`
`
`
`Second International Conference on Computational Intelligence, Modelling and SimulationSecond International Conference on Computational Intelligence, Modelling and SimulationSecond International Conference on Computational Intelligence, Modelling and Simulation
`
`VoIP Quality Optimization in IP–Multimedia Subsystem (IMS)
`
`Wagdy A. Aziz*, Salwa H. Elramly † and Magdy M. Ibrahim †
`* The Egyptian Company for Mobile Services-Mobinil/Technology Department, Cairo, Egypt, wanis@mobinil.com
`† Faculty of Engineering/Electronics and Communication Engineering Department, Cairo, Egypt
`sramlye@netscape.net and Magdy_Ibrahim@yahoo.com
`
`
`
`
` The E-Model, (ITU-T G.107) [2], is a model that allows
`users to relate Network impairments to voice quality.
`This model allows impairments to be introduced and
`voice quality to be assessed. Three cases are considered
`to demonstrate the effectiveness of optimizing the VoIP
`over IMS network using E-Model.
` New equations were also provided to enhance E-Model
`that can be used to relate packet loss to the level of
`Equipment Impairment (Ie) with different codecs.
` The objective function for all cases is to maximize the
`number of calls that can be active on a link while main-
`taining a minimum level of voice quality (R> 70).
` The cases considered are:
`1. Find voice coder given link bandwidth, packet
`loss level, and link utilization level.
`2. Find voice coder and packet loss level given link
`bandwidth and background link utilization.
`3. Find voice coder and background link utilization
`level given link bandwidth and packet loss level
`OPNET is the optimization tool that is used in this paper.
`
`A. IMS Architecture
`
` IP Multimedia Subsystem is defined by 3rd-Generation
`Partnership Project (3GPP) which defines IMS standards
`as a network domain dedicated to the control and integra-
`tion of multimedia services [1].
` IMS builds on Internet Engineering Task Force (IETF)
`protocols like Session Initiation Protocol (SIP), Session
`Description Protocol (SDP) [3] and Diameter protocol.
`Figure 1 shows the common nodes included in the IMS.
`These nodes are:
`1) P-CSCF (Proxy-CSCF): The P-CSCF is the first
`point of contact between the IMS terminal and the IMS
`network. All the requests initiated by the IMS terminal or
`destined to the IMS terminal traverse the P-CSCF.
` 2) I-CSCF (Interrogating-CSCF): It has an interface to
`the SLF (Subscriber Location Function) and HSS (Home
`Subscriber Server). This interface is based on the Diame-
`ter protocol [4].The I-CSCF retrieves user location in-
`formation and routes the SIP request to the appropriate
`destination, typically an S-CSCF.
` 3) S-CSCF (Serving-CSCF): It maintains a binding be-
`tween the user location and the user’s SIP address of
`record (also known as Public User Identity). Like the I-
`CSCF, the S-CSCF also implements a Diameter interface
`to the HSS.
`
`
`
`
`
`
`Abstract—IP Multimedia Subsystem (IMS) is very impor-
`tant due to the critical role it plays in the Next Generation
`Network (NGN) of the Fixed and Mobile Networks. Voice
`traffic in IMS will be served using Internet Protocol (IP)
`which is called Voice over IP (VoIP). This paper uses the
`"E-Model", (ITU-T G.107), as an optimization tool to select
`network and voice parameters like coding scheme, packet
`loss limitations, and link utilization level in IMS Network.
`The goal is to deliver guaranteed Quality of Service for voice
`while maximizing the number of users served.This optimiza-
`tion can be used to determine the optimal configuration for
`a Voice over IP in IMS network OPNET is the optimization
`tools that is used in this paper. The paper also provides new
`equations can be added to enhance E-Model to relate packet
`loss to the level of Equipment Impairment (Ie) with different
`codecs.
`
`I. INTRODUCTION
`
` The IP Multimedia subsystem (IMS) is an overlay sys-
`tem that is serving the convergence of mobile, wireless
`and fixed broadband data networks into a common net-
`work architecture where all types of data communications
`are hosted in all IP environments using the session initia-
`tion protocol (SIP) protocols infrastructure [1].
` IMS is logically divided into two main communication
`domains, one for data traffic, i.e., real time protocol
`packets consisting of audio, video and data and the
`second one is for SIP signaling traffic.
` This paper focuses on the VoIP Quality of Service over
`IMS using SIP as a signaling protocol.
` Quality is a subjective factor, which makes it difficult
`to measure. Taking an end to end perspective of the net-
`work further complicates the QoS measurements. The
`reasons for low quality voice transmission are due to de-
`grading parameters like delay, packet delay variation,
`codec related impairments like speech compression, echo
`and most importantly packet loss. Large research efforts
`have been made to solve the vital quality of service is-
`sues. In the VoIP end-to end QoS measuring and moni-
`toring area this has resulted in various objective QoS
`measuring models. The output is generally a single quali-
`ty rating correlated to the subjective MOS score.
