System modeling and performance evaluation of rate allocation schemes for packet data services in wideband CDMA systems

To fully exploit the potential of a wideband CDMA-based mobile Internet computing system, an efficient algorithm is needed for judiciously performing rate allocation, so as to orchestrate and allocate bandwidth for voice services and high data rate applications. However, in existing standards (e.g., cdma2000), only a first-come-first-served equal sharing allocation algorithm is used, potentially leading to a low bandwidth utilization and inadequate support of high data rate multimedia mobile applications (e.g., video/audio files swapping, multimedia messaging services, etc.). In this paper, we first analytically model the rate allocation problem that captures realistic system constraints such as downlink power limits and control, uplink Interference effects, physical channel adaptation, and soft handoff. We then suggest six efficient rate allocation schemes that are designed based on different philosophies: rate optimal, fairness-based, and user-oriented. Simulations are performed to evaluate the effectiveness of the rate allocation schemes using realistic system parameters In our model.published_or_final_versio

Peak-to-Average-Power-Ratio (PAPR) Reduction Techniques for Orthogonal-Frequency-Division- Multiplexing (OFDM) Transmission

Wireless communication has experienced an incredible growth in the last decade. Two decades ago,the number of mobile subscribers was less than 1% of the world\u27s population. As of 2011, the number of mobile subscribers has increased tremendously to 79.86% of the world\u27s population. Robust and high-rate data transmission in mobile environments faces severe problems due to the time-variant channel conditions, multipath fading and shadow fading. Fading is the main limitation on wireless communication channels. Frequency selective interference and fading, such as multipath fading, is a bandwidth bottleneck in the last mile which runs from the access point to the user. The last mile problem in wireless communication networks is caused by the environment of free space channels through which the signal propagates. Orthogonal Frequency Division Multiplexing (OFDM) is a promising modulation and multiplexing technique due to its robustness against multipath fading. Nevertheless, OFDM suffers from high Peak-to-Average- Power-Ratio (PAPR), which results in a complex OFDM signal. In this research, reduction of PAPR considering the out-of-band radiation and the regeneration of the time-domain signal peaks caused by filtering has been studied and is presented. Our PAPR reduction was 30% of the Discrete Fourier Transform (DFT) with Interleaved Frequency Division Multiple Access (IFDMA) utilizing Quadrature Phase Shift Keying (QPSK) and varying the roll-off factor. We show that pulse shaping does not affect the PAPR of Localized Frequency Division Multiple Access (LFDMA) as much as it affects the PAPR of IFDMA. Therefore, IFDMA has an important trade-off relationship between excess bandwidth and PAPR performance, since excess bandwidth increases as the roll-off factor increases. In addition, we studied a low complexity clipping scheme, applicable to IFDMA uplink and OFDM downlink systems for PAPR reduction. We show that the performance of the PAPR of the Interleaved-FDMA scheme is better than traditional OFDMA for the uplink transmission system. Our reduction of PAPR is 53% when IFDMA is used instead of OFDMA in the uplink direction. Furthermore, we also examined an important trade-off relationship between clipping distortion and quantization noise when the clipping scheme is used for OFDM downlink systems. Our results show a significant reduction in the PAPR and the out-of-band radiation caused by clipping for OFDM downlink transmission system

Convergence of packet communications over the evolved mobile networks; signal processing and protocol performance

In this thesis, the convergence of packet communications over the evolved mobile networks is studied. The Long Term Evolution (LTE) process is dominating the Third Generation Partnership Project (3GPP) in order to bring technologies to the markets in the spirit of continuous innovation. The global markets of mobile information services are growing towards the Mobile Information Society. The thesis begins with the principles and theories of the multiple-access transmission schemes, transmitter receiver techniques and signal processing algorithms. Next, packet communications and Internet protocols are referred from the IETF standards with the characteristics of mobile communications in the focus. The mobile network architecture and protocols bind together the evolved packet system of Internet communications to the radio access network technologies. Specifics of the traffic models are shortly visited for their statistical meaning in the radio performance analysis. Radio resource management algorithms and protocols, also procedures, are covered addressing their relevance for the system performance. Throughout these Chapters, the commonalities and differentiators of the WCDMA, WCDMA/HSPA and LTE are covered. The main outcome of the thesis is the performance analysis of the LTE technology beginning from the early discoveries to the analysis of various system features and finally converging to an extensive system analysis campaign. The system performance is analysed with the characteristics of voice over the Internet and best effort traffic of the Internet. These traffic classes represent the majority of the mobile traffic in the converged packet networks, and yet they are simple enough for a fair and generic analysis of technologies. The thesis consists of publications and inventions created by the author that proposed several improvements to the 3G technologies towards the LTE. In the system analysis, the LTE showed by the factor of at least 2.5 to 3 times higher system measures compared to the WCDMA/HSPA reference. The WCDMA/HSPA networks are currently available with over 400 million subscribers and showing increasing growth, in the meanwhile the first LTE roll-outs are scheduled to begin in 2010. Sophisticated 3G LTE mobile devices are expected to appear fluently for all consumer segments in the following years

