Uplink Capacity of VoIP on LTE System

Haiming Wang Dajie Jiang Esa Tuomaala Nokia Research Center (China) Beijing University of Posts and

Telecommunications Nokia Research Center (China)

Nokia House 1, No.11 He Ping Li Dong Jie, Beijing, 100013, P.R.C

Beijing University of Posts and Telecommunications, Beijing,

100876,P.R.C

Nokia House 1, No.11 He Ping Li Dong Jie, Beijing, 100013, P.R.C

Beijing, China Beijing, China Beijing, China haiming.wang@nokia.com jiangdajie@gmail.com esa.tuomaala@nokia.com

Abstract ─ In this paper, performance of VoIP service on LTE UL system is studied and analyzed via semi-static system level simulations. Simulations show that different scheduling schemes have a big influence on the UL VoIP capacity ── semi-persistent method is quite promising due to its ability to decrease DL signaling overhead and a good performance that is comparable to more advanced methods. The impacts of different VoIP packet sizes, different usage scenarios and different scheduling mechanism are analyzed as well. Those are concluded from the simulation results. Key words─ VoIP, LTE, Capacity, UL

I. INTRODUCTION The UTRAN Long Term Evolution (LTE), which is included in 3GPP Release’08 specification, is being designed to enable higher packet data throughput by means of a new Physical Layer technologies ── OFDMA and SC-FDMA in downlink (DL) and uplink (UL), respectively. Regarded as a stand-alone radio system, LTE has to be able to operate independently of any existing GSM or UTRAN system in the same area. It only operates in packet switched domain. For such an all-IP network, in order to convey speech, the traditional circuit switched (CS) speech has to be replaced by a real-time packet switched voice service called Voice Over IP (VoIP), which will imply cost saving for operators as CS related part of the core network would not be needed anymore. Furthermore, better capacity or coverage with VoIP can be expected as well. As LTE is a new radio system, the capacity and implications of VoIP need to be carefully analyzed. Our focus in this paper is the VoIP performance in LTE UL system. We will provide system simulation results and analysis for the capacity of VoIP on LTE, which will show that VoIP on Rel’08 achieves a capacity significantly higher than that reported for HSUPA [2]. This paper is organized as follows: in section II, the concept of VoIP in LTE system is presented, including the principles of the used scheduling methods. The theoretical analysis on VoIP capacity is shown in section III. Section IV contains the algorithm modeling and simulation assumptions. Capacity results are shown in the section V. Finally, conclusions are drawn in section VI.

II. CONCEPT OF VoIP OVER LTE

In this section, VoIP in LTE is described. The scheduling schemes used in this study are also presented.

A. VoIP over LTE In LTE system, 1ms Transmission Time Interval (TTI) consists of two 0.5ms sub-frames, and each sub-frame has 7 OFDM symbols. 2 symbols out of 14 are reserved for UL pilot transmission, the remaining 12 symbols are used for data and control information transmission. TTI is regarded as the minimal time allocation unit. In frequency domain, a minimal allocation unit is a Resource Block (RB), which consists of 12 sub-carriers (15 kHz per sub-carrier). One VoIP packet can be transmitted with one or multiple RBs within one TTI. Figure 1 illustrates the frame structure in LTE UL.

Figure 1. Frame structure in LTE UL system.

In LTE UL, synchronous Hybrid Automated Repeat Request (HARQ) is the current default assumption. If 3 HARQ processes are defined, it implies a round trip time of 3ms for the fast HARQ. Thus a maximum of 13 retransmissions are possible in order to keep the transmission delay below 40ms. Figure 2 shows the VoIP packet transmission in LTE UL system. A new VoIP packet is received from speech codec every 20 ms. Thus, a new VoIP transmission will occur every 20 TTIs. If the reception is not successful, packet will be transmitted again in the corresponding HARQ process.

Figure 2. VoIP on LTE UL with Synchronous HARQ.

B. Scheduling for VoIP Traffic Scheduling mechanisms are very important for VoIP traffic in order to achieving the required QoS. The characteristics of VoIP traffic are such that a series of fixed-size packets with a

Proceedings of Asia-Pacific Conference on Communications 2007

1-4244-1374-5/07/$25.00 ©2007 IEEE 397

fixed interval are generated. In terms of such VoIP peculiarity, three scheduling options are evaluated in this paper [3].