` Many of the developed models for measuring VoIP
`quality of service are inappropriate for smaller, private
`networks. They may take too much process resource, are
`intrusive on the regular traffic or contain very compli-
`cated test algorithms.
` One of the best models used for measuring VoIP quali-
`ty of service is the E-model, which is a parameter-based
`model.
`
`
`
`978-0-7695-4262-1/10 $26.00 © 2010 IEEE978-0-7695-4262-1/10 $26.00 © 2010 IEEE978-0-7695-4262-1/10 $26.00 © 2010 IEEE
`
`
`DOI 10.1109/CIMSiM.2010.102DOI 10.1109/CIMSiM.2010.102DOI 10.1109/CIMSiM.2010.102
`Authorized licensed use limited to: Parham Hendifar. Downloaded on September 29,2023 at 16:42:23 UTC from IEEE Xplore. Restrictions apply.
`
`
`
`
`
`496546546
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`Smart Mobile Technologies LLC, Exhibit 2036
`Page 1 of 7
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`

`

`models that derive quality estimations from knowledge
`about the network.
` One of the best models used for measuring VoIP quali-
`ty of service is the E-model, which is a parameter-based
`model.
`
`
`
`III. DESCRIPTION OF E-MODEL OPTIMIZATION
`
` The E-Model, (ITU-T G.107) [2] is extremely complex
`with 18 inputs that feed interrelated components. These
`components feed each other and recombine to form an
`output (R).
` The recommendation ITU-T G.108 [6 gives a thorough
`description on how to carry out an E-model QoS calcula-
`tion within VoIP networks
` Due to the complexity of the E-Model, the approach
`used here is to try to identify which E-Model parameters
`are fixed and which parameters are not. In the context of
`this research the only parameters of the E-Model that are
`not fixed are:
`
`
`(cid:131) T and Ta – Delay variables
`(cid:131)
`Ie – Equipment Impairment
`
` Where (T) is the mean one way delay of the echo path,
`(Ta) is the absolute delay in echo free conditions [4]. In
`addition, parameters that affect delay Id and Ie are intro-
`duced:
`
`
`
`
`Fig. 1. IMS Functional Elements.
`
` 4) SIP AS (Application Server): The AS is a SIP entity
`that hosts and executes IP Multimedia Services based on
`SIP.
` 5) The Home Subscriber Server (HSS): contains all the
`user related subscription data required to handle multi-
`media sessions.
`
`B. SIP in IMS
`
` Session Initiation Protocol (SIP) is a prominent proto-
`col (RFC 3261 [5]). SIP has been chosen in IMS to play
`the key role for setting up the session while inter-working
`with other protocol.
` All IP voice and multimedia call signaling in IMS will
`be performed by SIP, end to end, providing a basis for
`rapid new service introductions and integration with fixed
`network IP services.
`
`
`II. RELATED WORK
`
`
` Quality is a subjective factor, which makes it difficult
`to measure. Taking an end to end perspective of the net-
`work further complicates the QoS measurements. The
`reasons for low quality voice transmission are due to de-
`grading parameters like delay, packet delay variation,
`codec related impairments like speech compression, echo
`and most importantly packet loss. Large research efforts
`have been made to solve the vital quality of service is-
`sues. In the VoIP end to end QoS measuring and monitor-
`ing area this has resulted in various objective QoS mea-
`suring models. The output is generally a single quality
`rating correlated to the subjective MOS score.
` These methods are subdivided in three categories: com-
`parison or intrusive methods, absolute estimation models
`also called non-intrusive models and transmission rating
`
`497547547
`
`Idd
`
`(cid:32)
`
`
`
`
`
`With:
`
`
`(cid:131) PL - Packet Loss %
`(cid:131)
`ρ- Link Utilization
`(cid:131) Coder Type
`
` Next, the relationship between these parameters is iden-
`tified. Since, we are making the assumption that the echo
`cancellers are on the end and are very good, we can say
`that T = Ta and Ie is directly related to a particular coding
`scheme and the packet loss ratio.
