Space-time coding techniques are widely used in multiple-input multiple-output communication systems to mitigate the effect of multipath fading in wireless channels. An important subset of space-time codes are linear dispersion (LD) codes, which are used for quasi-static Rayleigh flat fading channels when the channel state information (CSI) is only available at the receiver side. In this thesis, we propose a new receiver structure for LD codes. We suggest to use widely-linear minimum-mean-squared-error (WL-MMSE) estimates of the transmitted symbols in lieu of the sufficient statistics for maximum likelihood (ML) detection of these symbols. This structure offers both optimal and suboptimal operation modes. The structures of the proposed receivers in both modes are derived for general LD codes. As special cases, we study two important subsets of LD codes, namely orthogonal and quasi-orthogonal codes, and examine the performance of the proposed receivers for these codes.

Space-time coding techniques are widely used in multiple-input multiple-output communication systems to mitigate the effect of multipath fading in wireless channels. An important subset of space-time codes are linear dispersion (LD) codes, which are used for quasi-static Rayleigh flat fading channels when the channel state information (CSI) is only available at the receiver side. In this thesis, we propose a new receiver structure for LD codes. We suggest to use widely-linear minimum-mean-squared-error (WL-MMSE) estimates of the transmitted symbols in lieu of the sufficient statistics for maximum likelihood (ML) detection of these symbols. This structure offers both optimal and suboptimal operation modes. The structures of the proposed receivers in both modes are derived for general LD codes. As special cases, we study two important subsets of LD codes, namely orthogonal and quasi-orthogonal codes, and examine the performance of the proposed receivers for these codes.

The scarce and overpopulated radio spectrum is going to present a major barrier to the growth and development of future wireless networks. As such, spectrum sharing seems to be inevitable to accommodate the exploding demand for high data rate applications. A major challenge to realizing the potential advantages of spectrum sharing is interference management. This thesis deals with interference management techniques in noncooperative networks. In specific, interference alignment is used as a powerful technique for interference management. We use the degrees of freedom (DoF) as the figure of merit to evaluate the performance improvement due to the interference management schemes. This dissertation is organized in two parts. In the first part, we consider the K-user multiple input multiple output (MIMO) Gaussian interference channel (IC) with M antennas at each transmitter and N antennas at each receiver. This channel models the interaction between K transmitter-receiver pairs sharing the same spectrum for data communication. It is assumed that the channel coefficients are constant and are available at all nodes prior to data transmission. A new cooperative upper-bound on the DoF of this channel is developed which outperforms the known bounds. Also, a new achievable transmission scheme is provided based on the idea of interference alignment. It is shown that the achievable DoF meets the upper-bound when the number of users is greater than a certain threshold, and thus it reveals the channel DoF. In the second part, we consider communication over MIMO interference and X channels in a fast fading environment. It is assumed that the transmitters obtain the channel state information (CSI) after a finite delay which is greater than the coherence time of the channel. In other words, the CSI at the transmitters becomes outdated prior to being exploited for the current transmission. New transmission schemes are proposed which exploit the knowledge of the past CSI at the transmitters to retrospectively align interference in the subsequent channel uses. The proposed transmission schemes offer DoF gain compared to having no CSI at transmitters. The achievable DoF results are the best known results for these channels. Simple cooperative upper-bounds are developed to prove the tightness of our achievable results for some network configurations.

For wireless communication systems, due to broadcasting nature of wireless medium, how to keep eavesdroppers from wiretapping messages is worth investigated. In addition to encryption techniques applied in application layer, physical layer secrecy techniques have been studied in literature. Under the premise that eavesdropper cannot steal any information, physical layer secrecy focus on maximizing the capacity of legal transmission, and make it more reliable by using physical properties of wireless channel. This thesis considers an amplify-and-forward (AF) multiple-input multiple-output (MIMO) cooperative communication network with an untrusted relay (UR), and linear precoders are employed at source, relay, and destination. The relay here serves as a bridge of transmission 1 between the source and the destination. However, assume that the untrusted relay may wiretap information from the source without authorization. In order to prevent relay from wiretapping information, the destination generates artificial noise (AN) to interfere the relay, when the relay is receiving information from the source. Since AN is generated by the destination, the destination can eliminate AN by itself after receiving signal from the relay without corrupting signals of legal transmission. We propose precoder design for source, relay and destination to maximize secrecy capacity under the power constraint of three nodes. By utilizing singular value decomposition (SVD) of all channel matrices and Hadamard inequality, we simplify the optimization problem of precoding matrices to scalar optimization problem, and optimization can be accomplished recursively.

