Throughput-optimal resource allocation in LTE-Advanced with distributed antennas

Accongiagioco, Giovanni; Andreozzi, Matteo; Migliorini, Daniele; Stea, Giovanni

doi:10.1016/j.comnet.2013.10.002

Cited by 4 publications

(4 citation statements)

References 18 publications

(21 reference statements)

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“…As ILSs have a well-defined size, any multi-band scheduling algorithm can be adapted to this purpose. As already stated, solving optimally the multi-band version of the most common scheduling algorithms (e.g., MaxC/I and PF) is NP-hard in general (see [28] ). We therefore use a commonplace heuristic, which consists in filling up one ILS at a time, starting from the double-muting one.…”

Section: Heuristic Solution For Small-scale Coordinationmentioning

confidence: 98%

“…one where a MaxC/I allocation has to be made on per-subband CQIs), subbands being replaced by ILSs, with the added complication that the dimension of ILSs is not known in advance, but is obtained as a result, as per constraints (v-vi). Since the multi-band-CQI scheduling problem has been proven to be NP-hard in [28], this one can only be NP-hard as well. In any case, solving it in a TTI's time is out of question, even for a small number of UEs (i.e., [10][11][12][13][14][15][16][17][18][19][20], as shown in [24].…”

Section: Small-scale Coordinationmentioning

confidence: 99%

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Practical large-scale coordinated scheduling in LTE-Advanced networks

et al. 2015

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In LTE-Advanced, the same spectrum can be re-used in neighboring cells, hence coordinated scheduling is employed to improve the overall network performance (cell throughput, fairness, and energy efficiency) by reducing inter-cell interference. In this paper, we advocate that large-scale coordination can be obtained through a layered solution: a cluster of few (i.e., three) cells is coordinated at the first level, and clusters of coordinated cells are then coordinated at a larger scale (e.g., tens of cells). We model both small-scale coordination and large-scale coordination as optimization problems, show that solving them at optimality is prohibitive, and propose two efficient heuristics that achieve good results, and yet are simple enough to be run at every Transmission Time Interval (TTI). Detailed packet-level simulations show that our layered approach outperforms the existing ones, both static and dynamic

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Section: Heuristic Solution For Small-scale Coordinationmentioning

confidence: 98%

Section: Small-scale Coordinationmentioning

confidence: 99%

Practical large-scale coordinated scheduling in LTE-Advanced networks

et al. 2015

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“…Therefore, MaxC/I scheduling can be obtained at a complexity of ( ) log O N N , N being the number of UEs. When per-sub-band CQI are used, however, obtaining the maximum throughput becomes an NP-hard problem, as shown in (Accongiagioco et al, 2013), hence some heuristics are used to obtain suboptimal solutions. Recall that a UE can use one CQI in a TTI (typically, the minimum of all the CQIs in the sub-bands where it is allocated some RBs).…”

Section: Multi-band Schedulingmentioning

confidence: 99%

Simulating LTE/LTE-Advanced Networks with SimuLTE

Virdis

Stea

Nardini

2015

Advances in Intelligent Systems and Computing

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In this work we present SimuLTE, an OMNeT++-based simulator for LTE and LTE-Advanced networks. Following well-established OMNeT++ programming practices, SimuLTE exhibits a fully modular structure, which makes it easy to be extended, verified, and integrated. Moreover, it inherits all the benefits of such a widely used and versatile simulation framework as OMNeT++, i.e., experiment support and seamless integration with the OMNeT++ network modules, such as INET. This allows SimuLTE users to build up mixed scenarios where LTE is only a part of a wider network. This paper describes the architecture of SimuLTE, with particular emphasis on the modeling choices at the MAC layer, where resource scheduling is located. Furthermore, we describe some of the verification and validation efforts and present an example of the performance analysis that can be carried out with SimuLTE

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“…Such schemes cannot scale with the number of UEs or cells, since both the amount of information to be conveyed and the algorithm complexity are infeasibly high. Under these settings, in fact, achieving an optimal result (i.e., a scheme that guarantees the maximum throughput on each TTI) is impossible in practice, since this requires solving to optimality an optimization problem that is too complex for a 1ms-timeframe [8], [9].…”

Section: Introductionmentioning

confidence: 99%