Multidimensional Frequency Estimation with Applications in Automotive Radar

This thesis considers multidimensional frequency estimation with a focus on computational efficiency and high-resolution capability. A novel framework on multidimensional high-resolution frequency estimation is developed and applied to increase the range, radial velocity, and angular resolution capcability of state-of-the-art automotive radars

Analysis of Hepatocyte Secretion Pathways: A Case Study on Hepatic Apolipoproteins, Serum Albumin, and Hepatitis C Virus

The hepatocyte is one of the major secretory cell types in the body. It fulfills many of the liver\u27s essential functions in protein secretion, lipid storage and transport, and excretion. Some of these functions are carried out via polarized secretion of simple protein cargo, such as serum albumin, or large macromolecular lipid-protein complexes, the lipoproteins. The hepatocyte is also the site of infection of several hepatotropic viruses. Of these, hepatitis C virus (HCV) is peculiar due to its close structural and functional association with the hepatic lipoproteins. All these cargoes are transported from the endoplasmic reticulum (ER) to the cell surface by the vesicular secretory pathway, yet insufficient knowledge exists regarding the molecular regulation of their secretion by the hepatocyte. Furthermore, differential modalities of regulation may be involved in the shuttling of such a diverse set of cargoes as albumin, the lipoproteins and HCV. The work presented here head-starts a comprehensive examination of how the hepatocyte regulates the secretion of the following cargoes: serum albumin, the apolipoproteins E and B100 (ApoE and ApoB100, respectively, both lipoprotein components, and surrogate markers for these complex macromolecular particles), and HCV, a lipoprotein-associated virus. I propose to combine genetic, biochemical, virological and imaging approaches to identify which vesicular secretory pathways are utilized by each of these cargoes. These approaches include inactivation of specific vesicular transport pathways, accompanied by measurements of their effects on cargo secretion efficiencies, and establishment of functional fluorescent protein-tagged cargo markers to be used in live cell imaging experiments. I begin by describing a dominant negative (DN) Rab GTPase screen that I performed to identify Rab proteins involved in ApoE, ApoB100 or albumin secretion. The small Rab GTPases control individual steps of vesicular transport. I analyzed how expression of individual dominant negative Rab proteins affected cargo secretion compared to expression of their wild type (WT) counterparts. I identified several Rabs that caused significant changes in secretion, many of which had previously been described as regulators of various exocytic vesicular transport steps. I next present ongoing work that aims to define the involvement of the Rabs 11a, 11b, 8a, and 8b in hepatic cargo secretion. Their dominant negative mutants exhibited some of the largest secretion phenotypes in my dominant negative Rab screen. These Rabs have been implicated in various aspects of post-Golgi secretion in polarized and non-polarized cell types. I thus discuss the implications of their involvement in cargo secretion in the polarized hepatocyte and outline my ongoing efforts to define the parameters of this involvement. I also investigated the function of Rab1b in hepatic secretion. I show that inactivation of Rab1 function, by expression of a set of dominant negative mutants, or by expression of a bacterial effector which affects Rab1 function, led to impairment of albumin, ApoE, ApoB100 and HCV secretion. I implicate Rab1, for the first time to my knowledge, in the transport of these cargoes. I also document differences in the sensitivity of cargo secretion to the various means of Rab1 inactivation. ApoE secretion, in particular, was insensitive to several means of transport inactivation, consistent with existing models of differential regulation of hepatic cargo transport. Lastly, I functionally characterize an ApoE-green fluorescent protein fusion (ApoE-GFP). I show that while ApoE-GFP does not support infectious HCV release, a hallmark function of untagged ApoE, ApoE-GFP nevertheless reproduces several known behaviors of ApoE that have been associated with lipoprotein release. I thus conclude that ApoE-GFP may be a useful marker for live cell imaging of lipoprotein release. This work therefore identifies potential regulators of hepatic cargo transport, establishes molecular tools useful for the continued study of cargo secretion in hepatocytes and elsewhere, and advances the understanding of the involvement of Rabs 11, 8, and, in particular, Rab1, in the regulation of hepatic cargo transport. I propose that this work forms a solid foundation for extensive studies on how these biomedically relevant hepatic cargoes are secreted

