SIR distribution analysis in cellular networks considering the joint impact of path-loss, shadowing and fast fading

Cheikh, Dorra Ben; Kélif, Jean-Marc; Coupechoux, Marceau; Godlewski, Philippe

doi:10.1186/1687-1499-2011-137

Cited by 33 publications

(12 citation statements)

References 14 publications

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“…The outage probability taking into account the collective impact of FF and PL for CEU located at a distance ( r ) from operating BS is expressed as follows:

normalρ ((), CEU' normals SIRp β) = 1 - \frac{1}{{((), \frac{λ}{r^{- η}} β + 1)}^{v}},

where

v = \frac{true}{{((), \sum_{J = 1}^{N} r_{J}^{- η})}^{2}}

and

λ = \frac{true}{\sum_{J = 1}^{N} r_{J}^{- 2 η}}

.…”

Section: Different Metrics For Evaluating the Performance Of Each Systemmentioning

confidence: 99%

Analysis and comparison of different cooperative cellular networks

Mahmoud

Elgazzar

Hashima

et al. 2020

Int J Communication

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This paper addresses cochannel interference (CCI) in mobile networks. So enhancements of network performance by decreasing CCI are assessed using four diverse interference reduction techniques. These techniques signify traditional sectored fractional frequency reuse (FFR), sectored FFR with beamforming (BF), relay-assisted (R-A) sectored FFR, and R-A sectored FFR with BF technique. Additionally, each BF cooperative technique applies the vertical BF, threedimensional (3D) BF, and horizontal BF. Consequently, sectored FFR with BF contains three cases. These cases indicate sectored FFR applies horizontal BF, sectored FFR deploys vertical BF, and sectored FFR uses 3D BF. Furthermore, there are three different arrangements of applying BF in R-A sectored FFR with BF. These arrangements signify that relay station (RS) employs BF only, base station (BS) uses BF only, and both RS and BS apply BF. Therefore, each arrangement consists of three different cases according to the applied BF technique. Consequently, nine dissimilar cases are considered. Also, a comparison of all cases in different techniques is introduced to enhance the network performance. Analytical treatments are conducted. As a result, closed-form expressions (CFEs) for worst cases cell-center user's (CCU's) signal-to-interference ratio (SIR), cell-edge user's (CEU's) SIR, and inner radius (IR) are implemented. These closed forms are used to complete the comparison of all techniques using numerous performance evaluation metrics. The results show, that as unpredicted, the performance of R-A sectored FFR is close to that of R-A sectored FFR BF in low SIR threshold and high path-loss exponent (PLE) ranges. Therefore, R-A sectored FFR is preferred to be used from the perspectives of network cost and power consumption. Furthermore, vertical BF shows performance close to that of 3D BF in low PLE range. Consequently, using vertical BF is preferable with regard to the energy preservation and network budget. Moreover, it is noticed that BS that applies BF arrangement outperforms other arrangements when vertical or horizontal BF technique is applied. Additionally, the arrangement of both RS and BS that apply BF is superior to the other arrangements when 3D BF is used. But, as expected, it does worse than the others if the other BF techniques are applied. The work results achieve much higher CEU SIR enhancement. Therefore, the probability of outage is decreased. Then, rate of served users by the network is communication systems, cooperative cellular systems, correction factor, interference reduction techniques, relay-assisted networks | INTRODUCTIONThe main issue which restricts achieving great system performance in cellular networks (CNs) is the cochannel interference (CCI) matter. 1 Therefore, fractional frequency reuse (FFR) technique is addressed to resolve this problem. This technique divides each cell into outer and inner parts. Furthermore, inner zone serves cell-center users (CCUs) and uses frequency reuse factor (FRF) of one. Moreover, the outer zone deploys F...

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“…The outage probability taking into account the collective impact of FF and PL for CEU located at a distance ( r ) from operating BS is expressed as follows:

normalρ ((), CEU' normals SIRp β) = 1 - \frac{1}{{((), \frac{λ}{r^{- η}} β + 1)}^{v}},

where

v = \frac{true}{{((), \sum_{J = 1}^{N} r_{J}^{- η})}^{2}}

and

λ = \frac{true}{\sum_{J = 1}^{N} r_{J}^{- 2 η}}

.…”

Section: Different Metrics For Evaluating the Performance Of Each Systemmentioning

confidence: 99%

Analysis and comparison of different cooperative cellular networks

Mahmoud

Elgazzar

Hashima

et al. 2020

Int J Communication

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“…For the sake of further developments, we exploit the approximation proposed by authors of [32], [33], [34] for the sum of interferers powers in (3):…”

Section: Relay and Direct Link Modelsmentioning

confidence: 99%

Scheduling Impact on the Performance of Relay-Enhanced LTE-A Networks

Minelli

Coupechoux

et al. 2016

IEEE Trans. Veh. Technol.

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This paper studies the performance of two traditional schedulers, Proportional Fair (PF) and Round Robin (RR), in the context of relay-enhanced LTE-A networks. These two schedulers are indeed natural candidates for implementation in relays nodes (RN) and, following the results obtained in singlehop networks, mobile operators could be tempted to adopt PF because of the good trade-off it offers between cell capacity and fairness. Based on a statistical throughput evaluation model, we show that this is not necessarily the right option. The number of RNs, their locations in the cell, and the backhaul link quality have indeed a decisive influence on the scheduler choice. In some scenarios, it is even not desirable to deploy relays as they degrade the network performance compared to the no relay case. For the purpose of performance evaluation, we develop a realistic and computationally tractable statistical network model that takes into account fast fading, multiple interferers, cell range expansion bias, backhaul link quality, and traffic load. We also propose an optimization of the radio frame structure and a sub-optimal RN placement scheme in order to fairly compare RR and PF.

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“…(21). The combined fading and shadowing terms in the interference are assumed to not significantly affect the aggregated value [36].…”

Section: Appendix C Aggregate Interference Expressionmentioning

confidence: 99%

Interference Allocation Scheduler for Green Multimedia Delivery

Wang

Guo

Khirallah

et al. 2014

IEEE Trans. Veh. Technol.

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One of the key challenges in wireless networking is how to allocate the available radio resources in order to maximise key service delivery parameters such as the aggregate throughput and the multimedia quality of experience (QoE). We propose a novel and effective scheduling policy that allocates resource blocks, such that interference power is shifted towards capacity-saturated users, while improving the throughput of unsaturated users. The highlight of the research is that the proposed scheme can dramatically improve the performance of cells that have a high discrepancy in its signal-to-noise-ratio (SNR) distribution, which is typical in urban areas. The results show that a \emph{free-lunch} solution is possible, whereby for a negligible performance degradation in the saturated users, a large improvement in the non-saturated users can be obtained. However, on average, the number of free-lunch user pairings are low. By relaxing the degradation constraints, the \emph{non-free-lunch} solution can yield a greater multi-user throughput gain. Motivated by surge in mobile multimedia traffic, we further demonstrate that the proposed scheduling may have a profound impact on both energy efficiency and QoE of multimedia service delivery.Comment: 29 pages, 9 figure

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SIR distribution analysis in cellular networks considering the joint impact of path-loss, shadowing and fast fading

Cited by 33 publications

References 14 publications

Analysis and comparison of different cooperative cellular networks

Analysis and comparison of different cooperative cellular networks

Scheduling Impact on the Performance of Relay-Enhanced LTE-A Networks

Interference Allocation Scheduler for Green Multimedia Delivery

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