Proposed Allocation Framework Research Articles

Utilizing the strategic concession behavior in a bargaining game for optimal allocation of water in a transboundary river basin during water bankruptcy

In basins that lie across multiple administrative boundaries, for instance in international river basins like the Nile, water tends to be contested especially during times of scarcity. Riparian countries sharing a transboundary river basin may emphasize the multi-dimensionality of their water demands to obtain access to a greater portion of the available shared water. As a result, the frequency and intensity of water conflicts may increase, hindering the sustainable development of riparian countries and threatening the security and stability of the whole region. Therefore, designing a fair, reasonable, and adaptive allocation scheme is of paramount importance to ensure the integrity of livelihoods and ecosystem health. This paper analyzed the general features of transboundary river basins and built an allocation mechanism combining Bankruptcy Theory with Bargaining and Concession games. A Bankruptcy-Concession-Bargaining Game Model (BCBGM) was constructed to ensure multi-agent participation, multi-stage negotiation, and optimal allocation. Considering the different water demand preferences and linked satisfaction functions, the framework yielded an optimal solution by making concessions on the water claims of riparian countries. As a case study, the proposed model was applied to allocate the limited water resources of the Euphrates-Tigris River. To further measure the stability of model allocation results, a model was built to evaluate the stability of water allocation. The results show that the stability of the allocation output from the proposed allocation framework was relatively high compared to those obtained from classical allocation rules, such as Proportion, Adjusted Proportion, Constrained Equal Loss, and Constrained Equal Award. The model's results satisfied the Pareto efficiency, individual rationality, and maximized group utility. Therefore, for the most part, the allocation outputs of the proposed scheme were generally self-enforceable and sustainable.

Non-Convex Generalized Nash Games for Energy Efficient Power Allocation and Beamforming in mmWave Networks

Network management is a fundamental ingredient for efficient operation of wireless networks. With increasing bandwidth, number of antennas and number of users, the amount of information required for network management increases significantly. Therefore, distributed network management is a key to efficient operation of future networks. This paper focuses on the problem of distributed joint beamforming control and power allocation in ad-hoc mmWave networks. Over the shared spectrum, a number of multi-input-multi-output links attempt to minimize their supply power by simultaneously finding the locally optimal power allocation and beamformers in a self-organized manner. Our design considers a family of non-convex quality-of-service constraint and utility functions characterized by monotonicity in the strategies of the various users. We propose a two-stage, decentralized optimization scheme, where the adaptation of power levels and beamformer coefficients are iteratively performed by each link. We first prove that given a set of receive beamformers, the power allocation stage converges to an optimal generalized Nash equilibrium of the generalized power allocation game. Then we prove that iterative minimum-mean-square-error adaptation of the receive beamformer results in an overall converging scheme. Several transmit beamforming schemes requiring different levels of information exchange are also compared in the proposed allocation framework. Our simulation results show that allowing each link to optimize its transmit filters using the direct channel results in a near optimum performance with very low computational complexity, even though the problem is highly non-convex.