With the limited wireless spectrum and the ever-increasing demand for wireless services, two issues are pressing and difficult: efficient spectrum utilization and heterogeneous traffic management. Throughput and utility maximization problems are proposed to quantify these two issues. To exploit the wireless spatial multiplex gain, concurrent transmissions, if controlled appropriately, can lead to overall higher network throughput as well as utility. The optimal scheduling and power control for concurrent transmissions in rate-adaptive wireless networks is a very challenging NPhard problem. In the thesis, we propose efficient power allocation and scheduling algorithms for concurrent transmissions which can improve network throughput and utility with fairness consideration. We first formulate the optimal power allocation and scheduling problem for network throughput and utility maximization individually, and convert the original non-convex problems into a series of convex problems using a two-phase approximation. Then, we propose power and channel allocation with fairness for network throughput maximization (PCAF-NTM) and for network utility maximization (PCAF-NUM) algorithms to solve the converted problems. Extensive simulation results show the substantial improvement in terms of both network throughput and utility, comparing to the previous scheduling algorithms. / Graduate

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Emerging body-wearable sensor devices for continuous health monitoring are severely energy constrained and yet required to offer high communication reliability under fluctuating channel conditions. This thesis aims at investigating the opportunities and challenges in the use of dynamic radio transmit power control for prolonging the lifetime of such devices. We first present extensive empirical evidence that the wireless link quality can change rapidly in body area networks, and a fixed transmit power results in either wasted energy (when the link is good) or low reliability (when the link is bad). We then propose a class of schemes feasible for practical implementation that adapt transmit power in real-time based on feedback information from the receiver. We show conservative, balanced, and aggressive adaptations of our scheme that progressively achieve higher energy savings of 14%-30% in exchange for higher potential packet losses (up to 10%). We also provide guidelines on how the parameters can be tuned to achieve the desired trade-off between energy savings and reliability within the chosen operating environment. Finally, we implement and profile our scheme on a MicaZ mote based platform, demonstrating that energy savings are achievable even with imperfect feedback information, and report preliminary results on the ultra-low-power integrated healthcare monitoring platform from our collaborating partner Toumaz Technology. In conclusion, our work shows adaptive radio transmit power control as a low-cost way of extending the battery-life of severely energy constrained body wearable devices, and opens the door to further optimizations customized for specific deployment scenarios.

We study the stability of power control algorithms applied to optical networks in the presence of both time-delays and uncertainties. The objective of power control algorithms acting on optical networks is to ensure each signal channel attains an optimal optical signal-to-noise ratio (OSNR) value such that transmission errors are minimized. The inputs to the optical network are the transmitter powers and the outputs of the optical network are the OSNR values. The primal control algorithms adjust the channel powers at the transmitters using the channel OSNR values as feedbacks to attain OSNR optimality. We also present the dual control algorithm located at the links which transmits a channel price as an additional feedback to the primal control algorithms. Together, these are called primal-dual control algorithms. We present robust OSNR models for optical networks with multiple time-delays. Specifically, we consider additive system uncertainties, input multiplicative uncertainties on the signal powers, and transmitter noise uncertainties, all within a norm-bounded uncertainty framework. We analyze and modify both central cost based algorithms and game-theoretic based algorithms, with an emphasis on the latter, to ensure the stability of the closed-loop system. We apply time-delay stability analyses to exploit the structures of the closed-loop systems for each type of control algorithm. These techniques include frequency analyses, Lyapunov-Razumikhin techniques, and Lyapunov-Krasovskii techniques. Due to nonlinearities in the closed-loop system models, and their time-scale separated dynamics, we apply singular perturbation theory modified to handle either Lyapunov-Razumikhin theory or Lyapunov-Krasovskii theory. Singular perturbation theory, modified for time-delays, allows us to decouple complicated closed-loop systems into two simpler subsystems, one on a "slow" time-scale, and the other on a "fast" time-scale. We develop stability conditions for primal algorithms applied to arbitrary networks with delays. We also develop stability conditions for primal-dual algorithms applied to single-links, single-sink networks, two channel networks, and multi-link networks with both time-delays and uncertainties. The main results are presented as either LMI conditions and algebraic criteria. Simulations verify the stability of the closed-loop systems in the presence of time-delays. In addition, the simulations show the stabilization of perturbed systems at the expense of transient convergence time.

