Virtual Cell Clustering with Optimal Resource Allocation to Maximize Cellular System Capacity

Yemini, Michal; Goldsmith, Andrea

doi:10.1109/globecom38437.2019.9014051

Cited by 10 publications

(25 citation statements)

References 41 publications

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“…Cluster-based resource allocation algorithms [30]- [32] reduces the complexity of the load balancing, resource selection and often used for the resource-constrained network scenario. In [30] proposes the energy-efficient resource allocation considering the cluster node's residual energy.…”

Section: Related Workmentioning

confidence: 99%

GateSelect: A novel Internet gateway selection algorithm for client nodes

Batbayar

Meseguer

Sadre

et al. 2020

2020 16th International Conference on Network and Service Management (CNSM)

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The Internet gateway selection problem is becoming very important as the number of Internet-connected devices increases and stresses the limited number of Internet gateway nodes. The gateway nodes often experience frequent performance fluctuations, and the best gateway selection candidate changes frequently with growing network dynamics. We propose GateSelect, a customized selection algorithm for each client node that not only provides the best-effort selection candidate but also ensures the global, balanced distribution of the gateway nodes. We utilize over the counter, lightweight calculations to optimize the client-side selection algorithm by combining classification, short term performance prediction, and randomized selection. We compare our algorithm with several baseline algorithms, and the experiment results show that our proposal provides better performance and balanced distribution of gateway nodes.

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Section: Related Workmentioning

confidence: 99%

GateSelect: A novel Internet gateway selection algorithm for client nodes

Batbayar

Meseguer

Sadre

et al. 2020

2020 16th International Conference on Network and Service Management (CNSM)

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show abstract

“…Thus, this cluster has to be formed in a CPU-centric way. This concept was inspired by [21], [28]. The association between a UE and a nearby BS is based on their channel condition and thus can be UE-centric.…”

Section: Introductionmentioning

confidence: 99%

“…Existing literatures have shed light on the design for uplink (UL) and downlink (DL) cooperative networks. The authors of [21], [28], [22] proposed a Fog-RAN network structure and discussed the optimal UL RA in the frequency domain, relying on both an independent and a joint decoding scheme. These impressive contributions have also quantified the impact of cluster-size on the system performance: full scale cooperation may attain a factor of three UL throughput enhancement.…”

Section: Introductionmentioning

confidence: 99%

Optimal Massive-MIMO-Aided Clustered Base-Station Coordination

Zhang

Zhou

et al. 2021

IEEE Trans. Veh. Technol.

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A large-scale clustered massive MIMO network is proposed for improving the spectral efficiency of the nextgeneration wireless infrastructure by maximizing its sum-rate. Our solution combines the advantages of the centralized processing architecture and massive MIMO. Explicitly, the network is divided into multiple clusters; each cluster is handled by a centralized processing unit, which connects to a certain number of massive MIMO-aided BSs, where only limited information is exchanged among the clusters; each user of a cluster can be served by several nearby BSs in a user-centric way.We analyze the maximum sum-rate of the network with multiple antennas at BSs and UEs, relying on the optimal transmit precoder matrix of each BS configured for each user, and on the optimal frequency-domain power sharing scheme of each cluster. The optimizations are conceived for multiple coordination schemes that were widely studied in literature, namely the coherent-joint-transmission (CJT) scheme, the noncoherent-joint-transmission (NCJT) scheme and the coordinatedbeamfoming/scheduling (CBF/CS) scheme. Our simulations show that the optimal CJT achieves 2.2 -4.5 times higher average sumrate than its non-cooperative massive MIMO network counterpart, while the optimal NCJT and the optimal CBF/CS achieve at most a factor 1.3 average sum-rate gain. The popular signalto-leakage-and-noise-ratio (SLNR) scheme is also extended to the multi-antenna UE scenario and achieves a factor 1.1 -1.2 gain. Index Terms-Large-scale clustered MIMO network, cell free MIMO, weighted sum rate maximization, optimal precoding matrix, optimal power sharing.

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“…In our previous works, [20]- [22], we developed a resource allocation optimization scheme that clusters BSs and users in the network to create entities that we named "virtual cells", each comprising a set of BSs and the users they jointly serve. Our model distinguished between two types of channel state information (CSI): the global information about the network which is used in creating clusters of BSs that we call virtual BSs, and the local instantaneous CSI.…”

Section: Introductionmentioning

confidence: 99%

“…Then, the users in the BS clusters look to optimally allocate their power to maximize the cluster sum rate. The resource allocation techniques used in [20]- [22] are successful in reducing interference in the network by jointly allocating power and channels to users in a virtual cell to mitigate the interference within that virtual cell. Nonetheless, the optimization in these prior works does not actively cancel interference for edge users.…”

Section: Introductionmentioning

confidence: 99%

Interference Reduction in Virtual Cell Optimization

Yemini¹,

Erkip²,

Goldsmith³

2020

Preprint

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Virtual cell optimization clusters cells into neighborhoods and performs optimized resource allocation over each neighborhood. In prior works we proposed resource allocation schemes to mitigate the interference caused by transmissions in the same virtual cell. This work aims at mitigating both the interference caused by the transmissions of users in the same virtual cell and the interference between transmissions in different virtual cells. We propose a resource allocation technique that reduces the number of users that cannot achieve their constant guaranteed bit rate, i.e., the "unsatisfied users", in an uplink virtual cell system with cooperative decoding. The proposed scheme requires only the knowledge of the number of users each base station serves and relies on creating the interference graph between base stations at the edges of virtual cells. Allocation of frequency bands to users is based on the number of users each base station would serve in a non cooperative setup. We evaluate the performance of our scheme for a mmWave system. Our numerical results show that our scheme decreases the number of users in the system whose rate falls below the guaranteed rate, set to 128Kpbs, 256Kpbs or 512Kpbs, when compared with our previously proposed optimization methods.

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Virtual Cell Clustering with Optimal Resource Allocation to Maximize Cellular System Capacity

Cited by 10 publications

References 41 publications

GateSelect: A novel Internet gateway selection algorithm for client nodes

GateSelect: A novel Internet gateway selection algorithm for client nodes

Optimal Massive-MIMO-Aided Clustered Base-Station Coordination

Interference Reduction in Virtual Cell Optimization

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