Centralized dynamic frequency allocation for cell-edge demand satisfaction in fractional frequency reuse networks

Hina, Maryum; Sohaib, Sarmad

doi:10.1007/s11235-016-0266-z

Cited by 5 publications

(6 citation statements)

References 34 publications

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“…Centralized dynamic frequency allocation technique: In the centralized dynamic allocation of frequencies for cell-edge demand satisfaction, the number of users in the cell-center and the received SINR are used to determine the distance threshold [9] . It has been assumed that users are uniformly distributed in every cell as the intensity is varied, thus allowing for dynamic cell portioning and resource allocation based on demand.…”

Section: Introductionmentioning

confidence: 99%

“…It has been assumed that users are uniformly distributed in every cell as the intensity is varied, thus allowing for dynamic cell portioning and resource allocation based on demand. Full frequency re-use has been implemented for cell-center regions where all the considered cells with varying requirements utilize the same sub-band for the cell-center users [9] . Depending on each cell's center area and the re-use factor, an average of the available sub-bands is selected and used by every cell.…”

Section: Introductionmentioning

confidence: 99%

“…If multiple cells have their cell-center areas surpassing the cell-edge areas, bands proportionate to the maximum normalized area,

, the cell with the biggest normalized cell centre radius is used as the cell centre radius for the network. [9] . The threshold radius is represented by

.…”

Section: Introductionmentioning

confidence: 99%

“…In order to overcome this constraint, proportional allocation of sub-bands based on weight factors is performed on the cell-edge regions. The weight factor,

, partitions the cell-edge band,

, into individual sub-bands,

[9] . This algorithm, as in Table 1 , performs

number of iterations twice and a search operation on the same number of participating cells where

represents the cell-edge re-use factor.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Selection of optimal SINR threshold in fractional frequency reuse by comparing Otsu's and entropy method

Onim¹,

Musyoki²,

Kihato³

2022

Heliyon

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…If multiple cells have their cell-center areas surpassing the cell-edge areas, bands proportionate to the maximum normalized area,

, the cell with the biggest normalized cell centre radius is used as the cell centre radius for the network. [9] . The threshold radius is represented by

.…”

Section: Introductionmentioning

confidence: 99%

“…In order to overcome this constraint, proportional allocation of sub-bands based on weight factors is performed on the cell-edge regions. The weight factor,

, partitions the cell-edge band,

, into individual sub-bands,

[9] . This algorithm, as in Table 1 , performs

number of iterations twice and a search operation on the same number of participating cells where

represents the cell-edge re-use factor.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Selection of optimal SINR threshold in fractional frequency reuse by comparing Otsu's and entropy method

Onim¹,

Musyoki²,

Kihato³

2022

Heliyon

View full text Add to dashboard Cite

“…The authors in [10] propose a centralized dynamic resource allocation. The proposed solution aims to improve the performance of the cell center and cell edge regions by allocating more resources to the cell center users as compared to the fixed FFR scheme.…”

Section: Introductionmentioning

confidence: 99%

Autonomous and dynamic inter-cell interference coordination techniques for future wireless networks

Ezzaouia

Gueguen

Yassin

et al. 2017

2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

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Inter-Cell Interference Coordination (ICIC) techniques are proposed as solutions to alleviate the negative impact of interference on system performance, while enhancing the provided Quality of Service (QoS). Typically, the available bandwidth is divided into inner and edge sub-bands. Users are also classified into interior and edge users. The available resources in each zone are exclusively allocated to users belonging to this zone. Mobile users classification is usually based on a threshold that can be either a given mean SINR value or a given distance. However, ICIC approaches based on these static parameters cannot efficiently manage non-homogeneous distribution of users. In this paper, we introduce a dynamic handoff algorithm that aims to adapt static ICIC schemes to uneven distribution of users. Our new solution dynamically computes the classification of active users into interior and edge users, based on a heuristic load balancing algorithm. In our proposal, each cell autonomously reconfigures its bandwidth allocation constraints without modifying bandwidth repartition across the cellular network. This makes the solution well adapted to the non-uniform repartition of users at the multicell scale. Simulation results show that the proposed scheme improves bandwidth usage, reduces packet delay, and increases user satisfaction compared to state-of-the-art ICIC techniques.

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An intra–inter-cell device-to-device communication scheme to enhance 5G network throughput with delay modeling

et al. 2018

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Centralized dynamic frequency allocation for cell-edge demand satisfaction in fractional frequency reuse networks

Cited by 5 publications

References 34 publications

Selection of optimal SINR threshold in fractional frequency reuse by comparing Otsu's and entropy method

Selection of optimal SINR threshold in fractional frequency reuse by comparing Otsu's and entropy method

Autonomous and dynamic inter-cell interference coordination techniques for future wireless networks

An intra–inter-cell device-to-device communication scheme to enhance 5G network throughput with delay modeling

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