In this thesis we investigate the design of transmission resource allocation in current and future wireless communication systems. We focus on systems with multiple antennas and characterize their performance from an information-theoretic viewpoint. The goal of this work is to provide practical transmission and resource allocation strategies taking into account imperfections in estimating the wireless channel, as well as the broadcast nature of the wireless channel. In the first part of the thesis, we consider training-based transmission schemes in which pilot symbols are inserted into data blocks to facilitate channel estimation. We consider one-way training-based systems with and without feedback, as well as two-way training-based systems. Two-way training enables both the transmitter and the receiver to obtain the channel state information (CSI) through reverse training and forward training, respectively. In all considered cases, we derive efficient strategies for transmit time and/or energy allocation among the pilot and data symbols. These strategies usually have analytical closed-form expressions and can achieve near optimal capacity performance evidenced by extensive numerical analysis. In one-way training-based systems without feedback, we consider both spatially independent and correlated channels. For spatially independent channels, we provide analytical bounds on the optimal training length and study the optimal antenna conguration that maximizes an ergodic capacity lower bound. For spatially correlated channels, we provide simple pilot and data transmission strategies that are robust under least-favorable channel correlation conditions. In one-way training-based systems with feedback, we study channel gain feedback (CGF), channel covariance feedback (CCF) and hybrid feedback. For spatially independent channels with CGF, we show that the solutions to the optimal training length and energy coincide with those for systems without feedback. For spatially correlated channels with CCF, we propose a simple transmission scheme, taking into account the fact that the optimal training length is at most as large as the number of transmit antennas. We then provided solution to the optimal energy allocation between pilot and data transmissions, which does not depend on the channel spatial correlation under a mild condition. Our derived resource allocation strategies in CGF and CCF systems are extended to hybrid CCF-CGF systems. In two-way training-based systems, we provide analytical solutions to the transmit power distribution among the different training phases and the data transmission phase. These solutions are shown to have near optimal symbol error rate (SER) and capacity performance. We find that the use of two-way training can provide noticeable performance improvement over reverse training only when the system is operating at moderate to high signal-to-noise ratio (SNR) and using high-order modulations. While this improvement from two-way training is insignificant at low SNR or low-order modulations. In the second part of the thesis, we consider transmission resource allocation in security-constrained systems. Due to the broadcast nature of the wireless medium, security is a fundamental issue in wireless communications. To guarantee secure communication in the presence of eavesdroppers, we consider a multi-antenna transmission strategy which sends both an information signal to the intended receiver and a noise-like signal isotropically to confuse the eavesdroppers. We study the optimal transmit power allocation between the information signal and the artificial noise. In particular, we show that equal power allocation is a near optimal strategy for non-colluding eavesdroppers, while more power should be used to generate the artificial noise for colluding eavesdroppers. In the presence of channel estimation errors, we find that it is better to create more artificial noise than to increase the information signal strength.

"Exploding demand for various wireless services has fueled significant development of wireless communication systems and networks in the past few decades. Wireless service providers are continuously striving to improve the design of communication systems and to enable higher data rate and more reliable wireless transmission. A major challenge in designing these systems is the random nature of the wireless transmission media due to the fading process. A recent paradigm shift from the conventional point-to-point communications is relay assisted communications. Motivated by the great success of multiple-input multiple-output (MIMO) wireless communication systems, with multiple transmit and receive antennas, researchers have considered relay assisted communications. Relying on the broadcast nature of the wireless media, a relay assisted communication system emulates a virtual MIMO system and exploits the spatial diversity, also known as cooperative diversity. Cooperative diversity increases the transmission reliability and coverage, without expanding the expenditure of the scarce transmission resources (power and bandwidth). Recently, the research community has witnessed an increasing interest in studying relay assisted communication systems. These studies include proposing novel relaying schemes, exploring ways to maximize the cooperative gain, and investigating the fundamental performance limits of these systems. The bulk of the literature is based on the main assumption that the effect of fading channels (commonly referred to as channel state information) is perfectly known at the destination. In practical communication systems, however, the unknown fading channels are first estimated and the channel estimates are used for decoding the message transmitted by the source. In order to have a more realistic and accurate understanding of the benefits of relay assisted systems, one needs to study the effect of uncertainty, imposed by channel estimation error, on the fundamental performance limits. Such study can guide to a more efficient system design and provide optimal resource allocation between data and training (required for channel estimation). Two widely used relay assisted wireless communication systems are: 1) a one-way relay assisted system, in which there is a source, a relay and a destination, and the relay helps the source by forwarding the overheard message to the destination; 2) a two-way relay assisted system, in which two sources are interested in mutual communication, i.e., one source is the destination of the other source. In this system the relay helps both users by forwarding the overheard messages to the intended destinations. For each system, one can envision different system designs, depending on the specific relaying scheme and the specific signal processing algorithm adopted at the relay. The most commonly used relaying schemes are Amplify-and-Forward (AF) and Decodeand- Forward (DF), where in the former the relay amplifies and forwards the overheard messages, while in the latter, the relay decodes the overheard messages and then forwards them. In this thesis, we consider one-way and two-way AF relay assisted systems with a half-duplex relay. We study the impact of uncertainty, due to channel estimation errors, on the fundamental performance limits. In particular, we consider mean squared error (MSE) and the Bayesian Cramer -Rao lower bound (CRLB) for channel estimation as the estimation theoretic optimality criteria and channel mutual information lower bound and outage probability upper bound as the information theoretic optimality criteria. We explore how the negative effect of channel uncertainty can be mitigated, via optimal transmission resource allocation that maximizes or minimizes a specific optimality criteria. We also compare the bidirectional mutual information lower bounds of direct transmission without the relay, one-way AF relay and two-way AF relay systems. Furthermore, we examine the effect of joint optimization of the media access control and physical layers on the system throughput for one-way AF and DF relay assisted systems"--Abstract.

