In multiple-input multiple-output (MIMO) systems, the use of lattice reduction methods such as the one proposed by Lenstra-Lenstra-Lovasz (LLL) significantly improves the performance of the suboptimal solutions like zero-forcing (ZF) and zero-forcing deceision-feedback-equalizer (ZF-DFE). Today's high rate data communication demands faster lattice reduction methods. Taking advantage of the temporal correlation of a Rayleigh fading channel, a new method is proposed to reduce the complexity of the lattice reduction methods. The proposed method achieves the same error performance as the original lattice reduction methods, but significantly reduces the complexity of lattice reduction algorithm. The proposed method can be used in any MIMO scenario, such as the MIMO detection, and broadcast cases, which are studied in this work.

Although the Multi-Input and Multi-Output (MIMO) communication systems provide very high data rates with low error probabilities, these advantages are obtained at the expense of having high signal processing tasks and the hardware cost, e.g. expensive Analog-to-Digital (A/D) converters. The increased hardware cost is mainly due to having multiple Radio Frequency (RF) chains (one for each antenna element). Antenna selection techniques have been proposed to lower the number of RF chains and provide a low cost MIMO system. Among them, due to a beamforming capability Soft Antenna Selection (SAS) schemes have shown a great performance improvement against the traditional antenna sub-set selection methods for the MIMO communication systems with the same number of RF chains. A SAS method is basically realized by a pre-processing module which is located in RF domain of a MIMO system. In this thesis, we investigate on the receive SAS-MIMO, i.e. a MIMO system equipped with a SAS module at the receiver side, in noise-limited/interference channels. For a noise-limited channel, we study the SAS-MIMO system for when the SAS module is implemented before Low Noise Amplifier (LNA), so-called pre-LNA, under both spatial multiplexing and diversity transmission strategies. The pre-LNA SAS module only consists of passive elements. The optimality of the pre-LNA SAS method is investigated under two di erent practical cases of either the external or internal noise dominates. For the interference channel case, the post-LNA SAS scheme is optimized based on Power Angular Spectrum (PAS) of the received interference signals. The analytical derivations for both noise-limited and interference channels are verified via the computer simulations based on a general Rician statistical MIMO channel model. The simulation results reveal a superiority of the post-LNA SAS to the post-LNA SAS at any condition. Moreover, using the simulations performed for the interference channels we show that the post-LNA SAS is upper bounded by the full-complexity MIMO. Since in both above-mentioned channels, noise-limited and interference, the channel knowledge is needed for the SAS optimization, in this thesis we also propose a two-step channel estimation method for the SAS-MIMO. This channel estimation is based on an Orthogonal Frequency-Division Multiplexing (OFDM) MIMO system. Two di erent estimators of Least-Square (LS) and Minimum-Mean-Square- Error (MMSE) are applied. Simulation results show a superiority of the MMSE method to the LS estimator for a MIMO system simulated under the 802.16 framing strategy. Moreover, a 802.11a framing based SAS-MIMO is simulated using MATLAB SIMULINK to verify the two-step estimation procedure. Furthermore, we also employ a ray-tracing channel simulation to assess di erent SAS configurations, i.e. realized by active (post-LNA) and/or passive (pre-LNA) phased array, in terms of signal coverage. In this regard, a rigorous Signal to Noise Ratio (SNR) analysis is performed for each of these SAS realizations. The results show that although the SAS method performance is generally said to be upperbounded by a full-complexity MIMO, it shows a better signal coverage than the full-complexity MIMO.

