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Robust resource allocation for rates maximization using fuzzy estimation of dynamic channel states in OFDMA femtocell networks

机译:利用OFDMA Femtocell网络中使用动态信道状态的模糊估计的速率资源分配最大化

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摘要

One of the challenging issues in dynamic resource management scheme of wireless communications is to achieve the instantaneous channel gain for transmission pairs. When designing the resource allocation algorithms, the previous works usually rely on the statistical information of the channel distribution and the harsh assumption of uncertain channel, and they are with much conservatism for the dynamic channel gain. To overcome the limitations of the existing methods, the Fuzzy Logic System (FLS) is adopted in this paper to estimate the instantaneous channel gain for the dynamic communication environments. Based on the estimated channel gains, the power allocation scheme is proposed for the orthogonal frequency division multiple access (OFDMA) femtocell network. The proposed scheme attempts to maximize the total rate of the communication system and to guarantee the quality of service of each user. The original optimization problem is a nonconvex optimization problem which is difficult to solve. The successive convex approximation (SCA) is adopted to transform the nonconvex original problem into a tractable one. The distributed iterative algorithm is developed to integrate with the proposed scheme in real-time dynamic communication environments. The effectiveness of the proposed scheme is demonstrated through the simulations, and the results show that the sum rate and energy efficiency of users can be improved by the proposed scheme, compared to the existing schemes. (C) 2019 Elsevier B.V. All rights reserved.
机译:无线通信动态资源管理方案中的一个具有挑战性的问题是实现传输对的瞬时信道增益。在设计资源分配算法时,之前的作品通常依赖于信道分布的统计信息和不确定信道的严苛假设,并且它们对动态信道增益具有很多保守的。为了克服现有方法的局限性,本文采用模糊逻辑系统(FLS)来估计动态通信环境的瞬时信道增益。基于估计的信道增益,提出了用于正交频分多址(OFDMA)毫微微小区网络的功率分配方案。所提出的计划试图最大限度地提高通信系统的总速率,并保证每个用户的服务质量。原始优化问题是一个难以解决的非透露优化问题。采用连续的凸近似(SCA)将非凸起原始问题转换为贸易的问题。开发了分布式迭代算法以与实时动态通信环境中提出的方案集成。通过模拟证明了所提出的方案的有效性,结果表明,与现有方案相比,所提出的方案可以提高用户的总和率和能量效率。 (c)2019 Elsevier B.v.保留所有权利。

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