance of STBC by using Geometrically Based Single Bounce MIMO (GBSB-MIMO) channel models. Performance is analyzed for two scenarios: one without scatterers in the vicinity of the transmitter and other with scatterers. In the second part of the thesis, the sensitivity of BLAST to spatial correlation is analyzed. Later, schemes which use the principles of Multilayered Space-Time Coded Modulation to combine the benefits of BLAST and STBC are introduced and their performance is investigated in correlated and uncorrelated Rayleigh fading. Results indicate that schemes using orthogonal design space-time block codes are reasonably robust to spatial correlation while schemes like BLAST are very sensitive as they depend on array processing to separate signals from various transmit antennas. / Master of Science

Multi-antenna communication systems are attracting research interest as a means to increase the information capacity, reliability, and spectral efficiency of wireless information transfer. Ray-tracing methods predict the behavior of wireless channels using a model of the propagation environment and are a low-cost alternative to direct measurements. We use ray tracing simulations to validate the statistical time and angle of arrival characteristics of an indoor multipath channel and compare model parameter estimates with estimates derived from channel sounding measurements. Ray tracing predicts the time and angle clustering of multipaths observed in the measurements and provides model parameter estimates which are closely correlated with measured estimates. The ray tracing parameters relating to power characteristics show more deviation from measurements than the time and angle related parameters. Our results also indicate that the description of reflective scatterers in the propagation environment is more important to the quality of the predicted statistical behavior than the description of bulk materials. We use a ray synthesis model to investigate means of efficiently representing the channel for feedback information to the transmitter as a means to increase the information capacity. Several methods of selecting the ray-model feedback information are demonstrated with results from simulated and measured channels. These results indicate that an ESPRIT algorithm coupled with ad hoc transmit/receive pairing can yield better than 90% of the ideal waterfilling capacity when adequate training-based channel estimates are available. Additionally, we investigate a covariance feedback method for providing channel feedback for increased capacity. Both the ray-based and covariance-based feedback methods yield their highest capacity improvements when the signal to noise ratio is low. This results because of the larger benefit of focusing transmit power into the most advantageous eigenmodes of the channel when fewer eigenmodes have power allocated to them by the waterfilling capacity solution. In higher signal to noise ratio cases, more eigenmodes of the channel receive power when waterfilling, and the capacity improvement from feedback information decreases relative to a uniform power allocation. In general, ray model feedback methods are preferable because the covariance feedback quickly requires higher computational effort as the array sizes increase and typically results in lower capacity for a given amount of feedback information.

This research investigates techniques for iterative channel estimation to maximize channel capacity and communication security. The contributions of this dissertation are as follows: i) An accurate, low-complexity approach to pilot-assisted fast-fading channel estimation for single-carrier modulation with a turbo equalizer and a decoder is proposed. The channel is estimated using a Kalman filter (KF) followed by a zero-phase filter (ZPF) as a smoother. The combination of the ZPF with the KF of the channel estimator makes it possible to reduce the estimation error to near the Wiener bound. ii) A new semi-blind channel estimation technique is introduced for multiple-input-multiple-output channels. Once the channel is estimated using a few pilots, a low-order KF is employed to progressively predict the channel gains for the upcoming blocks. iii) The capacity of radio channels is investigated when iterative channel estimation, data detection, and decoding are employed. By taking the uncertainty in decoded data bits into account, the channel Linear Minimum Mean Square Error (LMMSE) estimator of an iterative receiver with a given pilot ratio is obtained. The derived error value is then used to derive a bound on capacity. It is shown that in slow fading channels, iterative processing provides only a marginal advantage over non-iterative approach to channel estimation. Knowing the capacity gain from iterative processing versus purely pilot-based channel estimation helps a designer to compare the performance of an iterative receiver against a non-iterative one and select the best balance between performance and cost. iv) A Radio channel is characterized by random parameters which can be used to generate shared secret keys by the communicating parties when the channel is estimated. This research studies upper bounds on the rate of the secret keys extractable from iteratively estimated channels. Various realistic scenarios are considered where the transmission is half-duplex and/or the channel is sampled under the Nyquist rate. The effect of channel sampling interval, fading rate and noise on the key rate is demonstrated. The results of this research can be beneficial for the design and analysis of reliable and secure mobile wireless systems. / Graduate / 0544