Cooperative communication has recently re-emerged as a possible paradigm shift to realize the promises of the ever increasing wireless communication market; how- ever, there have been few, if any, studies to translate theoretical results into feasi- ble schemes with their particular practical challenges. The multiple-input multiple- output (MIMO) technique is another method that has been recently employed in different standards and protocols, often as an optional scenario, to further improve the reliability and data rate of different wireless communication applications. In this work, we look into possible methods and algorithms for combining these two tech- niques to take advantage of the benefits of both. In this thesis, we will consider methods that consider the limitations of practical solutions, which, to the best of our knowledge, are the first time to be considered in this context. We will present complexity reduction techniques for MIMO systems in cooperative systems. Furthermore, we will present architectures for flexible and configurable MIMO detectors. These architectures could support a range of data rates, modulation orders and numbers of antennas, and therefore, are crucial in the different nodes of cooperative systems. The breadth-first search employed in our realization presents a large opportunity to exploit the parallelism of the FPGA in order to achieve high data rates. Algorithmic modifications to address potential sequential bottlenecks in the traditional bread-first search-based SD are highlighted in the thesis. We will present a novel Cooperative Partial Detection (CPD) approach in MIMO relay channels, where instead of applying the conventional full detection in the relay, the relay performs a partial detection and forwards the detected parts of the message to the destination. We will demonstrate how this approach leads to controlling the complexity in the relay and helping it choose how much it is willing to cooperate based on its available resources. We will discuss the complexity implications of this method, and more importantly, present hardware verification and over-the-air experimentation of CPD using the Wireless Open-access Research Platform (WARP). / NSF grants EIA-0321266, CCF-0541363, CNS-0551692, CNS-0619767, EECS-0925942, and CNS-0923479, Nokia, Xilinx, Nokia Siemens Networks, Texas Instruments, and Azimuth Systems.

In multiple-input multiple-output (MIMO) systems, the use of lattice reduction methods such as the one proposed by Lenstra-Lenstra-Lovasz (LLL) significantly improves the performance of the suboptimal solutions like zero-forcing (ZF) and zero-forcing deceision-feedback-equalizer (ZF-DFE). Today's high rate data communication demands faster lattice reduction methods. Taking advantage of the temporal correlation of a Rayleigh fading channel, a new method is proposed to reduce the complexity of the lattice reduction methods. The proposed method achieves the same error performance as the original lattice reduction methods, but significantly reduces the complexity of lattice reduction algorithm. The proposed method can be used in any MIMO scenario, such as the MIMO detection, and broadcast cases, which are studied in this work.

Although the Multi-Input and Multi-Output (MIMO) communication systems provide very high data rates with low error probabilities, these advantages are obtained at the expense of having high signal processing tasks and the hardware cost, e.g. expensive Analog-to-Digital (A/D) converters. The increased hardware cost is mainly due to having multiple Radio Frequency (RF) chains (one for each antenna element). Antenna selection techniques have been proposed to lower the number of RF chains and provide a low cost MIMO system. Among them, due to a beamforming capability Soft Antenna Selection (SAS) schemes have shown a great performance improvement against the traditional antenna sub-set selection methods for the MIMO communication systems with the same number of RF chains. A SAS method is basically realized by a pre-processing module which is located in RF domain of a MIMO system. In this thesis, we investigate on the receive SAS-MIMO, i.e. a MIMO system equipped with a SAS module at the receiver side, in noise-limited/interference channels. For a noise-limited channel, we study the SAS-MIMO system for when the SAS module is implemented before Low Noise Amplifier (LNA), so-called pre-LNA, under both spatial multiplexing and diversity transmission strategies. The pre-LNA SAS module only consists of passive elements. The optimality of the pre-LNA SAS method is investigated under two di erent practical cases of either the external or internal noise dominates. For the interference channel case, the post-LNA SAS scheme is optimized based on Power Angular Spectrum (PAS) of the received interference signals. The analytical derivations for both noise-limited and interference channels are verified via the computer simulations based on a general Rician statistical MIMO channel model. The simulation results reveal a superiority of the post-LNA SAS to the post-LNA SAS at any condition. Moreover, using the simulations performed for the interference channels we show that the post-LNA SAS is upper bounded by the full-complexity MIMO. Since in both above-mentioned channels, noise-limited and interference, the channel knowledge is needed for the SAS optimization, in this thesis we also propose a two-step channel estimation method for the SAS-MIMO. This channel estimation is based on an Orthogonal Frequency-Division Multiplexing (OFDM) MIMO system. Two di erent estimators of Least-Square (LS) and Minimum-Mean-Square- Error (MMSE) are applied. Simulation results show a superiority of the MMSE method to the LS estimator for a MIMO system simulated under the 802.16 framing strategy. Moreover, a 802.11a framing based SAS-MIMO is simulated using MATLAB SIMULINK to verify the two-step estimation procedure. Furthermore, we also employ a ray-tracing channel simulation to assess di erent SAS configurations, i.e. realized by active (post-LNA) and/or passive (pre-LNA) phased array, in terms of signal coverage. In this regard, a rigorous Signal to Noise Ratio (SNR) analysis is performed for each of these SAS realizations. The results show that although the SAS method performance is generally said to be upperbounded by a full-complexity MIMO, it shows a better signal coverage than the full-complexity MIMO.

