published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

In downlink multi-user multiple-input multiple-output (MU-MIMO) systems, different users, even multiple data streams serving one user, might require different quality-of-services (QoS). The transceiver should allocate resources to different users aiming at satisfying their QoS requirements. In order to design the optimal transceiver, channel state information is necessary. In practice, channel state information has to to be estimated, and estimation error is unavoidable. Therefore, robust transceiver design, which takes the channel estimation uncertainty into consideration, is important. For the previous robust transceiver designs, bounded estimation errors or Gaussian estimation errors were assumed. However, if there exists unknown distributed interference, the distribution of the channel estimation error cannot be modeled accurately a priori. Therefore, in this thesis, we investigate the robust transceiver design problem in downlink MU-MIMO system under probabilistic QoS constraints with arbitrary distributed channel estimation error. To tackle the probabilistic QoS constraints under arbitrary distributed channel estimation error, the transceiver design problem is expressed in terms of worst-case probabilistic constraints. Two methods are then proposed to solve the worst-case problem. Firstly, the Chebyshev inequality based method is proposed. After the worst-case probabilistic constraint is approximated by the Chebyshev inequality, an iteration between two convex subproblems is proposed to solve the approximated problem. The convergence of the iterative method is proved, the implementation issues and the computational complexity are discussed. Secondly, in order to solve the worst-case probabilistic constraint more accurately, a novel duality method is proposed. After a series of reformulations based on duality and S-Lemma, the worst-case statistically constrained problem is transformed into a deterministic finite constrained problem, with strong duality guaranteed. The resulting problem is then solved by a convergence-guaranteed iteration between two subproblems. Although one of the subproblems is still nonconvex, it can be solved by a tight semidefinite relaxation (SDR). Simulation results show that, compared to the non-robust method, the QoS requirement is satisfied by both proposed algorithms. Furthermore, among the two proposed methods, the duality method shows a superior performance in transmit power, while the Chebyshev method demonstrates a lower computational complexity. / published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

The increasing demand for high-mobility and high data rate in wireless communications results in constraints and problems in the limited radio spectrum, multipath fading, and delay spread. The multiple-input multiple-output (MIMO) system has been generally considered as one of the key technologies for the next generation wireless communication systems. MIMO systems which utilize multiple antennas in both the transmit side and the receive side can overcome the abovementioned challenges since they are able to increase the channel capacity and the spectrum usage efficiency without the need for additional channel bandwidth. The detection algorithm is a big bottleneck in MIMO systems. Generally, it is expected to fulfill two main goals simultaneously: low computational complexity and good error rate performance. However, the existing detection algorithms are either too complicated or suffering from very bad error-rate performance. The purpose of this thesis is to comprehensively investigate the detection algorithms of MIMO systems, and based on that, to develop new methods which can reduce the computational complexity while retain good system performance. Firstly, the background and the principle of MIMO systems and the previous work on the MIMO decoding algorithms conducted by other researchers are thoroughly reviewed. Secondly, the geometrical analysis of the signal detection is investigated, and a geometric decoding algorithm which can offer the optimum BLER performance is proposed. Thirdly, the semidefinite relaxation (SDR) detection algorithms are extended to high-order modulation MIMO systems, and a novel SDR detector for 256-QAM constellations is proposed. The theoretical analysis on the tightness and the complexity are conducted. It demonstrates that the proposed SDR detector can offer better BLER performance, while its complexity is in between those of its two counterparts. Fourthly, we combine the SDR detection algorithms with the sphere decoding. This is helpful for reducing the computational complexity of the traditional sphere decoding since shorter initial radius of the hyper sphere can be obtained. Finally, the novel lattice-reduction-aided SDR detectors are proposed. They can provide near-optimum error rate performance and achieve the full diversity gain with very little computational complexity added compared with the stand-alone SDR detectors. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA / Spatial modulation (SM) is a transmission scheme where only one transmit antenna is active at any time instant. It thus reduces interchannel interference (ICI) and receiver complexity over traditional multi-antenna systems. However, the spectral efficiency of SM is low. To improve the spectral efficiency, generalized spatial modulation (GSM) can be used. In this paper, we propose to apply the Alamouti technique with GSM for correlated antennas, and show that the proposed approach provides significant improvement over conventional SM and GSM. Our study also shows the importance of bit-to-antenna mappings and their roles on the selection of appropriate correlated antennas.

