دانلود رایگان مقاله مدیریت تداخل مبتنی بر خوشه بندی در شبکه فمتوسل

Abstract

Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this context, this paper proposes a novel concept of Universal Intelligent Small Cell (UnISCell) for enabling the densification of the next generation of cellular networks. The proposed novel concept envisions an integrated platform of providing a strong linkage between different stakeholders such as street lighting networks, landline telephone networks and future wireless networks, and is universal in nature being independent of the operating frequency bands and traffic types. The main motivating factors for the proposed small cell concept are the need of public infrastructure re-engineering, and the recent advances in several enabling technologies. First, we highlight the main concepts of the proposed UnISCell platform. Subsequently, we present two deployment scenarios for the proposed UnISCell concept considering infrastructure sharing and service sharing as important aspects. We then describe the key future technologies for enabling the proposed UnISCell concept and present a use case example with the help of numerical results. Finally, we conclude this article by providing some interesting future recommendations.

6. Conclusion

In this paper, we studied the RA and interference management problem in dense OFDM femtocell networks. In this context, the FAP will be responsible for the clustering phase, and then the CH (elected from the femtocell group) will be responsible for the sub-channel and power allocation phase. Our formulation leads to a mixed integer programming problem which is computationally intractable. So we divided the problem into two subproblems: clustering subproblem and subchannel and power allocation subproblem. First, femtocells are grouped into clusters to lower intra-tier interference. Then, the CCs will be responsible for the subchannel and power allocation in each cluster. We allocate subchannels to FUs by considering the rate gap between each FU's current rate and its requirement. Finally, we develop a fast algorithm which can achieve the optimal power distribution with a complexity of O(M N) 2 by exploiting the structure of the power distribution problem. Numerical simulations validate the effectiveness and efficiency of our proposed methods. For future work, we can consider QoS requirements. Uncertainty in channel gain information can be considered as well using a robust optimization framework. Instead of maximizing data rate, other objectives such as maximizing the energy efficiency can also be considered for clustering-based resource allocation in multi-tier OFDMA cellular networks.