Comments on "Cross-Tier Cooperation for Optimal Resource Utilization in Ultra-Dense Heterogeneous Networks"

© 2018 IEEE. Two adaptive dedicated channel allocation algorithms, namely dynamic dedicated channel partitioning (D2CP) and dynamic dedicated channel partitioning with cooperation (D2CP-C), were proposed in [1] to improve the system throughput of ultra-dense networks (UDN). However, due to the incorrect use of the geometric-arithmetic mean inequality theorem, the average system throughput could not be guaranteed to be optimal. In this letter, we study the proposed D2CP and D2CP-C algorithms in UDN and deduce the average system throughput. Consequently, we prove that the equal resource allocation strategy proposed in [1] is strictly not optimal

Energy Efficient Resource Allocation and Utilization in Future Heterogeneous Cellular Network

Future Mobile Heterogeneous Cellular Networks are emerging as promising technology in terms of high speed, low latency and ubiquitous connectivity. Providing energy efficient services in exponentially increasing user size and rigorous utilization of mobile services is a key challenge for mobile operators. The mobile operators deployed dense small cells to enhance the network capacity for providing the network services to maximum users. Instead of fully utilize of the existing deployment, operators leads to enhance the number of small cell base stations to enhance the network coverage. When the number of small cells increases, the energy consumption of the cellular network also increases. Thus a resource efficient, cost effective and energy efficient solution is required to control the deployment of new base station that consequently enhance the energy efficiency. In this paper, an efficient resource allocation and utilization model is proposed using Cognitive Fusion Centre (CFC). Where the CFC has Resource State Information (RSI) of the network resources and manages the free available resources. It helps in generating resource segment to facilitate the incoming users at peak hours. The propose solution can be deployed to any dense environment for maximum resource utilization