Scheduling algorithms for next generation cellular networks

Next generation wireless and mobile communication systems are rapidly evolving to satisfy the demands of users. Due to spectrum scarcity and time-varying nature of wireless networks, supporting user demand and achieving high performance necessitate the design of efficient scheduling and resource allocation algorithms. Opportunistic scheduling is a key mechanism for such a design, which exploits the time-varying nature of the wireless environment for improving the performance of wireless systems. In this thesis, our aim is to investigate various categories of practical scheduling problems and to design efficient policies with provably optimal or near-optimal performance. An advantage of opportunistic scheduling is that it can effectively be incorporated with new communication technologies to further increase the network performance. We investigate two key technologies in this context. First, motivated by the current under-utilization of wireless spectrum, we characterize optimal scheduling policies for wireless cognitive radio networks by assuming that users always have data to transmit. We consider cooperative schemes in which secondary users share the time slot with primary users in return for cooperation, and our aim is to improve the primary systems performance over the non-cooperative case. By employing Lyapunov Optimization technique, we develop optimal scheduling algorithms which maximize the total expected utility and satisfy the minimum data rate requirements of the primary users. Next, we study scheduling problem with multi-packet transmission. The motivation behind multi-packet transmission comes from the fact that the base station can send more than one packets simultaneously to more than one users. By considering unsaturated queueing systems we aim to stabilize user queues. To this end, we develop a dynamic control algorithm which is able to schedule more than one users in a time slot by employing hierarchical modulation which enables multi-packet transmission. Through Lyapunov Optimization technique, we show that our algorithm is throughput-optimal. We also study the resulting rate region of developed policy and show that it is larger than that of single user scheduling. Despite the advantage of opportunistic scheduling, this mechanism requires that the base station is aware of network conditions such as channel state and queue length information of users. In the second part of this thesis, we turn our attention to the design of scheduling algorithms when complete network information is not available at the scheduler. In this regard, we study three sets of problems where the common objective is to stabilize user queues. Specifically, we first study a cellular downlink network by assuming that channels are identically distributed across time slots and acquiring channel state information of a user consumes a certain fraction of resource which is otherwise used for transmission of data. We develop a joint scheduling and channel probing algorithm which collects channel state information from only those users with su±ciently good channel quality. We also quantify the minimum number of users that must exist to achieve larger rate region than Max-Weight algorithm with complete channel state information. Next, we consider a more practical channel models where channels can be time-correlated (possibly non-stationary) and only a fixed number of channels can be probed. We develop learning based scheduling algorithm which tracks and predicts instantaneous transmission rates of users and makes a joint scheduling and probing decision based on the predicted rates rather than their exact values. We also characterize the achievable rate region of these policies as compared to Max-Weight policy with exact channel state information. Finally, we study a cellular uplink system and develop a fully distributed scheduling algorithm which can perform over general fading channels and does not require explicit control messages passing among the users. When continuous backoff time is allowed, we show that the proposed distributed algorithm can achieve the same performance as that of centralized Max-Weight algorithm in terms of both throughput and delay. When backoff time can take only discrete values, we show that our algorithm can perform well at the expense of low number of mini-slots for collision resolution

Mobile Health Technologies

Mobile Health Technologies, also known as mHealth technologies, have emerged, amongst healthcare providers, as the ultimate Technologies-of-Choice for the 21st century in delivering not only transformative change in healthcare delivery, but also critical health information to different communities of practice in integrated healthcare information systems. mHealth technologies nurture seamless platforms and pragmatic tools for managing pertinent health information across the continuum of different healthcare providers. mHealth technologies commonly utilize mobile medical devices, monitoring and wireless devices, and/or telemedicine in healthcare delivery and health research. Today, mHealth technologies provide opportunities to record and monitor conditions of patients with chronic diseases such as asthma, Chronic Obstructive Pulmonary Diseases (COPD) and diabetes mellitus. The intent of this book is to enlighten readers about the theories and applications of mHealth technologies in the healthcare domain

Joint Downlink Beamforming and Discrete Resource Allocation Using Mixed-Integer Programming

