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.

Careful network planning has become increasingly critical with the rising deployment, coverage, and congestion of wireless local area networks (WLANs). This thesis outlines the achieved prediction accuracy of a direct-ray, single path loss exponent, adapted Seidel-Rappaport propagation model as determined through measurements and analysis of the established 2.4 GHz, 802.11g outdoor WiFi network deployed on the campus of the Georgia Institute of Technology. Additionally, the viability of using the obtained model parameters as a means for planning future network deployment is discussed. Analysis of measured data shows that accurate predictive planning for network coverage is possible without the need for overly complicated modeling techniques such as ray tracing. The proposed model performs with accuracy comparable to other commonly accepted, more complicated models and is offered as a simple, yet strong predictive model for network planning having both speed and accuracy. Results show, that for the area under study, the standard deviation of the prediction error for the proposed model is below 6.8dB in all analyzed environments, and is approximately 5.5dB on average. Further, the accuracy of model predictions in new environments is shown to be satisfactory for network planning.

In the past few years, due to the global economic recession, the structure of Taiwan media has been changed dramatically. Since the advertising have decreased year by yea and opening of the media market, the world's major media including newspapers¡Bmagazines¡Bradio and television all need to face the pressure of the environmental changed. According to the latest statistics, the advertising revenue of domestic cable TV has especially reduced in the past two years, from 5.038 billion in 2007 down sharply to 5.08 billion in 2008. Even though the challenges, the media still attempt to use new strategy with positive attitude to against harsh environment. For example, there was a newspaper company whcih planning exhibitions through the strategic alliance to create new revenue. Furthermore, the television media try to use the strategy of integrated marketing communication¡]IMC¡^ to increase revenue or change income structure in stead of declining advertising revenue. However, Formosa Television¡]FTV¡^is a good case to show the income steadily through IMC strategy even then decreased of advertisement. We have found that the proportion of advertising revenue up 90% of total revenue in 1997. However, after the changed of business policy, the advertising revenue has been reduced to 60%. Other 40% revenue comes from merchandise¡Bcopyright and integrated marketing. This thesis takes FTV cultural foundation as the case study and try to find out how FTV increased revenue through by internal resources¡Bmultiple communication and innovative products. Meanwhile¡Athe study also analyzes how FTV use IMC tools such as advertising, promotion, personal selling, direct marketing, public relations to change the overall revenue structure and improve the profit. In conclusion, we would like to realize the management of media and provide new strategy for reference.

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Wireless networks are becoming more and more popular. In current wireless network environments, mobile users can use multiple wireless network interfaces built in their mobile devices to roam around the mobile networks. They can scan the wireless spectrums and utilize the network resources extremely, and they can roam into nearby wireless networks due to the mobility capabilities of the powerful mobile devices. Before connecting to an access point, an authentication process is necessary. There are many interactive wireless authentication protocols which have been proposed in the literature. Under the wireless networks, handover is an important property for a mobile user to change her/his position. However, the existing interactive wireless authentication protocols may cause unstable connection. This is because that a mobile user may perform failed authentications with some nearby invalid access points and thus she/he cannot finish handover in time. Hence, we would like to design a mechanism for a mobile user to determine the validity of access points before the interactive authentication, and the mobile user can choose a valid one when making handover. In our proposed scheme, the mobile user can just scan and receive authentication messages from access points without interactions with them while she/he can determine which one of them is valid. We call this cognitive authentication. Besides, we also propose cooperative defense which allows mobile users to exchange their received authentication messages for detecting illegal access points. Finally, we provide security proofs for our proposed scheme.

Conguring a network system to operate at optimal levels of performance re-quires a comprehensive understanding of the eects of a variety of system parameterson crucial metrics like connectivity and resilience to network attacks. Traditionally,omni-directional antennas have been used for communication in wireless sensor net-works. In this thesis, a hybrid communication model is presented where-in, nodes ina network are capable of both omni-directional and uni-directional communication.The eect of such a model on performance in randomly deployed wireless sensor net-works is studied, specically looking at the eect of a variety of network parameterson network performance.The work in this thesis demonstrates that, when the hybrid communication modelis employed, the probability of 100% connectivity improves by almost 90% and thatof k-connectivity improves by almost 80% even at low node densities when comparedto the traditional omni-directional model. In terms of network security, it was foundthat the hybrid approach improves network resilience to the collision attack by almost85% and the cost of launching a successful network partition attack was increased byas high as 600%. The gains in connectivity and resilience were found to improve withincreasing node densities and decreasing antenna beamwidths.

