Abstract
The densification of modern wireless networks into a dense ecosystem of small cells imposes challenges for the reliable service and high quality of experience of its users as it can result into severe intercell interference, especially for users scattered on the cell edges. Joint Transmission Coordinated Multipoint (JT-CoMP) is a technique that can be deployed to form cooperating clusters of transmission points, enabling them to jointly transmit data to significantly mitigate this type of interference for these users. However, JT-CoMP stresses the backhaul links and radio resources are limited, meaning that, with incautious clustering, the data rates for cell edge users may not improve, while the data rates for the non-cell edge users may severely decrease. To tackle these drawbacks, a dynamic coalition formation algorithm is proposed to form the appropriate transmission point clusters to implement JT-CoMP. Furthermore, to ensure reliable service for all the network’s users, the case where JT-CoMP is enhanced with the capability to serve users based on their selected application is examined. The proposed scheme’s adaptability and capability to increase cell edge user throughput is then tested and compared to the non JT-CoMP case, a JT-CoMP scheme with static clustering and a JT-CoMP scheme with greedy clustering for a user mobility scenario. To obtain more reliable and accurate results of the JT-CoMP deployment, physical layer parameters retrieved from a fully deterministic physical layer radio planning tool (TruNET wireless) are imported for our simulations.
Highlights
The emergence of the fifth generation (5G) wireless networks aims to satisfy the ever-growing demands of mobile users by providing them with increased data rates and ultra-reliable low-latency provision of a certain level of communication services [1]
Contrary to traditional clustering methods, such as the formation of static clusters only based on the inter-site distance, we developed a coalition formation game in which the players form coalitions to solve the optimization problem defined in equations (13)-(15)
As it can be observed, for the no Coordinated Multipoint (CoMP) and both Joint Transmission Coordinated Multipoint (JT-CoMP) scenarios, the corresponding edge user equipment (UE) throughput values are completely different in both the inactive integration and active integration cases, showcasing the vast difference in the computation of the channel parameters between deterministic and empirical models
Summary
The emergence of the fifth generation (5G) wireless networks aims to satisfy the ever-growing demands of mobile users by providing them with increased data rates and ultra-reliable low-latency provision of a certain level of communication services [1]. Different coverage are planned to be co-deployed in high traffic indoor and outdoor propagation environments, creating a multi-tier heterogeneous network of small cells and increasing the network capacity [3] This means that flexible radio resource allocation strategies, which strive for a fair distribution of the available radio resources to a plethora of connected devices, need to be adopted [4], [5]. CoMP in the downlink can be distinguished into two main techniques, coordinated scheduling/beamforming CoMP and joint processing CoMP These cooperation techniques aim to avoid or exploit interference in order to improve the cell edge user data rates. C-RAN can efficiently support advanced features such as CoMP and interference mitigation as multiple BBUs can coordinate with each other to share the scheduling information, channel status and user data efficiently to improve the system capacity as well as reduce interference in the system [7]. | · | and || · || indicate the norm and the Euclidean norm of a scalar and vector respectively
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