• Dynamic allocation The fully dynamic scheduling means that the UE sends a resource request in UL for every VoIP packet; Node B allocates UL resources for every retransmission separately by the L1/L2 control signaling. With dynamic scheduling VoIP users can benefit from channel diversity in both time and frequency domains and unused resources due to silent periods as well as due to early termination of HARQ can be easily reallocated to other VoIP users. The main drawback for dynamic scheduling is the large amount of control signaling it requires.

• Persistent Allocation Persistent means that a CS like allocation for VoIP is made. RRC signaling would be used to allocate a time/frequency resource (localized or distributed) as well as a fixed modulation scheme for a VoIP user. The allocation should also include resources required for HARQ retransmissions. The allocation could even be so persistent that HARQ ACK/NACK messages are not sent but instead each packet is sent a fixed number of times (as proposed in [5]). This would result in a fixed FEC scheme instead of an adaptive HARQ scheme. The advantage of this scheme is that it is simple and requires less signaling overhead. However, such scheme can not make full use of resources.

• Semi-persistent Allocation This is a talk spurt based resource allocation. At the beginning of a talk spurt the UE is allocated a persistent time/frequency resource where the UE can send the initial transmissions without receiving UL allocation via the L1/L2 control channel. The allocation information is sent either on L1/L2 control channel, in a MAC control PDU or as an RRC message. All the retransmissions are allocated dynamically using the L1/L2 control channel. The UE monitors the L1/L2 control channel in all or in preconfigured TTIs (DRX). If no valid UL allocation is given to the UE, the UE is allowed to send an initial data transmission using the pre-assigned resource. Since the retransmissions are always scheduled, this scheme allows using adaptive HARQ: the retransmissions can be freely allocated on any available resources, e.g., on those remaining unused by silent users. Some capacity loss may occur due to persistent allocation of the initial transmission.

III. THEORETICAL ANALYSIS Assuming a pure VoIP system in which 100 % time-frequency resources can be occupied for data transmission, VoIP capacity in theory can be roughly estimated as follows. Firstly, UsedTF represents the number of used resources.

TotalTF is the total number of available resources for VoIP

traffic. The unit of UsedTF and TotalTF is TTI-RB block and, thus,

( 20 )*( )TotalTF NumOfTTI per ms NumOfRUs per TTI= (1) Considering 1.25MHz bandwidth (6RB/TTI) and 1 ms TTI, there are 120 TTI-RB blocks. Here usedTF can be written as:

, _ _1

_ , _ _1

(1 )

(1 )

K

Used Act k ave re k kk

L

Non act l ave re l ll

TF N R

N R

ε

ε

=

=

= + ⋅

+ + ⋅

∑

∑ (2)

where K and L stand for the number of the active and non-active users, respectively. _Act kN and _ _Non act kN are the number of needed TTI-RB grids to transmit one speech packet or SID packet of user k under active status and DTX status, respectively. _ _ave re kR and _ _ave re lR are the average retransmission number for the user under active and non-active state, respectively. kε and lε is the ratio of resources for retransmissions to resources for initial transmissions of a specific user in different state. If 1iε = , then it means the same number of frequency resources is used for new transmission and retransmission. Considering of the total resources, obviously

1Used

tal

TFTF ≤ (3)

Combining (1) and (3), the number of supported users per cell can be estimated correspondingly. However, it is hard to use such equation because the detailed parameters are needed for each user. For the rough estimation purpose, the following conditions are set to simplify the estimation: let 1) v be the average activity factor for all the VoIP users, 2) the same average retransmission _ave reR be used for both active and

non-active state for all users, 3) 1k lε ε= = and

, _ ,Act k Non act l aveN N N= = , and 4) the proportion of packets arriving in active and non-active state be p with a default value of 1/ 8p = . By using above setting, let the number of users supported per cell be SupN , when the total number used resources can be depicted as:

_(1 )

((1 ) )U sed ave re ave SupTF R N N

p v p

= + ⋅ ⋅

⋅ − ⋅ + (4)

Combining (3) and (4), and again letting 1/8p = , the number of users supported becomes

_(1 ) (0.875 0.125)tal

Supave re ave

TFNR N v

≤+ ⋅ ⋅ ⋅ +

(5)

The capacity budget of VoIP is calculated in Table 1 for some example parameters. The capacity numbers in Table 1 are just an upper limit of VoIP in terms of resources. In a real multi-cell network, the interference and coverage situation will have some influence on the capacity.

