Masters Research - Master of Engineering / This thesis demonstrates the process of building a system to test multiple-input multiple-output (MIMO) communications over-the-air. It covers the entire process, from concept to design and construction, culminating in transmitting space-time coded data packets and producing bit error rate (BER) performance curves. A flexible modular architecture is designed, able to test current MIMO systems and to be upgraded as the field develops. Printed circuit boards for a field-programmable gate array (FPGA) based mainboard, 2.4 GHz transceivers and antennas are then designed, embodying the aforementioned architecture. The mainboard uses a Xilinx XC2S600E FPGA, with ∼600,000 logic gates. Hardware is assembled and tested, forming a foundation for further layers of firmware and software. An abstraction layer, with associated test benches, is written in a hardware description language (VHDL), allowing the core logic of the FPGA to be written and simulated in a device-independent manner. Further VHDL is written and the testbed configured to transmit and receive bursts of data. A device driver is implemented, and abstract data types are layered on top of the driver, enabling high-level control of the testbed. Single antenna and MIMO data links are implemented using 1x1 binary phase-shift keying (BPSK) and 2x2 Alamouti encoded BPSK modulation respectively. Finally, data packets are transmitted and measured BER performance curves constructed. Channel estimation is proved to work on a 2x2 MIMO channel over-the-air, the introduced loss of Eb/N0 shown to be approximately 0.5 dB compared to perfect channel information. The analogue limitations of the hardware are investigated and bit error rate performance measured as a function of operating point. Finally single antenna communications and a 2x2 Alamouti MIMO scheme are compared over-the-air, the Alamouti scheme delivering a 3 dB improvement in Eb/N0 performance. Satisfyingly the MIMO scheme also exceeds the best case theoretical performance bound of the single antenna case by a margin of 2 dB in Eb/N0.

Visible light communication (VLC) is an emerging form of optical wireless communication that transmits data by modulating light in the visible spectrum. To meet the growing demand for wireless communication capacity from mobile devices, we investigate multiple-input multiple-output (MIMO) VLC to achieve multiplexing capacity gains and to allow multiple users to simultaneously transmit without disrupting each other. Previous approaches to receive VLC signals have either been unable to simultaneously receive multiple independent signals from multiple transmitters, unable to adapt to moving transmitters and receivers, or unable to sample the received signals fast enough for high-speed VLC. In this dissertation, we develop and evaluate two novel approaches to receive high-speed MIMO VLC signals from mobile transmitters that can be practically scaled to support additional transmitters. The first approach, Token-Based Pixel Selection (TBPS) exploits the redundancy and sparsity of high-resolution transmitter images in imaging VLC receivers to greatly increase the rate at which complementary metal-oxide semiconductor (CMOS) active pixel sensor (APS) image sensors can sample VLC signals though improved signal routing to enable such high-resolution image sensors to capture high-speed VLC signals. We further model the CMOS APS pixel as a linear shift-invariant system, investigate how it scales to support additional transmitters and higher resolutions, and investigate how noise can affect its performance. The second approach, a spatial light modulator (SLM)-based VLC receiver, uses an SLM to dynamically control the resulting wireless channel matrix to enable relatively few photodetectors to reliably receive from multiple transmitters despite their movements. As part of our analysis, we develop a MIMO VLC channel capacity model that accounts for the non-negativity and peak-power constraints of VLC systems to evaluate the performance of the SLM VLC receiver and to facilitate the optimization of the channel matrix through the SLM.

abstract: Characterization of standard cells is one of the crucial steps in the IC design. Scaling of CMOS technology has lead to timing un-certainties such as that of cross coupling noise due to interconnect parasitic, skew variation due to voltage jitter and proximity effect of multiple inputs switching (MIS). Due to increased operating frequency and process variation, the probability of MIS occurrence and setup / hold failure within a clock cycle is high. The delay variation due to temporal proximity of MIS is significant for multiple input gates in the standard cell library. The shortest paths are affected by MIS due to the lack of averaging effect. Thus, sensitive designs such as that of SRAM row and column decoder circuits have high probability for MIS impact. The traditional static timing analysis (STA) assumes single input switching (SIS) scenario which is not adequate enough to capture gate delay accurately, as the delay variation due to temporal proximity of the MIS is ~15%-45%. Whereas, considering all possible scenarios of MIS for characterization is computationally intensive with huge data volume. Various modeling techniques are developed for the characterization of MIS effect. Some techniques require coefficient extraction through multiple spice simulation, and do not discuss speed up approach or apply models with complicated algorithms to account for MIS effect. The STA flow accounts for process variation through uncertainty parameter to improve product yield. Some of the MIS delay variability models account for MIS variation through table look up approach, resulting in huge data volume or do not consider propagation of RAT in the design flow. Thus, there is a need for a methodology to model MIS effect with less computational resource, and integration of such effect into design flow without trading off the accuracy. A finite-point based analytical model for MIS effect is proposed for multiple input logic gates and similar approach is extended for setup/hold characterization of sequential elements. Integration of MIS variation into design flow is explored. The proposed methodology is validated using benchmark circuits at 45nm technology node under process variation. Experimental results show significant reduction in runtime and data volume with ~10% error compared to that of SPICE simulation. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