This dissertation documents alternative designs of the Zero Forcing decoding algorithm with Successive Interference Cancellation (ZF-SIC) for use in Vertical Bell Laboratories Layered Space Time Architecture (V-BLAST) Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems, in an effort to reduce the computational complexity of the receiver. The development of a wireless platform utilizing this architecture intended for use in an indoor wireless multipath environment was created to analyze the multipath environment. This implementation is the result of efforts from several individuals within the CST group. My contributions are documented in this dissertation. In order to obtain channel state information (CSI), a training sequence is sent with each incoming frame. A pseudo-inverse operation is performed on the channel matrix and applied to each OFDM symbol that was received. Performing this operation on each tone and across each OFDM symbol is computationally inefficient in a MIMO configuration. If the number of pseudo-inverses can be reduced while maintaining acceptable levels of bit error, the processing time of each frame can be decreased. Traditionally, tests of the performance of ZF-SIC have been conducted with simulations modelling a multipath channel. In this thesis, CSI is observed using an open loop platform developed for MIMO-OFDM communications. The rate of change of the channel is observed for different multipath environments. The proposed methods of decoding require modifications to ZF-SIC. The suggested changes are only applicable to a MIMO OFDM based method of data transmission. The most effective method of reducing decoding complexity and maintaining an acceptable number of bit errors was observed to occur in the time domain rather than in the frequency domain. For selecting frames and averaging frames in the time domain it was determined that the optimal number of OFDM symbols per frame is 1932 and 174, respectively.

The objective of the proposed research is to devise high-performance and low-complexity signal-detection algorithms for communication systems over fading channels. They include channel equalization to combat intersymbol interference (ISI) and multiple input multiple output (MIMO) signal detection to deal with multiple access interference (MAI) from other transmit antennas. As the demand for higher data-rate and more efficiency wireless communications increases, signal detection becomes more challenging. We propose novel transmission and iterative signal-detection techniques based on energy spreading transform (EST). Different from the existing iterative methods based on the turbo principle, the proposed schemes are independent of channel coding. EST is an orthonormal that spreads a symbol energy over the symbol block in time and frequency for channel equalization; space and time for MIMO signal detection with flat fading channels; and space, time, and frequency for MIMO signal detection with frequency-selective fading channels. Due to the spreading, EST obtains diversity in the available domains for the specific application and increases the reliability of the feedback signal. Moreover, it enables iterative signal detection that has near interference-free performance only at the complexity of linear detectors. Either a hard or soft decision can be fed back to the interference-cancellation stage at the subsequent iteration. The soft-decision scheme prevents error propagation of the hard-decision scheme for a low SNR and improves the performance. We analyze the performance of the proposed techniques. Analytical and simulation results show that these schemes perform very close to the interference-free systems.

