Dynamic clustering for max-min fairness with joint processing CoMP

Aminu, Mubarak Umar; Kaleva, Jarkko; Tölli, Antti

doi:10.1109/pimrc.2016.7794772

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…In [32], a dynamic cluster formation algorithm is presented which merges cells into clusters based on the total improvement in spectral efficiency and users' SINR. In [33], the authors examine a joint dynamic base station clustering and beamformer design problem in a network where Joint Processing CoMP is deployed in the downlink, by formulating and solving a nonconvex max-min rate problem. The main aim of this study is to maximize the minimum rate among all users and limit the cooperating cluster size without hurting the achievable common rate.…”

Section: Related Work and Contribution A Related Studiesmentioning

confidence: 99%

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

et al. 2021

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In today's wireless communication systems, the exponentially growing needs of mobile users require the combination of new and existing techniques to meet the demands for reliable and high-quality service provision. This may not always be possible, as the resources in wireless telecommunication systems are limited and a significant number of users, usually located at the cell edges, can suffer from severe interference. For this purpose, a new Joint Transmission Coordinated Multipoint (JT-CoMP) scheme, in which the transmission points' clustering is based on a coalition formation game, is deployed alongside with Non-Orthogonal Multiple Access (NOMA) in a Cloud Radio Access Network (C-RAN) consisting of small cells. To further enhance the network's performance, Multiuser Multiple-Input Multiple-Output (MU-MIMO) with Zero-Forcing (ZF) beamforming is applied. The proposed scheme's performance, in terms of user throughput, is then compared to that of a scheme where JT-CoMP with static clustering is selected, a JT-CoMP scheme with clustering based on a greedy algorithm and a scenario where JT-CoMP is not deployed. Simulation results confirm that the proposed scheme reliably improves the throughput of users with poor wireless channels while guaranteeing that the performance of the rest is not severely undermined.

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Section: Related Work and Contribution A Related Studiesmentioning

confidence: 99%

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

et al. 2021

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“…The study showed that the CoMP gain by increasing cluster size becomes much less or even negligible if backhaul constraints are considered. In [23], the authors examine a joint dynamic base station clustering and beamformer design problem in a network where Joint Processing CoMP is deployed in the downlink by formulating and solving a non-convex max-min rate problem. The main aim of this study is to maximize the minimum rate among all users and limit the cooperating cluster size without hurting the achievable common rate.…”

Section: Background and Contribution A Related Studiesmentioning

confidence: 99%

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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Dynamic clustering for max-min fairness with joint processing CoMP

Cited by 2 publications

References 14 publications

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

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

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

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