Combining dynamic clustering and scheduling for coordinated multi-point transmission in LTE

Scholz, Sebastian

doi:10.1109/pimrc.2017.8292176

Cited by 3 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Greedy algorithms based approaches have been widely used in network-centric clustering algorithms, e.g. [8]- [12]. They are based on the idea of sequentially adding the best BSs to the cluster up to a certain maximum cluster size.…”

Section: A Related Workmentioning

confidence: 99%

“…In [11], a dynamic BS clustering algorithm has been proposed based on maximizing the weighted sum rate, using a greedy iterative algorithm. This clustering is combined with a scheduling algorithm and evaluated with dynamic traffic models in [12]. However, greedy search method based clustering algorithms may not provide the optimal cluster for group communications, since the cluster must be designed based on all group users performance.…”

Section: A Related Workmentioning

confidence: 99%

“…Otherwise, a new vertex is added to S and some vertices are removed so that S becomes a corral. The algorithm thus proceeds by major cycles (steps 4-19) and every major cycles possibly involves several minor cycles (steps [8][9][10][11][12][13][14][15][16][17]. At the beginning of a major cycle (step 5), we have a corral S together with its affine minimizer x ∈ conv(S).…”

Section: Lemma 3 ( [23]mentioning

confidence: 99%

“…2) Greedy Clustering: The greedy algorithm has been widely used in the literature on clustering for multi-point transmissions, see e.g. [8]- [12]. For comparison with GCCA, we thus adapt the greedy approach to our context in order to find an approximate minimizer of the function Ψ U for a given group of users U and a set of weights ω ∈ R n .…”

Section: Lemma 3 ( [23]mentioning

confidence: 99%

See 3 more Smart Citations

A Dynamic Clustering Algorithm for Multi-Point Transmissions in Mission-Critical Communications

Daher

Coupechoux

Godlewski

et al. 2020

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

Reliable group video call is one of the main services offered by future Mission-Critical Communications (MCC). To support its requirements, coordinated multi-point transmission in multi-cell environments is an attractive feature for MCC over Multimedia Broadcast Multicast Services owing to its potential for coverage improvement and multicast transmission. In such a scheme, full cooperation among all cells of an area achieves the highest cooperative gain, but has stringent impact on system capacity. A trade-off in the cluster's size of serving cells thus arises between high Signal to Interference plus Noise Ratio (SINR) and network capacity. In this paper, we formulate an optimization problem to maintain an acceptable system blocking probability, while maximizing the average SINR of the multicast group users. For every multicast group to be served, a dynamic cluster of cells is selected based on the minimization of a submodular function that takes into account the traffic in every cell through some weights and the average SINR achieved by the group users. Traffic weights are then optimized using a modified Nelder-Mead simplex method with the objective of tracking a blocking probability threshold. The proposed clustering scheme is compared to full cooperation and to Single-Cell Point-To-Multipoint (SC-PTM) schemes. Results show that dynamic clustering offers the best trade-off between coverage and capacity for MCC.

show abstract

Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Section: Lemma 3 ( [23]mentioning

confidence: 99%

Section: Lemma 3 ( [23]mentioning

confidence: 99%

See 2 more Smart Citations

A Dynamic Clustering Algorithm for Multi-Point Transmissions in Mission-Critical Communications

Daher

Coupechoux

Godlewski

et al. 2020

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

show abstract

“…It will then be pruned at required level, creating disjointed clusters inside the cellular network. Clustering method includes (i) static clustering [9], (ii) semi-static clustering [10], and (iii) dynamic clustering [11]. Regardless of the advantage offered by clustering, a bad cluster design will increase interference.…”

Section: B Clusteringmentioning

confidence: 99%

Fair Channel Allocation Scheme for Base Station Cooperative Communication in LTE Mobile Network

Ismail*,

Nordin,

Abdullah

et al. 2020

IJRTE

View full text Add to dashboard Cite

 Abstract : Unjust provision of channels by base station greatly affects Mobile subscribers. A standard cluster, would be able to serve Many User Equipments (UEs). A typical cluster would contain 3, 7 19, or 21 cells. An issue of ambiguity exist in the demarcation boundary of adjacent cells, thus, radio transmission in a cell from a particular eNode Base Station (eNBs) may leak into neighbouring cells, which causes interferences. Furthermore, the eNBs geographical location is sensitive to obstructions such as towering buildings. The absence of line of sight has a major impact on radio signals, as this would amplify the loss of propagated radio signals, leading to weaken signal strength at the transmitter, that ultimately affecting current the Fixed Channel Allocation (FCA) technique. Despite the effort for fair channel through the current mechanism, users on the edge of the cell experience unfairness. The primary cause for this can be traced to poor received signal power. There are two considered UEs clustered in this simulation scenarios, which is proposed in this paper: (i) random fixed UEs and (ii) 5 step move UEs. A combination of static and dynamic clustering is proposed, thus leading to enhanced channel allocation. From the results, there is a drastic reduction in inter-cell interference, which would increase the performance of the cellular network to become ideal.

show abstract

Coordinated Multi-Point Transmission in 5G and Beyond Heterogeneous Networks

Irram

Ali

Maqbool

et al. 2020

2020 IEEE 23rd International Multitopic Conference (INMIC)

View full text Add to dashboard Cite

Combining dynamic clustering and scheduling for coordinated multi-point transmission in LTE

Cited by 3 publications

References 14 publications

A Dynamic Clustering Algorithm for Multi-Point Transmissions in Mission-Critical Communications

A Dynamic Clustering Algorithm for Multi-Point Transmissions in Mission-Critical Communications

Fair Channel Allocation Scheme for Base Station Cooperative Communication in LTE Mobile Network

Coordinated Multi-Point Transmission in 5G and Beyond Heterogeneous Networks

Contact Info

Product

Resources

About