Genetic algorithm approach for dynamic configuration of Multicast Broadcast Single Frequency Network deployment in LTE

Tuban, N. F.; Azman, Mohd Fahmi; Noordin, Kamarul Ariffin; Ismail, M. F.

doi:10.1109/icimu.2011.6122733

Cited by 9 publications

(14 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To our knowledge, the only previous works dealing with aspects related to the formation or the configuration of MBSFNs are [13,15,9,10,11]. The analysis in [13] assumes eNBs to be distributed according to a random point process and studies the impact of the minimum spatial separation between eNBs on the network outage probability.…”

Section: Previous Work and Contributionmentioning

confidence: 99%

“…The analysis in [13] assumes eNBs to be distributed according to a random point process and studies the impact of the minimum spatial separation between eNBs on the network outage probability. As for [15], it has the merit of having first dealt with the problem of area formation, however it sketches a genetic algorithm that makes several major simplifications. Firstly, the algorithm in [15] does not account for the topological and technical constraints imposed by the eMBMS standard, including the requirement that MBSNF areas be contiguous.…”

Section: Previous Work and Contributionmentioning

confidence: 99%

See 1 more Smart Citation

Area formation and content assignment for LTE broadcasting

et al. 2017

View full text Add to dashboard Cite

Broadcasting and multicasting services in LTE networks are shaping up to be an effective way to provide popular content. A key requirement is that cells are aggregated into areas where a tight time synchronization among transmissions is enforced, so as to broadcast the same radio resources. Our paper addresses a facet of LTE broadcasting that has so far received little attention: the creation of broadcasting areas and the assignment of content to them in order to efficiently exploit radio resources and satisfy user requests. Our original clustering approach, named Single-Content Fusion, achieves these goals by initially aggregating cells into single-content areas and maximizing cell similarity in content interests. Aggregated areas are then merged into multiple-content areas by virtue of similar spatial coverage. We show the validity of our solution pointing out the advantages it provides in comparison to other approaches. We also discuss the impact of various system factors (e.g., number of served users, broadcast data rate, area size) and the scalability of our proposal in large, realistic scenarios with both static and time-varying user interest.

show abstract

Section: Previous Work and Contributionmentioning

confidence: 99%

Section: Previous Work and Contributionmentioning

confidence: 99%

Area formation and content assignment for LTE broadcasting

et al. 2017

View full text Add to dashboard Cite

show abstract

“…There are some works that have applied GAs to the problem of resource allocation in LTE networks, although with different approaches than the one we propose in the present paper. Most of them tackle exclusively the resource allocation problem in DL, [104][105][106][107][108][109][110] while only a few research works focus on the uplink. 111,112 Along with these approaches of allocating resource blocks (RBs), there are other research works that also include the problem of energy saving using GAs, on the allocation of radio resources themselves (for instance, by minimizing emitted power) 110,[113][114][115] or on eNB deployment 116,117 or on redimensioning the number of eNBs for Green LTE.…”

Section: User Assignment In Lte Via Evolutionary Computingmentioning

confidence: 99%

Near‐optimal user assignment in LTE mobile networks with evolutionary computing

Arco-Vega

Cuadra

Portilla-Figueras

et al. 2016

Trans. Emerging Tel. Tech.

View full text Add to dashboard Cite

This paper tackles the problem of users assignment to evolved NodeBs in long‐term evolution mobile networks. We propose a model that aims at assigning users by minimizing a function called download time of the complete system, defined as the minimum time required for all the users in the system to complete their downloads. This strategy helps the network use its resources in a more balanced way, by assigning users from cells (which otherwise would be overloaded when using a simple signal‐to‐interference‐plus‐noise ratio‐based approach) to others with less load. The user‐cell association problem is, in general, a combinatorial NP hard problem. Although other approaches indirectly tackle this complexity by transforming the problem into another whose optimal solution is less difficult (but still with very high computational cost), we tackle directly our download time of the complete system minimization problem by finding an approximate solution provided by a specific implementation of an evolutionary algorithm, which is based on a long‐term evolution domain‐specific initial population along with fully tailored operators adapted to this assignment problem. A variety of experiments in different realistic scenarios point out that the proposed method outperforms the conventional signal‐to‐interference‐plus‐noise ratio‐based and load balancing approaches, specially in urban and dense urban environments (where the assignment is more critical in terms of capacity). We have also tested our approach in simple scenarios that mimic heterogeneous networks and ultra‐dense networks in which the number of users is similar to that of nodes, proving its beneficial properties. Our method is aimed at the design/dimensioning stage and not to the operation stage, and in this sense, it is an off‐line algorithm that could be useful to make better decisions on cost‐effective network dimensioning and upgrading.

show abstract

“…[12] used the logarithm of the allocated rates as the system 229 utility whereas [13] adopted the video quality perceived by the 230 user (e.g., the peak signal-to-noise ratio, PSNR) as the system uti- [19]. In this work, user mobility is not taken into 275 consideration.…”

mentioning

confidence: 99%