In summary, we made the following contributions in this dissertation:
Heterogeneous Networks
1. We are the first to study the cell-breathing phenomenon in heterogeneous networks.
We propose a novel femtocell cell-breathing control framework for managing the load-balancing and coverage control among overlay cells.
2. Based on the cell-breathing framework, we formulate a game-theoretical model for discussing the cheating issue in overlay network with selfish mobile stations. We introduce the concept of voting theory into the cell-breathing control framework.
The proposed voting-based FEVER mechanism is proved to be truthful. This
truth-ful strategies form a dominant-strategy Nash Equilibrium in FEVER mechanism, which can be easily implemented. In addition, we prove that FEVER mechanism offers the flexibility to strike a balance between capacity efficiency and allocation fairness.
3. We propose a novel wireless service differentiation framework to investigate the profit service providers make under a variety of differentiated contracts in the het-erogeneous system. This framework addresses the differences between wireless service quality among users, which is the basis of the service differentiation.
4. We draw a comparison between the shared-spectrum and split-spectrum systems in our service differentiation framework and have derived the optimal (profit max-imizing) contracts under three schemes: flat fee contracts, differentiated contracts without incentive compatible concerns, and incentive compatible differentiated con-tracts. In a split-spectrum system, it is difficult to further extract profits from MSs as the only incentive compatible contract is a flat fee one. By contrast, in a shared-spectrum system, there are differentiated contracts generating profits by raising ser-vice prices for the MSs with good serser-vice qualities in femtocells, while providing cheaper prices to other MSs with poor service qualities.
5. We address the heterogeneous characteristics of carrier quality, coverage, and UE QoS requirements in the proposed game-theoretic approach to carrier aggregation mechanism. We make use of the carrier aggregation to enhance the system perfor-mance by satisfying the QoS requirements of UEs more efficiently. Specifically, we consider two type of UEs, throughput-sensitive and delay-sensitive UEs, in this work. The proposed solution effectively reduces the delay for delay-sensitive UEs while satisfying the throughput requirements of throughput-sensitive UEs. Addi-tionally, we propose a truthful auction design specifically for the heterogeneous carrier quality and QoS requirements of UEs. We theoretically prove that the pro-posed design indeed provides proper incentive for the UEs to truthfully report their QoS requirements.
6. All proposed solutions for each problem in heterogeneous networks are evaluated through extensive simulations in our LTE-Advances simulator, which uses the mod-els and parameters suggested in 4G evaluation document [1] and 3GPP LTE stan-dard [2].
Device-to-device Communication
1. We propose a novel LTE-Advanced D2D resource allocation framework based on the resource exchange approach. We reuse most existing LTE-Advanced compo-nents and followed the same signalling flow logic in order to minimize the protocol impacts.
2. We theoretically prove that the resource exchange approach is equivalent to the tra-ditional resource allocation approach in the solution feasibility. Adtra-ditionally, we prove that any arbitrary algorithm, either distributed or centralized, will converge in the proposed framework whenever all exchanges are beneficial. To the best of our knowledge, we are the first group to present the resource exchange approach to the D2D resource allocation problem.
3. We propose the Trader-assisted Resource Exchange (T-REX) mechanism as an effi-cient and flexible solution to the D2D resource allocation problem in the proposed framework. The T-REX mechanism identifies the beneficial exchanges through an-alyzing the corresponding exchange graph. The algorithm's complexity is polyno-mial, which makes it a practical solution to large-scale D2D networks. In addition, the derived allocation is Pareto optimal; therefore, the efficiency is guaranteed. In addition, we prove that the T-REX mechanism is strategy-proof when the trader preference functions are properly designed.
4. All the proposed solutions were evaluated through the proposed LTE-Advanced D2D simulator, which uses the models and parameters suggested in the latest 3GPP technical contribution [3]. Our simulation results showed that the proposed T-REX mechanism significantly mitigates the interference experienced by D2D devices.
Additionally, the convergence of the proposed framework is verified and evaluated in the simulations.
Social Learning and Multicasting System
1. We propose a novel game, called Chinese Restaurant Game, to formulate the so-cial learning problem with negative network externality by introducing the strate-gic behavior into the non-stratestrate-gic Chinese restaurant process. Through analyzing the Chinese restaurant game, we observe that the timing of making decision signifi-cantly influences a participant's utility. We show that there exists a tradeoff between two contradictory advantages, which are making decisions earlier for choosing bet-ter actions and making decisions labet-ter for learning more accurate believes.
2. Chinese restaurant game is general enough to model various learning and decision making problems in social network, cloud computing, and wireless networks. We demonstrate how the model can be applied in real applications by studying the chan-nel access and sensing problems in cognitive radio network. Through simulations, we show that both the sensing accuracy and utilities of network users are enhanced by applying the best strategies derived from Chinese restaurant game.
3. We develop a Markov decision process based stochastic framework to analyze the resource allocation in a SVC multicasting system with heterogeneous user demands.
By considering the stochastic user arrival, such a framework is more general than the existing snapshot-based approaches in the literature.
4. We propose a game-theoretic model, which is based on Chinese restaurant game, to analyze the behaviors of heterogeneous users. We study how rational and intelligent users submit their demands, i.e., subscriptions, under two pricing schemes: one-time charge scheme and per-slot charge scheme, and derive the equilibrium conditions of the game. To the best of our knowledge, this is the first work bringing game theoretic analysis to the SVC multicasting system.
5. We theoretically evaluate the economic value of the SVC multicasting system. Specif-ically, we investigate the revenue-maximized policy and pricing strategies in both one-time charge and per-slot charge schemes. We propose an efficient algorithm to derive the optimal policy and pricing strategies of the SVC multicasting system.
Both theory and simulation results confirm that the derived solution not only maxi-mizes the expected revenue but also optimaxi-mizes the social welfare.