3 resultados para proposed solution

em DRUM (Digital Repository at the University of Maryland)


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In this dissertation, I study three problems in market design: the allocation of resources to schools using deferred acceptance algorithms, the demand reduction of employees on centralized labor markets, and the alleviation of traffic congestion. I show how institutional and behavioral considerations specific to each problem can alleviate several practical limitations faced by current solutions. For the case of traffic congestion, I show experimentally that the proposed solution is effective. In Chapter 1, I investigate how school districts could assign resources to schools when it is desirable to provide stable assignments. An assignment is stable if there is no student currently assigned to a school that would prefer to be assigned to a different school that would admit him if it had the resources. Current assignment algorithms assume resources are fixed. I show how simple modifications to these algorithms produce stable allocations of resources and students to schools. In Chapter 2, I show how the negotiation of salaries within centralized labor markets using deferred acceptance algorithms eliminates the incentives of the hiring firms to strategically reduce their demand. It is well-known that it is impossible to eliminate these incentives for the hiring firms in markets without negotiation of salaries. Chapter 3 investigates how to achieve an efficient distribution of traffic congestion on a road network. Traffic congestion is the product of an externality: drivers do not consider the cost they impose on other drivers by entering a road. In theory, Pigouvian prices would solve the problem. In practice, however, these prices face two important limitations: i) the information required to calculate these prices is unavailable to policy makers and ii) these prices would effectively be new taxes that would transfer resources from the public to the government. I show how to construct congestion prices that retrieve the required information from the drivers and do not transfer resources to the government. I circumvent the limitations of Pigouvian prices by assuming that individuals make some mistakes when selecting routes and have a tendency towards truth-telling. Both assumptions are very robust observations in experimental economics.

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Wireless power transfer (WPT) and radio frequency (RF)-based energy har- vesting arouses a new wireless network paradigm termed as wireless powered com- munication network (WPCN), where some energy-constrained nodes are enabled to harvest energy from the RF signals transferred by other energy-sufficient nodes to support the communication operations in the network, which brings a promising approach for future energy-constrained wireless network design. In this paper, we focus on the optimal WPCN design. We consider a net- work composed of two communication groups, where the first group has sufficient power supply but no available bandwidth, and the second group has licensed band- width but very limited power to perform required information transmission. For such a system, we introduce the power and bandwidth cooperation between the two groups so that both group can accomplish their expected information delivering tasks. Multiple antennas are employed at the hybrid access point (H-AP) to en- hance both energy and information transfer efficiency and the cooperative relaying is employed to help the power-limited group to enhance its information transmission throughput. Compared with existing works, cooperative relaying, time assignment, power allocation, and energy beamforming are jointly designed in a single system. Firstly, we propose a cooperative transmission protocol for the considered system, where group 1 transmits some power to group 2 to help group 2 with information transmission and then group 2 gives some bandwidth to group 1 in return. Sec- ondly, to explore the information transmission performance limit of the system, we formulate two optimization problems to maximize the system weighted sum rate by jointly optimizing the time assignment, power allocation, and energy beamforming under two different power constraints, i.e., the fixed power constraint and the aver- age power constraint, respectively. In order to make the cooperation between the two groups meaningful and guarantee the quality of service (QoS) requirements of both groups, the minimal required data rates of the two groups are considered as constraints for the optimal system design. As both problems are non-convex and have no known solutions, we solve it by using proper variable substitutions and the semi-definite relaxation (SDR). We theoretically prove that our proposed solution method can guarantee to find the global optimal solution. Thirdly, consider that the WPCN has promising application potentials in future energy-constrained net- works, e.g., wireless sensor network (WSN), wireless body area network (WBAN) and Internet of Things (IoT), where the power consumption is very critical. We investigate the minimal power consumption optimal design for the considered co- operation WPCN. For this, we formulate an optimization problem to minimize the total consumed power by jointly optimizing the time assignment, power allocation, and energy beamforming under required data rate constraints. As the problem is also non-convex and has no known solutions, we solve it by using some variable substitutions and the SDR method. We also theoretically prove that our proposed solution method for the minimal power consumption design guarantees the global optimal solution. Extensive experimental results are provided to discuss the system performance behaviors, which provide some useful insights for future WPCN design. It shows that the average power constrained system achieves higher weighted sum rate than the fixed power constrained system. Besides, it also shows that in such a WPCN, relay should be placed closer to the multi-antenna H-AP to achieve higher weighted sum rate and consume lower total power.