TABLE I. VoIP capacity budget in 1.25MHz (6RU/TTI). _ave reR 0.2 0.4

aveN 1 2 3 1 2 3

v 0.5

SupN 177 88 59 152 76 50

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IV. MODELING AND ASSUMPTION

In this section, modeling of key VoIP features is introduced. Those include VoIP traffic modeling and QoS based outage criterion. For the simulation environment, a semi-static system level simulation methodology and assumptions are summarized. A. VoIP traffic modeling The duration of each VoIP call is sampled from a negative exponential distribution function with an average call length of 60 seconds. Discontinuous transmission (DTX) is simulated assuming 50% probability of transmission and silent periods, i.e., on and off periods. The duration of both on and off periods is negative exponentially distributed with an average 3 seconds. During on periods, a voice encoder generates a payload per VoIP packet of 20 or 32 bytes every 20 ms, respectively, corresponding to a source rate of approximately 7.95 or 12.2Kbps. Additional 8 bytes for headers of RTP/UDP/IP/PDCP/RLC with header compression will be included in each VoIP packet. During off period, a 15 byte SID packet including headers will be generated once every 160 ms interval. Figure 3 illustrates the VoIP traffic model.

Figure 3. VoIP traffic model.

B. QoS based Outage Criterion The outage criterion is introduced to evaluate the performance of VoIP on LTE system. Here, an outage is considered if more than 2% of VoIP packets for one user are not received correctly within the delay budget, i.e. 40ms. Furthermore, VoIP capacity is defined as the maximum number of per sector VoIP users that can be supported without exceeding a 5% outage level. That is,

2%{ 5%}FERi

Total

Nk MAXN

>= < (6)

where TotalN is the total number of users in the system,

2%FERN > the number of users for whom the average FER exceeds 2%, k capacity (Num of user /cell), and i the simulated number of users per cell.

C. Simulator and Environment A semi-static system level simulator where all essential RRM algorithms (HARQ, PC, schedulers etc.) as well as their interactions are modeled is used to investigate the performance of VoIP on LTE UL. This platform includes a detailed

simulation of the users within multiple cells. The fast fading is explicitly modeled for each user according to the TU channel profile. A wrap-around multi-cell layout modeling several layers of interference described in [4] is used in this study for real emulation. Two typical scenarios named as case 1 and 4 in Table II are defined in [1]. The overall channel attenuation in case 4 is less than case 1.

TABLE II. Simulation Cases (Refer to [1]). Scenario CF

(GHz) ISD (m)

Penetration Loss(dB)

Speed (km/h)

BW (MHz)

Case1 2.0 500 20 3 1.25 Case4 0.9 1000 10 3 1.25

Main parameters used in the system simulation are shown in Table III. Fixed 2 RU resources are allocated to each user. QPSK modulation is used.

TABLE III. System simulation parameters. Parameter Value or description

Layout 19 cell sites, 3 sectors per site

Antenna pattern 70 deg (-3 dB) with 20 dB front-to-back ratio

Standard deviation of slow fading 8 dB

Shadowing correlation between cells / sectors 0.5 / 1.0

eNodeB/UE antenna gain 14 dBi / 0 dBi eNodeB receiver 2 antennas

Thermal noise density -174 dBm/Hz Frequency re-use 1 Channel model 6-ray TU

Max UE Tx Power 21 dBm Channel update per sub-frame (0.5 ms)

TTI length 1 ms Control overhead per TTI 11 long blocks/TTI for data

HARQ Max. num of Txs = 4 Num of HARQ processes = 3

Interference Control Semi-static IC Frequency band allocation and

MCS Assignment of 2 RUs (180 kHz

per RU) for one packet Link-to-System interface AVI with realistic CE

Evaluation method

5% outage based on users having < 98% of its speech frames

delivered successfully within 40 ms (PER<2%)

V. SYSTEM-LEVEL SIMULATION RESULTS

In this section, system simulation results are shown to give the VoIP capacity in different scenarios. The impact of different VoIP packet size and different packet scheduling methods are presented for comparison.