Abstract Advanced multiple-input multiple-output (MIMO) transceiver structures which utilize the knowledge of channel state information (CSI) at the transmitter side to optimize certain link parameters (e.g., throughput, fairness, spectral efficiency, etc.) under different constraints (e.g., maximum transmitted power, minimum quality of services (QoS), etc.) are considered in this thesis. Adaptive transmission schemes for point-to-point MIMO systems are considered first. A robust link adaptation method for time-division duplex systems employing MIMO-OFDM channel eigenmode based transmission is developed. A low complexity bit and power loading algorithm which requires low signaling overhead is proposed. Two algorithms for computing the sum-capacity of MIMO downlink channels with full CSI knowledge are derived. The first one is based on the iterative waterfilling method. The convergence of the algorithm is proved analytically and the computer simulations show that the algorithm converges faster than the earlier variants of sum power constrained iterative waterfilling algorithms. The second algorithm is based on the dual decomposition method. By tracking the instantaneous error in the inner loop, a faster version is developed. The problem of linear transceiver design in MIMO downlink channels is considered for a case when the full CSI of scheduled users only is available at the transmitter. General methods for joint power control and linear transmit and receive beamformers design are provided. The proposed algorithms can handle multiple antennas at the base station and at the mobile terminals with an arbitrary number of data streams per scheduled user. The optimization criteria are fairly general and include sum power minimization under the minimum signal-to-interference-plus-noise ratio (SINR) constraint per data stream, the balancing of SINR values among data streams, minimum SINR maximization, weighted sum-rate maximization, and weighted sum mean square error minimization. Besides the traditional sum power constraint on the transmit beamformers, multiple sum power constraints can be imposed on arbitrary subsets of the transmit antennas.This extends the applicability of the results to novel system architectures, such as cooperative base station transmission using distributed MIMO antennas. By imposing per antenna power constraints, issues related to the linearity of the power amplifiers can be handled as well. The original linear transceiver design problems are decomposed as a series of remarkably simpler optimization problems which can be efficiently solved by using standard convex optimization techniques. The advantage of this approach is that it can be easily extended to accommodate various supplementary constraints such as upper and/or lower bounds for the SINR values and guaranteed QoS for different subsets of users. The ability to handle transceiver optimization problems where a network-centric objective (e.g., aggregate throughput or transmitted power) is optimized subject to user-centric constraints (e.g., minimum QoS requirements) is an important feature which must be supported by future broadband communication systems.

Spatial Modulation (SM) is a Multiple-Input Multiple-Output (MIMO) transmission technique which realizes low complexity implementations in wireless communication systems. Due the transmission principle of SM, only one Radio Frequency (RF) chain is required in the transmitter. Therefore, the complexity of the transmitter is lower compared to the complexity of traditional MIMO schemes, such as Spatial MultipleXing (SMX). In addition, because of the single RF chain configuration of SM, only one Power Amplifier (PA) is required in the transmitter. Hence, SM has the potential to exhibit significant Energy Efficiency (EE) benefits. At the receiver side, due to the SM transmission mechanism, detection is conducted using a low complexity (single stream) Maximum Likelihood (ML) detector. However, despite the use of a single stream detector, SM achieves a multiplexing gain. A point-to-point closed-loop variant of SM is receive space modulation. In receive space modulation, the concept of SMis extended at the receiver side, using linear precoding with Channel State Information at the Transmitter (CSIT). Even though receive space modulation does not preserve the single RF chain configuration of SM, due to the deployed linear precoding, it can be efficiently incorporated in a Space Division Multiple Access (SDMA) or in a Virtual Multiple-Input Multiple-Output (VMIMO) architecture. Inspired by the potentials of SM, the objectives of this thesis are the evaluation of the EE of SM and its extension in different forms of MIMO communication. In particular, a realistic power model for the power consumption of a Base Station (BS) is deployed in order to assess the EE of SM in terms of Mbps/J. By taking into account the whole power supply of a BS and considering a Time Division Multiple Access (TDMA) multiple access scheme, it is shown that SM is significantly more energy efficient compared to the traditional MIMO techniques. In the considered system setup, it is shown that SM is up to 67% more energy efficient compared to the benchmark systems. In addition, the concept of space modulation is researched at the receiver side. Specifically, based on the union bound technique, a framework for the evaluation of the Average Bit Error Probability (ABEP), diversity order, and coding gain of receive space modulation is developed. Because receive space modulation deploys linear precoding with CSIT, two new precoding methods which utilize imperfect CSIT are proposed. Furthermore, in this thesis, receive space modulation is incorporated in the broadcast channel. The derivation of the theoretical ABEP, diversity order, and coding gain of the new broadcast scheme is provided. It is concluded that receive space modulation is able to outperform the corresponding traditional MIMO scheme. Finally, SM, receive space modulation, and relaying are combined in order to form a novel virtual MIMO architecture. It is shown that the new architecture practically eliminates or reduces the problem of the inefficient relaying of the uncoordinated virtual MIMO space modulation architectures. This is undertaken by using precoding in a novel fashion. The evaluation of the new architecture is conducted using simulation and theoretical results.