This thesis first addresses an important topic concerning space structure control systems, namely, attitude stabilization and control, which is followed by a study on subsystem interactions of general Multi Input Multi Output (MIMO) systems for better performance and actuator fault tolerance. A novel and simple output feedback stabilization approach is proposed for a space structure system characterized with kinematics and dynamics. The approach globally, asymptotically stabilizes the plant and the closed-loop stability is proved using Lyapunov analysis. The simplicity and robustness of the designed controller are demonstrated by investigating the closed-loop response after reducing the degree of freedom in control structure. The stability of the closed-loop system is further analyzed and the performance is compared with two other robust control approaches. The study carries on to another space plant, a Large Space Telescope (LST). Its dynamic model which is fitted with reaction wheels initially developed by NASA is analyzed and the fully coupled dynamics are derived by taking into account the nonlinear coupling phenomena and other terms neglected in their original (NASA) form. The dynamics are combined with Quaternion based kinematics to form an intricate yet realistic LST attitude model. The attitude of the nonlinear LST model is stabilized using a state feedback controller and the LST model is shown to track a time varying attitude reference. Structure configuration is an imperative task in the design of MIMO control systems. In order to make use of interactions between multiple channels so that the system can deal with vulnerability due to actuator degradation, a novel interaction measure is proposed. It is defined as Relative Dependency Index (RDI) and is based on H∞ norms. Such a measurement is effective in understanding the influence of the jth input on the ith output of a system. RDI based guidelines are outlined for configuring a system towards coupling/decoupling. RDI is further extended to the Input Impact Index (i.i.i.) which helps in determining how much an actuator degradation would affect the output of a system. The validity of RDI and i.i.i. is illustrated by simulation results and tested on the linearized spacecraft attitude model presented in the former part of the thesis.

Recent theoretical study shows that the sparsest solution to an underdetermined linear system is unique, provided the solution vector is sufficiently sparse, and the operator matrix has sufficiently incoherent column vectors. In addition, efficient algorithms have been discovered to find such solutions. This intriguing result opens a new door for many potential applications. In this thesis, we study the design of a class of greedy algorithms that are extremely efficient, e.g., Orthogonal Matching Pursuit (OMP). These greedy algorithms suffer from a stability issue that the greedy selection approach always make locally optimal decisions, thereby easily biasing and mistaking the solutions in particular under data noise. We propose a solution approach that in designing greedy algorithms, new constraints can be devised by leveraging application-specific insights and incorporated into the algorithms. Given that sparse recovery problems by definition are underdetermined, introducing additional constraints can significantly improve the stability of greedy algorithms, yet retain their efficiency. / Engineering and Applied Sciences

The use of feedback to provide channel state information to the transmitter can greatly improve the performance of a communication system. However, the amount of information required to characterize a time-varying MIMO channel can exceed the capacity of the feedback channel. This paper surveys research in limited feedback systems, which employ a number of methods to reduce the information and improve performance in multi-antenna communication systems. This paper also presents a new method, Quantized Successor Pre-coding (QSP), that exploits time-correlation to implement spatial multiplexing in a MIMO system using very little feedback. QSP uses an ordered codebook of pre-coders and transmission modes to reduce the feedback to a single bit. Simulations of QSP demonstrate a substantial performance improvement relative to open-loop spatial multiplexing. / text

Transmission power control (TPC) has been used in wireless networks to improve channel reuse and/or reduce energy consumption. It has been mainly applied to single-input single-output (SISO) systems. Significant improvement in performancecan be achieved by employing multi-input multi-output (MIMO) techniques. In this dissertation, we propose adaptive medium-access control (MAC) protocols for power-controlled MIMO-capable wireless networks. In these protocols, we adapt the number of transmit/receive antennas, along with the transmission powers/rates, for the purpose of minimizing total energy consumption and/or maximizing network throughput. Our first protocol, called E-BASIC, exploits the diversity gain of MIMO by adapting the transmission mode, transmission power, and modulation order so as to minimize the total energy consumption. We incorporate E-BASIC in the design of an energy-efficient routing (EER) scheme that selects the least-energy end-to-end path. We then propose two MAC protocols that exploit the multiplexing gain of MIMO, and consider their integration into legacy systems. We alsopropose a combined energy/throughput MAC protocol, called CMAC, which dynamically switches between diversity and multiplexing modes so as to maximize a utility function that depends on both energy consumption and throughput. Finally, we consider employing "virtual" MIMO capability into single-antenna wireless sensor networks (WSNs). We propose a distributed MIMO-adaptive energy-efficient clustering/routing protocol, coined CMIMO, which aims at reducing energy consumption in multi-hop WSNs. In CMIMO, each cluster has up to two cluster heads (CHs), which are responsible for routing traffic between clusters. Simulation results indicate that our proposed protocols achieve significant energy/throughput improvement compared with non-adaptive protocols.

Ray tracing based on geometric optics can be utilized for generating propagation models for arbitrary and complex environments. These methods can be employed to determine important wireless channel characteristics such as path gain and the channel impulse response which in turn can be used to deduce channel capacity. In this thesis, a fully vectorial 3-D ray-tracer is developed. The simulator is applied to study novel wireless systems such as ultra-wideband pulse propagation in complex railway tunnels and MIMO systems employing closely spaced low mutual coupling meta-material antennas. The computational complexity of the ray-tracing algorithm is reduced using optimizations and via the development of a novel hybrid method that combines the efficiency and accuracy of waveguide models with the flexibility of a ray-tracer. The resulting simulator is validated against measured results and demonstrated to show good agreement. Convergence of the solution using the ray-tracing method is also discussed.