The cellular industry is undergoing a major paradigm shift from voice-centric, structured homogeneous networks to a more data-driven, distributed and heterogeneous architecture. One of the more promising trends emerging from this cellular revolution is femtocells. Femtocells are primarily viewed as a cost-effective way to improve both capacity and indoor coverage, and they enable offloading data-traffic from macrocell network. However, efficient interference management in co-channel deployment of femtocells remains a challenge. Decentralized strategies such as femtocell access control have been identified as an effective means to mitigate cross-tier interference in two-tier networks. Femtocells can be configured to be either open access or closed access. Prior work on access control schemes show that, in the absence of any coordination between the two tiers in terms of power control and user scheduling, closed access is the preferred approach at high user densities. Present methods suggest that in the case of orthogonal multiple access schemes like TDMA/OFDMA, femtocell access control should be adaptive according to the estimated cellular user density. The approach we follow, in this work, is to adopt an open access policy at the femtocell access points with a cap on the maximum number of users allowed on a femtocell. This ensures the femto owner retains a significant portion of the femtocell resources. We design an iterative algorithm for hybrid access control for femtocells that integrates the problems of uplink power control and base station assignment. This algorithm implicitly adapts the femtocell access method to the current user density. The distributed power control algorithm, which is based on Yates' work on standard interference functions, enables users to overcome the interference in the system and satisfy their minimum QoS requirements. The optimal allocation of femtocell resources is incorporated into the access control algorithm through a constrained sum-rate maximization to protect the femto owner from starvation at high user densities. The performance of a two-tier OFDMA femtocell network is then evaluated under the proposed access scheme from a home owner viewpoint, and network operator perspective. System-level simulations show that the proposed access control method can provide a rate gain of nearly 52% for cellular users, compared to closed access, at high user densities and under moderate-to-dense deployment of femtocells. At the same time, the femto owner is prevented from going into outage and only experiences a negligible rate loss. The results obtained establish the quantitative performance advantage of using hybrid access at femtocells with power control at high user densities. The convergence properties of the proposed iterative hybrid access control algorithm are also investigated by varying the user density and the mean number of femto access points in the network. It is shown that for a given system model, the algorithm converges quickly within thirty iterations, provided a feasible solution exists.

We study the stability of power control algorithms applied to optical networks in the presence of both time-delays and uncertainties. The objective of power control algorithms acting on optical networks is to ensure each signal channel attains an optimal optical signal-to-noise ratio (OSNR) value such that transmission errors are minimized. The inputs to the optical network are the transmitter powers and the outputs of the optical network are the OSNR values. The primal control algorithms adjust the channel powers at the transmitters using the channel OSNR values as feedbacks to attain OSNR optimality. We also present the dual control algorithm located at the links which transmits a channel price as an additional feedback to the primal control algorithms. Together, these are called primal-dual control algorithms. We present robust OSNR models for optical networks with multiple time-delays. Specifically, we consider additive system uncertainties, input multiplicative uncertainties on the signal powers, and transmitter noise uncertainties, all within a norm-bounded uncertainty framework. We analyze and modify both central cost based algorithms and game-theoretic based algorithms, with an emphasis on the latter, to ensure the stability of the closed-loop system. We apply time-delay stability analyses to exploit the structures of the closed-loop systems for each type of control algorithm. These techniques include frequency analyses, Lyapunov-Razumikhin techniques, and Lyapunov-Krasovskii techniques. Due to nonlinearities in the closed-loop system models, and their time-scale separated dynamics, we apply singular perturbation theory modified to handle either Lyapunov-Razumikhin theory or Lyapunov-Krasovskii theory. Singular perturbation theory, modified for time-delays, allows us to decouple complicated closed-loop systems into two simpler subsystems, one on a "slow" time-scale, and the other on a "fast" time-scale. We develop stability conditions for primal algorithms applied to arbitrary networks with delays. We also develop stability conditions for primal-dual algorithms applied to single-links, single-sink networks, two channel networks, and multi-link networks with both time-delays and uncertainties. The main results are presented as either LMI conditions and algebraic criteria. Simulations verify the stability of the closed-loop systems in the presence of time-delays. In addition, the simulations show the stabilization of perturbed systems at the expense of transient convergence time.

The OFDM technology has been extensively used in many radio communicationtechnologies. For example, OFDM is the core technology applied in WiFi, WiMAXand LTE. Its main advantages include high bandwidth utilization, strong noise im-munity and the capability to resist frequency selective fading. However, OFDMtechnology is not only applied in the field of radio communication, but has alsobeen developed greatly in acoustic communication, namely the so called acousticOFDM. Thanks to the acoustic OFDM technology, the information can be em-bedded in audio and then transmitted so that the receiver can obtain the requiredinformation through certain demodulation mechanisms without severely affectingthe audio quality.This thesis mainly discusses how to embed and transmit information in audioby making use of acoustic OFDM. Based on the theoretical systematic structure, italso designs a simulation system and a measurement system respectively. In thesetwo systems, channel coding, manners of modulation and demodulation, timingsynchronization and parameters of the functional components are configured in themost reasonable way in order to achieve relatively strong stability and robustnessof the system. Moreover, power control and the compatibility between audio andOFDM signals are also explained and analyzed in this thesis.Based on the experimental results, the author analyzes the performance of thesystem and the factors that affect the performance of the system, such as the typeof audio, distance between transmitter and receiver, audio output level and so on.According to this analysis, it is proved that the simulation system can work steadilyin any audio of wav format and transmit information correctly. However, dueto the hardware limitations of the receiver and sender devices, the measurementsystem is unstable to a certain degree. Finally, this thesis draws conclusions of theresearch results and points out unsolved problems in the experiments. Eventually,some expectations for this research orientation are stated and relevant suggestionsare proposed.

We question about multihop gets better performance than single hop in wireless networks. In this paper we design a new and simple multihop transmission model called PESR, performance enhancement of IEEE 802.11 by spatial reuse. We elect an intermediate node which between a source-destination pair for forwarding packets to become multihop instead of directly transmission from the source to the destination. By this way, we will have more links at the one time, the channel utilization should be grown and we will get better system performance. However, there is much overhead we have not considered. We will discuss the detail about overhead in coming sections. In fact, the results of simulation show that the performance is not present very well. And we wonder if the multihop in wireless networks is a pretty good idea.