Researchers have shown that by combining multiple input multiple output (MIMO) techniques with CDMA then higher gains in capacity, reliability and data transmission speed can be attained. But a major drawback of MIMO-CDMA systems is multiple access interference (MAI) which can reduce the capacity and increase the bit error rate (BER), so statistical analysis of MAI becomes a very important factor in the performance analysis of these systems. In this thesis, a detailed analysis of MAI is performed for binary phase-shift keying (BPSK) signals with random signature sequence in Raleigh fading environment and closed from expressions for the probability density function of MAI and MAI with noise are derived. Further, probability of error is derived for the maximum Likelihood receiver. These derivations are verified through simulations and are found to reinforce the theoretical results. Since the performance of MIMO suffers significantly from MAI and inter-symbol interference (ISI), equalization is needed to mitigate these effects. It is well known from the theory of constrained optimization that the learning speed of any adaptive filtering algorithm can be increased by adding a constraint to it, as in the case of the normalized least mean squared (NLMS) algorithm. Thus, in this work both linear and non-linear decision feedback (DFE) equalizers for MIMO systems with least mean square (LMS) based constrained stochastic gradient algorithm have been designed. More specifically, an LMS algorithm has been developed , which was equipped with the knowledge of number of users, spreading sequence (SS) length, additive noise variance as well as MAI with noise (new constraint) and is named MIMO-CDMA MAI with noise constrained (MNCLMS) algorithm. Convergence and tracking analysis of the proposed algorithm are carried out in the scenario of interference and noise limited systems, and simulation results are presented to compare the performance of MIMO-CDMA MNCLMS algorithm with other adaptive algorithms.

This dissertation introduces three novel multiuser detection approaches in Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems by blind signal separation (BSS) techniques. The conventional methodologies for multiuser detection have to retransmit channel state information (CSI) constantly from the transmitter in MIMO ODFM systems at the cost of economic efficiency, because they require more channel resources to improve the communication quality. Compared with the traditional methodologies, the proposed BSS methods are relatively efficient approaches without the unnecessary retransmission of channel state information. The current methodologies apply the space-time coding or the spatial multiplexing to implement an MIMO OFDM system, which requires relatively complex antenna design and allocation in the transmitter. The proposed Spatial Division Multiple Access (SDMA) method enables different mobile users to share the same bandwidth simultaneously in different geographical locations, and this scheme requires only one antenna for each mobile user. Therefore, it greatly simplifies the antenna design and allocation. The goal of this dissertation is to design and implement three blind multiuser detection schemes without knowing the channel state information or the channel transfer function in the SDMA-based uplink MIMO OFDM system. The proposed scenarios include: (a) the BSS-only scheme, (b) the BSS-Minimum Mean Square Error (MMSE) scheme, and (c) the BSS-Minimum Bit Error Ratio (MBER) scheme. The major contributions of the dissertation include: (a) the three proposed schemes save the commercially expensive cost of channel resources; (b) the proposed SDMA-based uplink MIMO OFDM system simplifies the requirements of antennas for mobile users; (c) the three proposed schemes obtain high parallel computing efficiency through paralleled subcarriers; (d) the proposed BSS-MBER scheme gains the best BER performance; (e) the proposed BSS-MMSE method yields the best computational efficiency; and (f) the proposed BSS-only scenario balances the BER performance and computational complexity.

