In a distributed system, one of the most important things is to establish an assignment method for distributing tasks. It is assumed that a dis tributed system does not have a central administrator, all independent pr...In a distributed system, one of the most important things is to establish an assignment method for distributing tasks. It is assumed that a dis tributed system does not have a central administrator, all independent processing units in this system want to cooperate for the best results, but they cannot know the conditions of one another. So in order to undertake the tasks in admirable pro portions, they have to adjust their undertaking tasks only by self-learning. In this paper, the performance of this system is analyzed by Markov chains, and a robust method of self-learning for independent processing units in this kind of systems is presented. This method can lead the tasks of the system to be distributed very well among all the independent processing units, and can also be used to solve the general assignment problem.展开更多
Coordinated multi-point transmission and reception （CoMP） for single user, named as SU-CoMP, is considered as an efficient approach to mitigate inter-cell interference in orthogonal frequency division multiple acce...Coordinated multi-point transmission and reception （CoMP） for single user, named as SU-CoMP, is considered as an efficient approach to mitigate inter-cell interference in orthogonal frequency division multiple access （OFDMA） systems. Two prevalent approaches in SU-CoMP are coordinated scheduling （CS） and joint processing （JP）. Although JP in SU-CoMP has been proved to achieve a great link performance improvement for the cell-edge user, efficient resource allocation （RA） on the system level is quite needed. However, so far limited work has been done considering JP, and most existing schemes achieved the improvement of cell-edge performance at cost of the cell-average performance degradation compared to the single cell RA. In this paper, a two-phase strategy is proposed for SU-CoMP networks. CS and JP are combined to improve both cell-edge and cell-average performance. Compared to the single cell RA, simulation results demonstrate that, the proposed strategy leads to both higher cell-average and cell-edge throughput.展开更多
文摘In a distributed system, one of the most important things is to establish an assignment method for distributing tasks. It is assumed that a dis tributed system does not have a central administrator, all independent processing units in this system want to cooperate for the best results, but they cannot know the conditions of one another. So in order to undertake the tasks in admirable pro portions, they have to adjust their undertaking tasks only by self-learning. In this paper, the performance of this system is analyzed by Markov chains, and a robust method of self-learning for independent processing units in this kind of systems is presented. This method can lead the tasks of the system to be distributed very well among all the independent processing units, and can also be used to solve the general assignment problem.
基金supported by the National Natural Science Foundation of China (61001116)State Emphasis Special Project 2009ZX03003-011-02+1 种基金the Hi-Tech Research and Development Program of China (2009AA011506)International Scientific and Technological Cooperation Program (2010DFA11060)
文摘Coordinated multi-point transmission and reception （CoMP） for single user, named as SU-CoMP, is considered as an efficient approach to mitigate inter-cell interference in orthogonal frequency division multiple access （OFDMA） systems. Two prevalent approaches in SU-CoMP are coordinated scheduling （CS） and joint processing （JP）. Although JP in SU-CoMP has been proved to achieve a great link performance improvement for the cell-edge user, efficient resource allocation （RA） on the system level is quite needed. However, so far limited work has been done considering JP, and most existing schemes achieved the improvement of cell-edge performance at cost of the cell-average performance degradation compared to the single cell RA. In this paper, a two-phase strategy is proposed for SU-CoMP networks. CS and JP are combined to improve both cell-edge and cell-average performance. Compared to the single cell RA, simulation results demonstrate that, the proposed strategy leads to both higher cell-average and cell-edge throughput.