Design and analysis of random-like codes for various multiple-input and multiple-output communication systems are addressed in this work. Random-like codes have drawn significant interest because they offer capacity-achieving performance. We first consider the analysis and design of low-density parity-check (LDPC) codes for turbo multiuser detection in multipath CDMA channels. We develop techniques for computing the probability density function (pdf) of the extrinsic messages at the output of the soft-input soft-output (SISO) multiuser detectors as a function of the pdf of input extrinsic messages, user spreading codes, channel impulse responses, and signal-to-noise ratios. Using these techniques, we are able to accurately compute the thresholds for LDPC codes and design good irregular LDPC codes. We then apply the tools of density evolution with mixture Gaussian approximations to optimize irregular LDPC codes and to compute minimum operational signal-to-noise ratios for ergodic MIMO OFDM channels. In particular, the optimization is done for various MIMO OFDM system configurations which include different number of antennas, different channel models and different demodulation schemes. We also study the coding-spreading tradeoff in LDPC coded CDMA systems employing multiuser joint decoding. We solve the coding-spreading optimization based on the extrinsic information SNR evolution curves for the SISO multiuser detectors and the SISO LDPC decoders. Both single-cell and multi-cell scenarios will be considered. For each of these cases, we will characterize the extrinsic information for both finite-size systems and the so-called large systems where asymptotic performance results must be evoked. Finally, we consider the design optimization of irregular repeat accumulate (IRA) codes for MIMO communication systems employing iterative receivers. We present the density evolution-based procedure with Gaussian approximation for optimizing the IRA code ensemble. We adopt an approximation method based on linear programming to design an IRA code with the extrinsic information transfer (EXIT) chart matched to that of the soft MIMO demodulator.

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology has been used widely in many wireless communication systems. Signals will be distorted when they are transmitted in wireless channels. For the reason that wireless channel is time or location variant, we have to estimate the channel impulse response and use the channel state information to compensate the channel distortion. In order to estimate the state of the channel, let the known training symbols put in front of the data symbols and use training symbols to estimate channel response. A typical channel estimate for MIMO OFDM systems is treated as spatially uncorrelated. However in many realistic scenarios, the channel tends to be spatially correlated. Indeed, we have no prior knowledge of the channel spatial correlation. So consider the spatial correlation, the channel can estimate accurately. And it is important that how to combine spatial correlation and channel estimation to reduce the estimation error. In the paper we propose a iterative channel spatial correlation and channel estimation algorithm. At first, channel spatial correlation estimation is obtained by synchronize symbols. The receiver uses the estimated channel to help the detection/decision of data symbol. And then the channel estimation treats the detected signals as known data to perform a next stage channel estimation iteratively. By utilizing the iterative channel estimation and signal detection process we can reduce the estimation error caused by channel spatial correlation estimation. The accuracy of the channel estimation can be improved by increasing the number of iteration process. Simulation results demonstrate the iterative spatial correlation and channel estimation algorithm can provide better mean-square-error performance.

As resources are limited, radio spectrum becomes congested due to the growth of wireless applications. However, measurements address the fact that most of the licensed spectrums experience low utilization even in intensively teeming areas. In the exertion to improve the utilization of the limited spectrum resources, cognitive radio networks have emerged as a powerful technique to resolve this problem. There are two types of user in cognitive radio networks (CRNs) named as primary user (PU) and secondary user (SU). Therein, the CRN enables the SU to utilize the unused licensed frequency of the PU if it possibly finds the vacant spectrum or white space (known as opportunistic spectrum access). Alternatively, SU can transmit simultaneously with the PU provided that transmission power of SU does not cause any harmful interference to the PU (known as spectrum sharing systems). In this thesis work, we study fundamental knowledge of the CRNs and focus on the performance analysis of the single input multiple output (SIMO) system for spectrum sharing approach. We assume that a secondary transmitter (SU-Tx) has full channel state information (CSI). The SU-Tx can adjust its transmit power not to cause harmful interference to the PU and obtain an optimal transmit rate. In particular, we derive the closed-form expressions for the cumulative distribution function (CDF), outage probability and an analytical expression for symbol error probability (SEP). / As resources are limited, radio spectrum becomes congested due to the growth of wireless applications. However, measurements address the fact that most of the licensed spectrums experience low utilization even in intensively teeming areas. In the exertion to improve the utilization of the limited spectrum resources, cognitive radio networks have emerged as a powerful technique to resolve this problem. There are two types of user in cognitive radio networks (CRNs) named as primary user (PU) and secondary user (SU). Therein, the CRN enables the SU to utilize the unused licensed frequency of the PU if it possibly finds the vacant spectrum or white space (known as opportunistic spectrum access). Alternatively, SU can transmit simultaneously with the PU provided that transmission power of SU does not cause any harmful interference to the PU (known as spectrum sharing systems). In this thesis work, we study fundamental knowledge of the CRNs and focus on the performance analysis of the single input multiple output (SIMO) system for spectrum sharing approach. We assume that a secondary transmitter (SU-Tx) has full channel state information (CSI). The SU-Tx can adjust its transmit power not to cause harmful interference to the PU and obtain an optimal transmit rate. In particular, we derive the closed-form expressions for the cumulative distribution function (CDF), outage probability and an analytical expression for symbol error probability (SEP). / Iqbal Hasan Haider, cell: +46704571807 MD. Fazla Rabby, cell: +46734965477