The primary objective of this thesis is to design advanced interference resilient schemes for asynchronous slow frequency hopping wireless personal area networks (FH-WPAN) and time division multiple access (TDMA) cellular systems in interference dominant environments. We also propose an interference-resilient power allocation method for multiple-input-multiple-output (MIMO) systems. For asynchronous FH-WPANs in the presence of frequent packet collisions, we propose a single antenna interference canceling dual decision feedback (IC-DDF) receiver based on joint maximum likelihood (ML) detection and recursive least squares (RLS) channel estimation. For the system level performance evaluation, we propose a novel geometric method that combines bit error rate (BER) and the spatial distribution of the traffic load of CCI for the computation of packet error rate (PER). We also derived the probabilities of packet collision in multiple asynchronous FH-WPANs with uniform and nonuniform traffic patterns. For the design of TDMA receivers resilient to CCI in frequency selective channels, we propose a soft output joint detection interference rejection combining delayed decision feedback sequence estimation (JD IRC-DDFSE) scheme. In the proposed scheme, IRC suppresses the CCI, while DDFSE equalizes ISI with reduced complexity. Also, the soft outputs are generated from IRC-DDFSE decision metric to improve the performance of iterative or non-iterative type soft-input outer code decoders. For the design of interference resilient power allocation scheme in MIMO systems, we investigate an adaptive power allocation method using subset antenna transmission (SAT) techniques. Motivated by the observation of capacity imbalance among the multiple parallel sub-channels, the SAT method achieves high spectral efficiency by allocating power on a selected transmit antenna subset. For 4 x 4 V-BLAST MIMO systems, the proposed scheme with SAT showed analogous results. Adaptive modulation schemes combined with the proposed method increase the capacity gains. From a feasibility viewpoint, the proposed method is a practical solution to CCI-limited MIMO systems since it does not require the channel state information (CSI) of CCI.

The objective of this dissertation is to design new architectures for multiple antenna wireless communication systems operating in a mobile-to-mobile environment and to develop a theoretical framework according to which these systems can be analyzed. Recent information theory has demonstrated that the wireless channel can support enormous capacity if the multipath is properly exploited by using multiple antennas. Future communication systems will likely evolve into a variety of combinations encompassing mobile-to-mobile and mobile-to-fixed-station communications. Therefore, we explore the use of multiple antennas for mobile-to-mobile communications. Based on the characteristics of mobile-to-mobile radio channels, we propose new architectures that deploy directional antennas for multiple antenna systems operating in a mobile-to-mobile environment. The first architecture consists of multiple input and multiple output (MIMO) systems with directional antennas, which have good spatial correlation properties, and provides higher capacities than conventional systems without requiring a rich scattering environment. The second one consists of single input and multiple output (SIMO) systems with directional antennas, which improve signal-to-interference-plus-noise ratio (SINR) over conventional systems. We also propose a new combining scheme to select the outputs of optimal combing (SOOC) in this architecture. Optimal combining (OC) is the key technique for multiple antenna systems to suppress interference and mitigate the fading effects. Based on the complex random matrix theory, we develop an analytical framework for the performance analysis of OC. We derive several important closed-form solutions such as the moment generating function (MGF) and the joint eigenvalue distributions of SINR with arbitrary-power interferers and thermal noise. We also analyze the effects of spatial correlations on MIMO OC systems with arbitrary-power interferers in an interference environment. Our novel multiple antenna architectures and the theoretical framework according to which they can be analyzed would provide other researchers with useful tools to analyze and develop future MIMO systems.

The traditional mobile radio channel has always suffered from the detrimental effects of multipath fading. The use of multiple antennae at both ends of the wireless channel has proven to be very effective in combatting fading and enhancing the channel's spectral efficiency. To exploit the benefits offered by Multi-Input Multi-Output (MIMO) systems, both the transmitter and the receiver have to be optimally designed. In this thesis, we are concerned with the problem of receiver design for MIMO systems in a spatial multiplexing scheme. The MIMO detection problem is an NP-hard combinatorial optimization problem. Solving this problem to optimality requires an exponential search over the space of all possible transmitted symbols in order to find the closest point in a Euclidean sense to the received symbols; a procedure that is infeasible for large systems. We introduce a new heuristic algorithm for the detection of a MIMO wireless system based on the Ant Colony Optimization (ACO) metaheuristic. The new algorithm, AntMIMO, has a simple architecture and achieves near maximum likelihood performance in polynomial time.