Coalition Formation Games for Coordinated Service in Realistic Small Cell Propagation Topologies

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 Multipont (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.

Coalition Formation Games for Improved Cell-Edge User Service in Downlink NOMA and MU-MIMO Small Cell Systems

“…In this section, the proposed coalition formation Algorithm 1 alongside its various properties will be presented, after some useful definitions are provided. The proposed coalition formation game algorithm is based on the algorithm of [55], [56] and [57]. In this study however, similarly to [57], an extra condition on the maximum coalition size was adopted to guarantee limited feedback overhead, alongside two external rules about its reactivation due to user mobility and the time-varying nature of the wireless channels.…”

“…The proposed coalition formation game algorithm is based on the algorithm of [55], [56] and [57]. In this study however, similarly to [57], an extra condition on the maximum coalition size was adopted to guarantee limited feedback overhead, alongside two external rules about its reactivation due to user mobility and the time-varying nature of the wireless channels. These external rules will be explained later in this Section.…”

“…Compared to [55], [56] and [57], where each coalition was examined for 10 TTIs, in this study all the coalitions indicated by the proposed algorithm are examined instantaneously. This is possible as zero feedback delay is assumed and allows the study of the upper bound of the performance gain achieved by the proposed scheme.…”