Multi-antenna processing is widely adopted as one of the key enabling technologies for current and future cellular networks. Particularly, multiuser downlink beamforming (also known as space-division multiple access), in which multiple users are simultaneously served with spatial transmit beams in the same time and frequency resource, achieves high spectral efficiency with reduced energy consumption. To harvest the potential of multiuser downlink beamforming in practical systems, optimal beamformer design shall be carried out jointly with network resource allocation. Due to the specifications of cellular standards and/or implementation constraints, resource allocation in practice naturally necessitates discrete decision makings, e.g., base station (BS) association, user scheduling and admission control, adaptive modulation and coding, and codebook-based beamforming (precoding). This dissertation focuses on the joint optimization of multiuser downlink beamforming and discrete resource allocation in modern cellular networks. The problems studied in this thesis involve both continuous and discrete decision variables and are thus formulated as mixed-integer programs (MIPs). A systematic MIP framework is developed to address the problems. The MIP framework consists of four components: (i) MIP formulations that support the commercial solver based approach for computing the optimal solutions, (ii) analytic comparisons of the MIP formulations, (iii) customizing techniques for speeding up the MIP solvers, and (iv) low-complexity heuristic algorithms for practical applications. We consider first joint network topology optimization and multi-cell downlink beamforming (JNOB) for coordinated multi-point transmission. The objective is to minimize the overall power consumption of all BSs while guaranteeing the quality-of-service (QoS) requirements of the mobile stations (MSs). A standard mixed-integer second-order cone program (MISOCP) formulation and an extended MISOCP formulation are developed, both of which support the branch-and-cut (BnC) method. Analysis shows that the extended formulation admits tighter continuous relaxations (and hence less computational complexity) than that of the standard formulation. Effective strategies are proposed to customize the BnC method in the MIP solver CPLEX when applying it to the JNOB problem. Low-complexity inflation and deflation procedures are devised for large-scale applications. The simulations show that our design results in sparse network topologies and partial BS cooperation. We study next the joint optimization of discrete rate adaptation and downlink beamforming (DRAB), in which rate adaptation is carried out via modulation and coding scheme (MCS) assignment and admission control is embedded in the MCS assignment procedure. The objective is to achieve the maximum sum-rate with the minimum transmitted BS power. As in the JNOB problem, a standard and an extended MISOCP formulations are developed, and analytic comparisons of the two formulations are carried out. The analysis also leads to efficient customizing strategies for the BnC method in CPLEX. We also develop fast inflation and deflation procedures for applications in large-scale networks. Our numerical results show that the heuristic algorithms yield sum-rates that are very close to the optimal ones. We then turn our attention to codebook-based downlink beamforming. Codebook-based beamforming is employed in the latest cellular standards, e.g., in long-term evolution advanced (LTE-A), to simplify the signaling procedure of beamformers with reduced signaling overhead. We consider first the standard codebook-based downlink beamforming (SCBF) problem, in which precoding vector assignment and power allocation are jointly optimized. The objective is to minimize the total transmitted BS power while ensuring the prescribed QoS targets of the MSs. We introduce a virtual uplink (VUL) problem, which is proved to be equivalent to the SCBF problem. A customized power iteration method is developed to solve optimally the VUL problem and hence the SCBF problem. To improve the performance of codebook-based downlink beamforming, we propose a channel predistortion mechanism that does not introduce any additional signalling overhead or require modification of the mobile receivers. The joint codebook-based downlink beamforming and channel predistortion (CBCP) problem represents a non-convex MIP. An alternating optimization algorithm and an alternating feasibility search algorithm are devised to approximately solve the CBCP problem. The simulation results confirm the efficiency of the channel predistortion scheme, e.g., achieving significant reductions of the total transmitted BS power. We study finally the worst-case robust codebook-based downlink beamforming when only estimated channel covariance matrices are available at the BS. Similar to the DRAB problem, user admission control is embedded in the precoding vector assignment procedure. In the robust codebook-based downlink beamforming and admission control (RCBA) problem, the objective is to achieve the maximum number of admitted MSs with the minimum transmitted BS power. We develop a conservative mixed-integer linear program (MILP) approximation and an exact MISOCP formulation of the RCBA problem. We further propose a low-complexity inflation procedure. Our simulations show that the three approaches yield almost the same average number of admitted MSs, while the MILP based approach requires much more transmitted BS power than the other two to support the admitted MSs. The MIP framework developed in this thesis can be applied to address various discrete resource allocation problems in interference limited cellular networks. Both optimal solutions, i.e., performance benchmarks, and low-complexity practical algorithms are considered in our MIP framework. Conventional approaches often did not adopt the exact discrete models and approximated the discrete variables by (quantized) continuous ones, which could lead to highly suboptimal solutions or infeasible problem instances

Diversity Combining under Interference Correlation in Wireless Networks

A theoretical framework is developed for analyzing the performance of diversity combining under interference correlation. Stochastic models for different types of diversity combining and networks are presented and used for analysis. These models consider relevant system aspects such as network density, path loss, channel fading, number of antennas, and transmitter/receiver processing. Theoretical results are derived, performance comparisons are presented, and design insights are obtained