Coordination Multipoint Enabled Small Cells for Coalition-Game-Based Radio Resource Management

Georgakopoulos, Panagiotis; Akhtar, Tafseer; Politis, Ilias; Tselios, Christos; Markakis, Evangelos; Kotsopoulos, Stavros

doi:10.1109/mnet.2019.1800464

Cited by 21 publications

(25 citation statements)

References 11 publications

(11 reference statements)

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“…Besides feedback overhead and backhaul traffic, in wireless systems with limited resources, when JT-CoMP is activated, there is a possibility of committing too many resources to cell edge UEs (or edge UEs), especially if their percentage in the formed clusters is high. As shown in our previous studies, [10], [11], this could result in severely reduced spectral efficiency and data rates for the UEs not in the cell edges (or non-edge UEs), while edge UEs may also not receive sufficient RBs to increase theirs. A game theoretic clustering approach based on coalition formation games was selected and compared to a static clustering approach where the only criterion to form a coalition was the distance between the transmission points.…”

Section: Introductionmentioning

confidence: 93%

“…Then, an effective SINR value is extracted using MIESM and the throughput of the UE is calculated based on the LTE specifications. It is evident by observing equations (10) and (11) that the more RRHs in a coalition, the more the numerator of equation (10) increases, while the denominator decreases, resulting in a higher edge UE post equalization SINR value.…”

Section: System Modelmentioning

confidence: 99%

“…Therefore, a dynamic coalition formation algorithm needs to be constructed that can adapt to possible changes. For this purpose, we adopted the same coalition formation algorithm based on merge and split operations that was used in [10], [11] with an extra restriction on the maximum coalition size and two additional external rules to adapt to user mobility, explained in Section VI, that enable its reactivation. The merge and split operations are based on the Pareto order, meaning that between two collections of coalitions with the same players, one is preferred to another if at least one player improves its payoff, while the payoff of the other players is not decreased.…”

Section: Proposed Coalition Formation Algorithmmentioning

confidence: 99%

“…Our algorithm must be able to efficiently and rapidly operate its merging and splitting functionalities in order to effectively adapt to these changes and ensure adequate QoS for all the network's UEs. To make this possible, a set of new rules must be introduced in our proposed algorithm compared to the algorithm proposed in [10], [11]: • When a handover for the moving UE occurs or its edge status changes, the proposed coalition formation algorithm is reactivated. • If a handover or an edge status change for the moving UE occurs while the algorithm is already running, the coalition formation algorithm ignores these events.…”

Section: ) User Mobility Casementioning

confidence: 99%

“…A game theoretic clustering approach based on coalition formation games was selected and compared to a static clustering approach where the only criterion to form a coalition was the distance between the transmission points. Coalition formation games account for network structure and the costs of cooperation, while satisfying the individual rational demands of the network nodes [12], which is why clustering based on this method was selected in [10], [11] and is also adopted in this study. However, in this study, we implement some additional rules and conditions to examine scenarios with user mobility and additional user data rate needs due to their application.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Introductionmentioning

confidence: 93%

Section: System Modelmentioning

confidence: 99%

Section: Proposed Coalition Formation Algorithmmentioning

confidence: 99%

Section: ) User Mobility Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

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Network Slicing forURLLC

Yang

Quek

et al. 2023

Ultra‐Reliable and Low‐Latency Communications (URLLC) Theory and Practice

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Combination of Ultra-Dense Networks and Other 5G Enabling Technologies: A Survey

2020

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Recently, to address the astonishing capacity requirement of 5G, researchers are investigating the possibility of combining different technologies with ultra-dense networks (UDNs). However, the ultradense deployment of small cells in the coverage area of conventional macrocells known as UDNs introduces new technical challenges such as severe interference, unfairness in radio resource sharing, unnecessary handover, a significant increase in energy consumption, and degraded quality-of-service (QoS). To overcome these challenges and achieve the performance requirements in 5G, there is a need to combine UDNs with other 5G enabling technologies and then, design intelligent management techniques for better performance of the overall networks. Hence, in this paper, we present a comprehensive survey on different generations of wireless networks, 5G new radio (NR) standards, 5G enabling technologies and the importance of combining UDNs with other 5G technologies. Also, we present an extensive overview of the recent advances and research challenges in intelligent management techniques and backhaul solutions in the last five years for the combination of UDNs and other enabling technologies that offers the visions of 5G. We summarise the mathematical tools widely exploited in solving these problems and the performance metrics used to evaluate the intelligent management algorithms. Moreover, we classify various intelligent management algorithms according to the adopted enabling technologies, benefits, challenges addressed, mathematical tools and performance metrics used. Finally, we summarise the open research challenges, provide design guidelines and potential research directions for the development of intelligent management techniques and backhaul solutions for the combination of UDNs and other 5G technologies. INDEX TERMS Macrocells, small cells, ultra-dense networks, QoS.

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Coordination Multipoint Enabled Small Cells for Coalition-Game-Based Radio Resource Management

Cited by 21 publications

References 11 publications

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

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

Network Slicing forURLLC

Combination of Ultra-Dense Networks and Other 5G Enabling Technologies: A Survey

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