The next-generation wireless technologies are currently being researched to address the ever-increasing demands for higher data rates, massive connectivity, improved reliability, and extended coverage. Recently, massive multiple-input multiple-output (MIMO) has gained significant attention as a new physical-layer transmission technology that can achieve unprecedented spectral and energy efficiency gains via aggressive spatial multiplexing. Thus, massive MIMO has been one of the key enabling technologies for the fifth-generation and subsequent wireless standards. This dissertation thus focuses on developing a system, channel, and signal models by considering the practical wireless transmission impairments for massive MIMO systems, and ascertaining the viability of massive MIMO in fulfilling massive access, improved spectrum, enhanced security, and energy efficiency requirements. Specifically, new system and channel models, pilot sequence designs and channel estimation techniques, secure transmit/receive beamforming techniques, transmit power allocation schemes with enhanced security provisions, energy efficiency, and user fairness, and comprehensive performance analysis frameworks are developed for massive MIMO-aided non-orthogonal multiple access (NOMA), cognitive spectrum-sharing, and wireless relaying architectures.Our first work focuses on developing physical-layer transmission schemes for NOMA-aided massive MIMO systems. A spatial signature-based user-clustering and pilot allocation scheme is first formulated, and thereby, a hybrid orthogonal multiple access (OMA)/NOMA transmission scheme is proposed to boost the number of simultaneous connections. In our second work, the viability of invoking downlink pilots to boost the achievable rate of NOMA-aided massive MIMO is investigated. The third research contribution investigates the performance of underlay spectrum-sharing massive MIMO systems for reverse time division duplexing based transmission strategies, in which primary and secondary systems concurrently operate in opposite directions. Thereby, we show that the secondary system can be operated with its maximum average transmit power independent of the primary system in the limit of infinity many primary/secondary base-station antennas. In our fourth work, signal processing techniques, power allocation, and relay selection schemes are designed and analyzed for massive MIMO relay networks to optimize the trade-off among the achievable user rates, coverage, and wireless resource usage. Finally, the cooperative jamming and artificial noise-based secure transmission strategies are developed for massive MIMO relay networks with imperfect legitimate user channel information and with no channel knowledge of the eavesdropper. The key design criterion of the aforementioned transmission strategies is to efficiently combine the spatial multiplexing gains and favorable propagation conditions of massive MIMO with properties of NOMA, underlay spectrum-sharing, and wireless relay networks via efficient signal processing.

Thanks to its improved capabilities, the Multiple Input Multiple Output (MIMO) radar is attracting the attention of researchers and practitioners alike. Because it transmits orthogonal or partially correlated waveforms, this emerging technology outperformed the phased array radar by providing better parametric identifiability, achieving higher spatial resolution, and designing complex beampatterns. To avoid jamming and enhance the signal to noise ratio, it is often interesting to maximize the transmitted power in a given region of interest and minimize it elsewhere. This problem is known as the transmit beampattern design and is usually tackled as a two-step process: a transmit covariance matrix is firstly designed by minimizing a convex optimization problem, which is then used to generate practical waveforms. In this work, we propose simple novel methods to generate correlated waveforms using finite alphabet constant and non-constant-envelope symbols. To generate finite alphabet waveforms, the proposed method maps easily generated Gaussian random variables onto the phase-shift-keying, pulse-amplitude, and quadrature-amplitude modulation schemes. For such mapping, the probability density function of Gaussian random variables is divided into M regions, where M is the number of alphabets in the corresponding modulation scheme. By exploiting the mapping function, the relationship between the cross-correlation of Gaussian and finite alphabet symbols is derived. The second part of this thesis covers the topic of target parameter estimation. To determine the reflection coefficient, spatial location, and Doppler shift of a target, maximum likelihood estimation yields the best performance. However, it requires a two dimensional search problem. Therefore, its computational complexity is prohibitively high. So, we proposed a reduced complexity and optimum performance algorithm which allows the two dimensional fast Fourier transform to jointly estimate the spatial location and Doppler shift. To assess the performance of the proposed estimators, the Cramér-Rao Lower Bound (CRLB) is derived. Simulation results show that the mean square estimation error of the proposed estimators achieve the CRLB. Keywords: Collocate antennas, multiple-input multiple-output (MIMO) radar, Finite alphabet waveforms, Hermite polynomials, Reflection coefficient, Doppler, Spatial location, Cramér-Rao Lower Bound.

With the advancement of wireless communication systems, the demand for higher data rates is increasing exponentially. Non Orthogonal Multiple Access (NOMA) is expected to play an important role in 5G new radio networks. In contrast to conventional multiple access schemes, NOMA allows different users to efficiently share the same resources (i.e., time, frequency and code) at different power levels so that the user with lower channel gain is served with a higher power and vice versa. Multiple Input Multiple Output (MIMO) technology to support multiple users, employ tens or even hundreds of antennas at the base station which increases throughput and spectrum efficiency. The combination of NOMA and MIMO techniques can achieve significant performance gains and provide better wireless services to cope with the demands of massive connectivity. In this thesis, we analyze the performance of NOMA-MIMO system. We derive analytical expressions for the performance metrics like Outage Probability (OP) and Symbol Error Rate (SER) in power domain of NOMA-MIMO communication system. The numerical results are validated with the simulation results in MATLAB and the influencing factors for better performance of the system are analysed.