A. Capacity for Persistent Allocation The capacity results for persistent scheduling are presented in Figure 4. SID frames are not considered (there are no packets in DTX periods). It can be seen that about 41 and 44 users per sector can be supported at 95% outage threshold in case 1 and case 4, respectively. The reason of such a low capacity is that most resources which are reserved for retransmissions (due to the characteristic of persistent scheduling) are wasted due to early HARQ termination. In the following subsections, persistent scheduling is no longer evaluated due to its limited performance.

399

B. Capacity for AMR 7.95kbps Figure 5 shows the VoIP capacity results for AMR 7.95kbps. For these simulations, SID packet during DTX is modeled and simulated but, for simplicity, using the same number of RB and different MCS. In case 4, about 86 and 82 users per sector can be supported for dynamic and semi-persistent allocation, respectively. Furthermore in case 1, 78 and 77 users per sector are supported, respectively. Thus, semi-persistent allocation with reduced signaling overhead gives almost the same capacity as dynamic allocation. Compared to case 1, nearly 10% higher capacity can be reached in case 4.

C. Capacity for AMR 12.2kbps Figure 6 shows the VoIP capacity results for AMR 12.2kbps. In case 4, 73 and 71 users per sector are supported for dynamic and semi-persistent allocation, respectively. Correspondingly in case 1, about 65 and 63 users per sector are supported. As in AMR 7.95kbps, semi-persistent allocation still gives almost the same capacity as dynamic allocation compared. Comparing the different use scenarios, case 4 has about 10% higher capacity than case 1. Comparison between different AMR rates under the same simulation cases, it is shown that AMR 7.95kbps can reach a capacity of 15-20% higher than AMR 12.2kbps.

30 35 40 45 50

86

88

90

92

94

96

98

100

No. of users/sector

Pr[U

ser

with

PE

R<2

%]

Case 1Case 4

Figure 4. Capacity for persistent allocation.

70 75 80 85 9050

55

60

65

70

75

80

85

90

95

100

No. of users/sector

Pr[

Use

r w

ith P

ER

<2%

]

VoIP Capacity for AMR 7.95K

7.95K-Case4-Dyna7.95K-Case4-SemiP7.95K-Case1-Dyna7.95K-Case1-SemiP

Figure 5. VoIP Capacity for AMR 7.95kbps.

50 55 60 65 70 75 8075

80

85

90

95

100

No. of users/sector

Pr[

Use

r w

ith P

ER

<2%

]

VoIP Capacity for AMR 12.2K

12.2K-Case4-Dyna12.2K-Case4-SemiP12.2K-Case1-Dyna12.2K-Case1-SemiP

Figure 6. VoIP capacity for AMR 7.95kbps.

VI. CONCLUSIONS

The performance of VoIP on LTE UL has been presented and analyzed via the semi-static system level simulations. Pre-defined small macro and micro-cellular environments have been assumed. The overall capacity in micro-cellular environment is about 10% higher than that in macro. The difference between AMR 7.95kbps and AMR 12.2kbpb voice coding results in a gap of 15-20% in system capacity. The results show that the performance of persistent allocation is poor while dynamic allocation achieves the highest capacity if the signaling load is acceptable. With semi-persistent allocation a system capacity fairly close to that of dynamic allocation can be achieved. However, semi-persistent method requires just a fraction of signaling compared to dynamic. Therefore, if the signaling load becomes too high, it is suggested that at least a part of the VoIP users be allocated in semi-persistent fashion.

ACKNOWLEDGMENT

We would like to thank Chen Tao, working at Nokia Technology Platforms for providing help and guidance in setting up the VoIP simulation platform.

REFERENCES

[1] 3GPP TR 25.814. Physical layer aspects for evolved Universal Terrestrial Radio Access (UTRA). V7.1.0 (2006-09)

[2] Tao Chen, Markku Kuusela and Esa Malkamaki. “Uplink Capacity of VoIP on HSUPA”, IEEE 63rd Vehicular Technology Conference, 2006 (VTC 2006-Spring), pp. 451-455

[3] R2-070476, “Scheduling of LTE UL VoIP”, Nokia, 3GPP TSG-RAN WG2 Meeting #57,12 - 16 February 2007

[4] Tuomas Hytönen, “Optimal wrap-around network simulation”, Research Report, Helsinki University of Technology, December 2001

[5] R2-062164, “Uplink Resource Allocation Scheme”, NTT DoCoMo, 3GPP TSG RAN WG2 #54, 28th August – 1st Sept 2006

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