Quality-of-service (QoS) guarantees will play a critically important role in future mobile wireless networks. In this dissertation, we study a set of QoS-driven resource allocation problems for mobile wireless communications and networks. In the first part of this dissertation, we investigate resource allocation schemes for statistical QoS provisioning. The schemes aim at maximizing the system/network throughput subject to a given queuing delay constraint. To achieve this goal, we integrate the information theory with the concept of effective capacity and develop a unified framework for resource allocation. Applying the above framework, we con-sider a number of system infrastructures, including single channel, parallel channel, cellular, and cooperative relay systems and networks, respectively. In addition, we also investigate the impact of imperfect channel-state information (CSI) on QoS pro-visioning. The resource allocation problems can be solved e±ciently by the convex optimization approach, where closed-form allocation policies are obtained for different application scenarios. Our analyses reveal an important fact that there exists a fundamental tradeoff between throughput and QoS provisioning. In particular, when the delay constraint becomes loose, the optimal resource allocation policy converges to the water-filling scheme, where ergodic capacity can be achieved. On the other hand, when the QoS constraint gets stringent, the optimal policy converges to the channel inversion scheme under which the system operates at a constant rate and the zero-outage capacity can be achieved. In the second part of this dissertation, we study adaptive antenna selection for multiple-input-multiple-output (MIMO) communication systems. System resources such as subcarriers, antennas and power are allocated dynamically to minimize the symbol-error rate (SER), which is the key QoS metric at the physical layer. We propose a selection diversity scheme for MIMO multicarrier direct-sequence code- division-multiple-access (MC DS-CDMA) systems and analyze the error performance of the system when considering CSI feedback delay and feedback errors. Moreover, we propose a joint antenna selection and power allocation scheme for space-time block code (STBC) systems. The error performance is derived when taking the CSI feedback delay into account. Our numerical results show that when feedback delay comes into play, a tradeoff between performance and robustness can be achieved by dynamically allocating power across transmit antennas.

Time synchronization in wireless sensor networks (WSNs) is essential and significant for maintaining data consistency, coordination, and performing other fundamental operations, such as power management, security, and localization. Energy efficiency is the main concern in designing time synchronization protocols for WSNs because of the limited and generally nonrechargeable power resources. In this dissertation, the problem of time synchronization is studied in three different aspects to achieve energy efficient time synchronization in WSNs. First, a family of novel joint clock offset and skew estimators, based on the classical two-way message exchange model, is developed for time synchronization in WSNs. The proposed joint clock offset and skew correction mechanisms significantly increase the period of time synchronization, which is a critical factor in the over-all energy consumption required for global network synchronization. Moreover, the Cramer-Rao bounds for the maximum likelihood estimators are derived under two different delay assumptions. These analytical metrics serve as good benchmarks for the experimental results thus far reported. Second, this dissertation proposes a new time synchronization protocol, called the Pairwise Broadcast Synchronization (PBS), which aims at minimizing the number of message transmissions and implicitly the energy consumption necessary for global synchronization of WSNs. A novel approach for time synchronization is adopted in PBS, where a group of sensor nodes are synchronized by only overhearing the timing messages of a pair of sensor nodes. PBS requires a far smaller number of timing messages than other well-known protocols and incurs no loss in synchronization accuracy. Moreover, for densely deployed WSNs, PBS presents significant energy saving. Finally, this dissertation introduces a novel adaptive time synchronization protocol, named the Adaptive Multi-hop Timing Synchronization (AMTS). According to the current network status, AMTS optimizes crucial network parameters considering the energy efficiency of time synchronization. AMTS exhibits significant benefits in terms of energy-efficiency, and can be applied to various types of sensor network applications having different requirements.

Time-synchronization in wireless ad-hoc sensor networks is a crucial piece of infrastructure. Thus, it is a fundamental design problem to have a good clock syn- chronization amongst the nodes of wireless ad-hoc sensor networks. Motivated by this fact, in this thesis, the joint maximum likelihood (JML) estimator for relative clock phase offset and skew under the exponential noise model for the reference broadcast synchronization protocol is formulated and found via a direct algorithm. The Gibbs Sampler is also proposed for joint estimation of relative clock phase offset and skew, and shown to provide superior performance compared to the JML-estimator. Lower and upper bounds for the mean-square errors (MSE) of the JML-estimator and the Gibbs Sampler are introduced in terms of the MSE of the uniform minimum variance unbiased estimator and the conventional best linear unbiased estimator, respectively. The suitability of the Gibbs Sampler for estimating additional unknown parameters is shown by applying it to the problem in which synchronization of clock drift is also needed.

Wireless network analysis and simulations rely on accurate physical layer models. The increased interest in wireless network design and cross-layer design require an accurate and efficient physical layer model especially when a large number of nodes are to be studied and building the real network is not possible. For analysis of upper layer characteristics, a simplified physical layer model has to be chosen to model the physical layer. In this dissertation, the widely used two-state Markov model is examined and shown to be deficient for low to moderate signal-to-noise ratios. The physical layer statistics are investigated, and the run length distributions of the good and bad frames are demonstrated to be the key statistics for accurate physical layer modeling. A four-state Markov model is proposed for the flat Rayleigh fading channel by approximating the run length distributions with a mixture of exponential distributions. The transition probabilities in the four-state Markov model can be established analytically without having to run extensive physical layer simulations, which are required for the two-state Markov model. Physical layer good and bad run length distributions are compared and it is shown that the four-state Markov model reasonably approximates the run length distributions. Ns2 simulations are performed and the four-state Markov model provides a much more realistic approximation compared to the popular two-state Markov model. Achieving good results with the flat Rayleigh fading channel, the proposed four-state Markov model is applied to a few diversity channels. A coded orthogonal fre- quency division multiplexing (OFDM) system with a frequency selective channel and the Alamouti multiple-input multiple-output system are chosen to verify the accuracy of the four-state Markov model. The network simulation results show that the four-state Markov model approximates the physical layer with diversity channel well whereas the traditional two-state Markov model estimates the network throughput poorly. The success of adapting the four-state Markov model to the diversity channel also shows the flexibility of adapting the four-state Markov model to various channel conditions.