Alleviating cellular network congestion caused by traffic lights Hind ZAARAOUI, Zwi ALTMAN, Tania...

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Alleviating cellular network congestion caused by traffic lights  

Hind ZAARAOUI , Zwi ALTMAN, Tania JIMENEZ, Eitan ALTMAN

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II.

III.

IV.

V.

Definition of the problem

Mobility model

Simulation and results

Resource allocation small-macro cells

Radio modelling

I.

VI. Conclusion and ongoing work

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I. Definition of the problem

𝝀𝟏

Macro cell

Small cell

𝝀𝟐

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II. Mobility model

Overtaking is excluded in the simulation:

The algorithm used in the simulation is therefore:

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III. Radio modelling: instantaneous cell load definition

Throughput of a user located at using modified Shannon formula:

The load density in stationary fixed case ,

The load density in non stationary mobility case

The instantaneous cell load for discrete case

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III. Radio modelling: network performance indicators

Instantaneous mean user throughput:

File transfer time for a user :

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IV. Resource allocation small-macro cells (1/2)

Macro-cell only

𝑚𝑎𝑐𝑟𝑜 :𝑤𝑠𝑚𝑎𝑙𝑙 :∅

Full frequency reuse (macro &

small cells)

𝑤𝑤

Dynamic frequency bandwidth

splitting (macro & small)

(1−𝛿 (𝑡 ) )𝑤

𝛿(𝑡)𝑤

Mean optimal frequency

bandwidth split (macro & small)

(1−𝛿∗ )𝑤

𝛿∗𝑤

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IV. Resource allocation small-macro cells (2/2)

Dynamic frequency bandwidth splitting :

For the case of (proportional fair), we maximize this utility by finding the solution of :

Mean optimal frequency bandwidth split:

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Network and traffic characteristics

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V. Simulation and results (1/2)

Loads comparison

MO

MFqSFqS

Reuse

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V. Simulation and results (1/2)

Mean user throughput in time and mean file transfer time comparison

FqS solution provides a significant gain with respect to MFqS: taking MFqS as reference

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Conclusion and ongoing work

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Scheduling in presence of mobility (1/2)

Normal scheduling

t = 1

scheduling percentile relative to the mobile user = 50%

Normal scheduling

t = 2

scheduling percentile relative to the mobile user < 50%

Dynamical scheduling

t = 1

scheduling percentile relative to the mobile user > 50%

Dynamical scheduling

t = 2

scheduling percentile relative to the mobile user = ?

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Scheduling in presence of mobility (2/2)

1. Normal Scheduling:

- Takes into account only past and present;- The utility function to maximize (-fair scheduler):

: mean past data rate: scheduler factor (variable that maximizes the utility): present data rate that can be received

2. Dynamical Scheduling:- Takes into account future and present;- The utility function to maximize (-fair forecast scheduler):

Multilevel beamforming in mobility scenarios

Context: Massive MIMO technology evolves rapidly towards antenna arrays with larger size, allowing to support multilevel beamforming

Multilevel beamforming is based on hierarchical beam structure which reduces the scheduling complexity

Objective: adapt multilevel beamforming to different mobility scenarios

z

x

yq

- f

f

dx

dz

Thank you for your attention