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Local altruistic coalition formation game for spectrum sharing and interference management in hyper-dense cloud-RANs

机译:高密度云-RAN中用于频谱共享和干扰管理的本地无私联盟形成游戏

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摘要

In this study, the authors investigate the spectrum sharing and interference management in hyper-dense cloud radio access networks (C-RANs). The authors formulate this problem as a local altruistic coalition formation game (LACF) with externalities. Different from previous studies considering maximising individual small cell's throughput, the authors' purpose is to maximise the social welfare, i.e. the sum satisfaction of remote radio heads (RRHs) with diverse traffic types. The authors design a local altruistic utility function for RRH, i.e. each RRH cares about not only his own interest but also his neighbours'. They make autonomous decisions, finally shaping the entire RRHs into multiple disjoint coalitions. In addition, joint transmission coordinated multi-point technology is considered within coalition to mitigate interference. Then, the authors propose a distributed coalitional formation algorithm based on modified recursive core to obtain the final stable coalition partition. Furthermore, the system stability, convergence and complexity of the proposed algorithm are analysed. Numerical results show that the proposed algorithm outperforms the classical and non-cooperation schemes in the perspective of both social welfare and individual fairness. To be specific, the average rate per RRH of the authors' proposed scheme is superior to the classical and non-cooperation cases by 20 and 25% in hyper-dense scenario, respectively.
机译:在这项研究中,作者研究了超密集云无线电接入网络(C-RAN)中的频谱共享和干扰管理。作者将此问题表述为具有外部性的局部利他联盟形成博弈(LACF)。与先前考虑最大程度地提高单个小小区的吞吐量的研究不同,作者的目的是最大程度地提高社会福利,即具有各种流量类型的远程无线电头端(RRH)的总满意度。作者为RRH设计了一个本地的利他效用函数,即每个RRH不仅关心自己的利益,而且关心他的邻居。他们做出自主决定,最终将整个RRH组成多个不相交的联盟。另外,联盟内部考虑采用联合传输协调多点技术来减轻干扰。然后,作者提出了一种基于改进递归核的分布式联盟形成算法,以获得最终的稳定联盟分区。此外,分析了所提算法的系统稳定性,收敛性和复杂性。数值结果表明,从社会福利和个人公平的角度出发,该算法均优于经典和非合作方案。具体来说,在高密度场景中,作者提出的方案的每个RRH的平均速率分别比传统和非合作案例高20%和25%。

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