Wireless networks promise ubiquitous communication, and thus facilitate an array of applications that positively impact human life. At a fundamental level, these networks deal with compression and transmission of sources over channels. Thus, accomplishing this task efficiently is the primary challenge shared by these applications. In practice, sources include data and video while channels include interference and relay networks. Hence, effective source and channel aware resource allocation for these scenarios would result in a comprehensive solution applicable to real-world networks. This dissertation studies the problem of source and channel aware resource allocation in certain scenarios. A framework for network resource allocation that stems from rate-distortion theory is presented. Then, an optimal decomposition into an application-layer compression control, a transport-layer congestion control and a network-layer scheduling is obtained. After deducing insights into compression and congestion control, the scheduling problem is explored in two cross-layer scenarios. First, appropriate queue architecture for cooperative relay networks is presented, and throughput-optimality of network algorithms that do not assume channel-fading and input-queue distributions are established. Second, decentralized algorithms that perform rate allocation, which achieve the same overall throughput region as optimal centralized algorithms, are derived. In network optimization, an underlying throughput region is assumed. Hence, improving this throughput region is the next logical step. This dissertation addresses this problem in the context of three significant classes of interference networks. First, degraded networks that capture highly correlated channels are explored, and the exact sum capacity of these networks is established. Next, multiple antenna networks in the presence of channel uncertainty are considered. For these networks, robust optimization problems that result from linear precoding are investigated, and efficient iterative algorithms are derived. Last, multi-cell time-division-duplex systems are studied in the context of corrupted channel estimates, and an efficient linear precoding to manage interference is developed.

Scientific Study from the year 2016 in the subject Engineering - Communication Technology, Mahalingam College of Engineering and Technology, language: English, abstract: The future Wireless Communication Systems (WCS) are supposed to provide high data rate to support personal and multimedia communications irrespective of the users' mobility and location. These services include heterogeneous classes of traffics such as voice, file transfer, web browsing, wireless multimedia, teleconferencing, and interactive games. In recent years, data and multimedia services have become important in wireless communications. As a result, bandwidth requirement and number of users become delicate problems. To support high data rate requirement for future WCS, it is essential to efficiently allocate the limited resources. The major challenges are the dynamic nature of wireless channel, limited resources such as power, frequency spectrum, and diversified Quality of Service (QoS) requirements. Orthogonal Frequency Division Multiplexing (OFDM) is a special case of multicarrier transmission that supports high data rate operation. OFDM is a modulation and multiplexing technique appropriate for current and future wireless networks. OFDM divides the available bandwidth into a number of parallel independent orthogonal subchannels and their bandwidth is much less than the coherence bandwidth of the channel. The wide band frequency selective fading channel is converted into several narrow band flat fading channels. OFDM is an excellent method to overcome multipath fading effects. One of the goals of WCS is to enhance the capacity of the channel. Multiple Access Technique (MAT) permits several mobile users to share the given bandwidth in an effective way. Basically there are four multiple access techniques available namely, Time Division Multiple Access (TDMA), Frequency Division Multiple access (FDMA), Code Division Multiple Access (CDMA) and Space Division Multiple Access (SDMA). MAT is employ

Optimal Resource Allocation in Coordinated Multi-Cell Systems provides a solid grounding and understanding for optimization of practical multi-cell systems and will be of interest to all researchers and engineers working on the practical design of such systems.

We also study the design of precoding and decoding matrices for the downlink of a multiuser MIMO system when spatial multiplexing is used. We investigate the block diagonalization approach for multiuser MIMO systems and propose a random precoding technique that schedules users for transmission with only limited feedback from the receivers. We then introduce a new optimization criterion for designing a linear transceiver which tries to minimize the maximum mean-squared error among all users or data substreams; we show that this approach results in fairness among users and improved average BER.

The ultimate goal of future generation wireless communications is to provide ubiquitous seamless connections between mobile terminals such as mobile phones and computers so that users can enjoy high-quality services at anytime anywhere without wires. The feature to provide a wide range of delay constrained applications with diverse quality of service (QoS) requirements, such as delay and data rate requirements, will require QoS-driven wireless resource allocation mechanisms to efficiently allocate wireless resources, such as transmission power, time slots and spectrum, for accommodating heterogeneous mobile data. In addition, multiple-input-multiple-output (MIMO) antenna technique, which uses multiple antennas at the transmitter and receiver, can improve the transmission data rate significantly and is of particular interests for future high speed wireless communications. In the thesis, we develop smart energy efficient scheduling algorithms for delay constrained communications for single user and multi-user single-input-single-output (SISO) and MIMO transmission systems. Specifically, the algorithms are designed to minimize the total transmission power while satisfying individual user's QoS constraints, such as rate, delay and rate or delay violation. Statistical channel information (SCI) and instantaneous channel state information (CSI) at the transmitter side are considered respectively, and the proposed design can be applied for either uplink or downlink. We propose to jointly deal with scheduling of the users that access to the channel for each frame time (or available spectrum) and how much power is allocated when accessing to the channel. In addition, the algorithms are applied with modifications for uplink scheduling in IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX). The success of the proposed research will significantly improve the ways to design wireless resource allocation for delay constrained communications.