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Performance of VoLTE and Data Traffic in LTE Heterogeneous Networks

報告人 :蘇蕙蕙指導教授 :陳偉業班級 :碩資管二甲學號 :MA390204

Ref: Ozcan Ozturk, Madhavan Vajapeyam(2013), “ Performance of VoLTE and Data Traffic in LTE Heterogeneous Networks , ” , Globecom - Communications QoS, Reliability and Modelling Symposium .

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Abstract INTRODUCTION BACKGROUND RESULTS AND ANALYSIS CONCLUSION

Outline

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VoLTE (Voice over LTE)◦ provide voice services.◦ increasing need for much higher data capacity as a result of

smartphone proliferation. VoLTE and data users

◦ evaluate the performance of LTE Downlink. data performance and VoLTE capacity

◦ HetNet with Pico cell range expansion significantly improves both the system.

Abstract

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The LTE radio access downlink system performance when both data and voice users are present.

INTRODUCTION

In Section II a background on the VoLTE considered scenarios are provided.

In Section III the simulation model and assumptions are discussed.

In Section IV we present the simulation results with analyses.

Section V includes concluding remarks.

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BACKGROUND

The advantage of VoLTE

• Reuses the LTE radio access to carry voice traffic.• Utilizes the IP Multimedia Subsystem (IMS) in the core

network which can support richer media services.• That LTE can provide significant capacity at the required

QoS.

SPS• The usual mode of scheduling in LTE is dynamic.• Downlink (DL) and Uplink (UL) assignments are

signaled on every subframe on the Physical Downlink Control Channel (PDCCH).

HetNet• The deployment of base stations (eNB) with lower power

such as Picos and Femtos is envisioned.• A key solution to increase the system capacity to meet the

(exponentially increasing) data traffic.

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MODEL AND ASSUMPTIONS The channel model and cell layout are based on 3GPP

simulation D1 model for LTE , with minor modifications. Main simulation parameters are summarized in Table I.

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A. Scheduler◦ The downlink scheduling uses a dynamic sub-band scheduler.◦ MIMO is enabled for all users and Discontinuous Reception

(DRX) is disabled for all users.◦ Each scheduled user is assigned a PDCCH resource to signal

the transport format and the resource allocation. For the availability of PDCCH resources, two options were simulated: Up to 5 PDCCH (control channel limitation). No limit on the number of PDCCH available.

MODEL AND ASSUMPTIONS

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B. VoLTE◦ VoLTE traffic is modeled using a two-state Markov model

based on AMR 12.65 wideband vocoder.◦ Assume that

Robust Header Compression (RoHC) is used which reduces the UDP/IP/PDCP header size to 3 bytes.

The VoLTE frames are not segmented or bundled at the source; however these may occur due to scheduling choices of the TB sizes for a user.

◦ The system capacity for VoLTE is reached when the number of users in outage is more than 5% of the total VoLTE users.

MODEL AND ASSUMPTIONS

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C. SPS◦ modeled by assigning static RBs to VoLTE users in active

state.◦ When a full frame voice frame is scheduled for the first time

for a user, an SPS grant of 2RBs is scheduled with periodicity of 20ms.

◦ SPS grants are given higher priority over other VoLTE transmissions

MODEL AND ASSUMPTIONS

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D. HetNet◦ no association bias is used so that users are served by the best

cell in terms of DL received power.◦ In order to enable CRE, two association biases of 9dB and

16dB were simulated, corresponding to different Pico cell range expansion and amounts of offloading.

◦ Three options of (6, 2), (5,3), and (4, 4) were tried for both 9dB and 16dB biases.

MODEL AND ASSUMPTIONS A. Macro Only

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The simulation duration was 20 seconds. Performance statistics were collected for VoLTE packets (delay, dropped, lost), FB throughput, and PDCCH and RB usage.

MODEL AND ASSUMPTIONS A. Macro Only

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A. Macro Only◦ FB user throughput comparing the Macro case is shown in

Table II.

MODEL AND ASSUMPTIONS A. Macro Only

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The impact of VoLTE users on FB performance is mainly through two aspects: ◦ the main cause of FB throughput decline with increased

number of VoLTE users.◦ Can be alleviated to some degree by relaxing the absolute

priority of VoLTE users.

MODEL AND ASSUMPTIONS A. Macro Only

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HetNet can provide significant gains for both VoLTE and FB.◦ The offloading of users to Pico cells◦ Reduced control channel limitation

RESULTS AND ANALYSISB. HetNet

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Table III shows the gains of HetNet over Macro usingdifferent CRE biases for 5 PDCCH limitation.

RESULTS AND ANALYSISB. HetNet

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Table IV shows the gains without PDCCH limitation.

RESULTS AND ANALYSISB. HetNet

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Fig 3 shows the edge and median user throughput with 5 PDCCH limit for 0dB bias.

It is seen that the Pico users have very good performance compared to the Macro users.

RESULTS AND ANALYSISB. HetNet

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This can be seen by comparing Fig. 5 and Fig. 6 where the Macro 5% and median throughputs are always higher than Pico ones in Fig.6 and vice versa in Fig.5.

RESULTS AND ANALYSIS

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A further comparison can be seen from the user throughput CDF curves Fig. 7 and Fig. 8.

RESULTS AND ANALYSIS

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SPS provides gains similar to no PDCCH limitation for the FB performance as shown in Fig.2. ◦ Even though the allocation of RBs is fixed and channel

insensitive for SPS, this under-utilization has little impact on FB performance.

RESULTS AND ANALYSIS

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The VoLTE capacity based on outage criteria for the 5 PDCCH was limited by this control channel bound in all cases except for SPS. These are shown in Table V.

RESULTS AND ANALYSIS C. The VoLTE Capacity

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VoLTE capacity would be higher if there were no data users in the system since, even though the scheduler gives higher priority to VoLTE users within a cell, the data users generate additional inter-cell interference.

RESULTS AND ANALYSIS C. The VoLTE Capacity

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LTE-Advanced systems◦ the performance of mixed VoLTE and data traffic.

The simulation results show◦ the data throughput decreases almost linearly.◦ the number of VoLTE users increases.

Control channel capacity is limited.◦ data users have less multi-user diversity gains due to PDCCH

availability◦ cannot be scheduled due to PDCCH blocking.

CONCLUSION(1/3)

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The implementation of SPS◦ help with the control channel limitation issue.

The VoLTE capacity is less◦ obtained under dynamic scheduling.

HetNet◦ provide significant gains by offloading the users to Pico cells.◦ alleviating the PDCCH limitation.

CONCLUSION(2/3)

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A positive CRE bias and ABS ◦ partitioning can provide gains for both data throughput. ◦ VoLTE capacity where the data gain increases with more

VoLTE users. Found by simulation

◦ the optimal partitioning choices for the two bias options.◦ Consistent with offloading statistics.

CONCLUSION(3/3)

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THE END