In multicell coordinated networks where multiple base stations cooperate to jointly combat interference from adjacent cells and fading to receivers, one of the outstanding questions is what is the role of receive antenna and receiver processing. Multiple receive antennas not only enable additional degrees of freedom at each receiver to combat the other-cell interference but also can change the transmitter design because transmitter and receiver beamforming design is often closely coordinated. In this dissertation, we investigate the role of the multiple receive antennas in multicell cooperative systems under different interference conditions. We then present novel non-iterative and iterative coordinated beamforming and precoding algorithms with different receiver processing. We present comprehensive performance comparison of various multicell cooperative systems and explore the feasibility of achieving much higher throughput via hyper-densification of heterogeneous and small cell networks with mandatory multicell cooperation. / text

In the modern world of technology, highly sophisticated electronic systems pave the way for future's information technology breakthroughs. However, rapid growth on complexity and functions in such systems has also been a harbinger for the power increase. Power management techniques have thus been introduced to mitigate this urgent power crisis. Switching power converters are considered to be the best candidate due to their high efficiency and voltage conversion flexibility. Moreover, switching power converter systems are highly nonlinear, discontinuous in time, and variable. This makes it viable over a wide operating range, under various load and line disturbances. However, only one control scheme cannot optimize the whole system in different scenarios. Hybrid control schemes are thus employed in the power converters to operate jointly and seamlessly for performance optimization during start-up, steady state and dynamic voltage/load transient state.In this dissertation, three switching power converter topologies, along with different hybrid control schemes are studied. First, an integrated switching buck converter with a dual-mode control scheme is proposed. A pulse-train (PT) control, employing a combination of four pulse control patterns, is proposed to achieve optimal regulation performance. Meanwhile, a high-frequency pulse-width modulation (PWM) control is adopted to ensure low output ripples and avoid digital limit cycling. Second, an integrated buck-boost converter with a tri-mode digital control is presented. It employs adaptive step-up/down voltage conversion to enable a wide range of output voltage. This is beneficial to ever-increasing dynamic voltage scaling (DVS) enabled, modern power-efficient VLSI systems. DVS adaptively adjusts the supply voltage and operation frequency according to instantaneous power and performance demand, such that a system is constantly operated at the lowest possible power level without compromising its performance. Third, a digital integrated single-inductor multiple-output (SIMO) converter, tailored for DVS-enabled multicore systems is addressed. With a multi-mode control algorithm, DVS tracking speed and line/load regulation are significantly improved, while the converter still retains low cross regulation.All three integrated CMOS DC-DC converters have been designed and fabricated successfully, demonstrating the techniques proposed in this research. The measurements results illustrate superior line and load regulation performances and dynamic response in all these designs.

In most wireless communications research, the channel models considered experience less severe fading than the classic Rayleigh fading case. In this thesis, however, we investigate MIMO channels where the fading is more severe. In these environments, we show that the coefficient of variation of the channel amplitudes is a good predictor of the link mutual information, for a variety of models. We propose a novel channel model for severely fading channels based on the complex multivariate t distribution. For this model, we are able to compute exact results for the ergodic mutual information and approximations to the outage probabilities for the mutual information. Applications of this work include wireless sensors, RF tagging, land-mobile, indoor-mobile, ground-penetrating radar, and ionospheric radio links. Finally, we point out that the methodology can also be extended to evaluate the mutual information of a cellular MIMO link and the performance of various MIMO receivers in a cellular scenario. In these cellular applications, the channel itself is not severely fading but the multivariate t distribution can be applied to model the effects of intercellular interference.