` According to the above assumption, R-Factor equation
`can be reduced to the following expression:
`
`R = 93.2 – Id (Ta) – Ie (codec, packet loss) (1)
`
`A. To Calculate The Delay Impairment Id [4]:
`
`For Ta (cid:31) 100 ms:
`Id=Idd=0 (2)
`For Ta (cid:33) 100 ms:
`Id=
`(cid:173)
`(cid:11)
`(cid:176)
`1
`25
`(cid:14)
`(cid:174)
`(cid:176)
`(cid:175)
`
` 1
`(cid:12)
`6
` 6
`
`X
`
`(cid:167)
`X
`(cid:170) (cid:14)
`(cid:168)
`3 –
`1
`(cid:171) (cid:172)
`(cid:168)
`3
`(cid:169)
`
`1
`6
`6
`(cid:183)
`(cid:186)
`(cid:184)
`(cid:187) (cid:188)
`(cid:184)
`(cid:185)
`
`(cid:189)
`(cid:176)
`(cid:14)
`2
`(cid:190)
`(cid:176)
`(cid:191)
` (3)
`
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`
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`
`

`

`Ta
`(cid:167)
`log
`(cid:168)
`100
`(cid:169)
`(cid:32)
`log
`2
`
`(cid:183)
`(cid:184)
`(cid:185)
`
`X
`
`
`
`
`
`B. To Calculate Equipment Impairment Ie
`
`The loss impairment Ie captures the distortion of the
`original voice signal due to low-rate codec, and packet
`losses in both the network and the play out buffer. Cur-
`rently, the E-Model can only cope with speech distortion
`introduced by several codecs i.e. G.729 [7] or G.723 [8].
`Specific impairment factor values for codec operation
`under random packet-loss have formerly been treated us-
`ing tabulated, packet-loss dependent Ie-values. Now, the
`Packet-loss Robustness Factor Bpl is defined as codec
`specific value.
`The packet-loss dependent Effective Equipment Im-
`pairment Factor Ie-eff is derived using the codec specific
`value for the Equipment Impairment Factor at zero pack-
`et-loss. Ie and the Packet-loss Robustness Factor Bpl, both
`listed in Table I for several codecs. With the Packet-loss
`Probability Ppl, Ie-eff is calculated using formula (4)
`
`
`
`
`Ie
`
`(cid:16)
`
`eff
`
`(cid:32)
`
`Ie
`
`(cid:14)
`
`(cid:11)
`95
`
`(cid:16)
`
`(cid:12)
`Ie
`
` (4)
`
`Ppl
`Bpl
`Ppl
`(cid:14)
`As can be seen from this formula (4), the Effective
`Equipment Impairment Factor in case of Ppl = 0 (no pack-
`et-loss) is equal to the Ie value defined in Table I.
` Ie represents the effect of degradation introduced by
`codecs, Packet Loss. G.113 provides parameters for use
`in calculating Ie from codec type and Packet Loss rate
`[9].
`
`
`TABLE I Provisional planning values for the equipment impairment
`factor Ie and for packet-loss robustness factor Bpl [9]
`
`
`
`
`
`
` Coming to the VoIP traffic Characterization, Human
`speech is traditionally modeled as sequence of alternate
`talk and silence periods whose durations are exponential-
`ly distributed and referred as to ON-OFF model.
` On the other hand all of the presently available codecs
`with VAD (Voice Activity Detection) have the ability to
`improve the speech quality by reproducing Speakers back
`ground by generating special frame type called SID (Si-
`lence Insert Descriptor). SID frames are generated during
`Voice Inactivity Period.
`C. Mapping R factor Into MOS Scale
`
`We can map R into MOS scale by the following equa-
`tions [2]
` For R < 0:
`
`498548548
`
` MOS = 1 (5)
` For 0 <R <100:
`MOS = 1 + 0.035 R + 7.10-6 R(R-60)(100-R) (6)
` For R > 100:
`MOS = 4.5
` (7)
`IV. PROJECT SETUP
`
` The simulation is done using OPNET simulation tool IT
`Guru Academic Edition 9.1 for VoIP in IMS network us-
`ing SIP Protocol.
` The network consists of IP-Telephones (VoIP or IMS
`Clients) connected to the Internet by routers which act as
`IP gateway, the network is managed by the SIP proxy
`server (act as P-CSCF) which uses the SIP protocol to
`establish the voice calls (VoIP) on the IMS network.
` The links between the routers and the Internet are T1
`with link speed 1.544 Mbps and the links between the
`dialer, dialed, Proxy Server and the routers are 1000 Base-
`x. The idea is to configure the network with a certain pa-
`rameters and run the simulation then getting from the tool
`the result values which used in E-Model equations to
`measure the Quality of service Factor R.
`The objective function for all cases is to maximize the
`number of calls that can be active on a link while main-
`taining a minimum level of voice quality (R). The cases
`considered are:
`1. Find the optimal voice coder given link band-
`width, packet loss level, and background link uti-
`lization level.
`2. Find the optimal voice coder and the optimal
`packet loss level given link bandwidth and back-
`ground link utilization.
`3. Find the optimal voice coder and the optimal
`background link utilization level given link
`bandwidth and packet loss level.
`
`
`
`
`
`
`
`
`Fig .2. Network Topology
`
`
`Table II shows standard parameters for each codec used
`in the analysis
`
`
`
`
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`TABLE II Codec Parameters
`
`
`TABLE IV Codec Parameters for case1-2
`
`
`
`
`
`
`R-Value and Number of Calls Vs. Coder
`
`R-Value
`Number of Calls
`Thershold R-Value
`
`G.711
`
`G.729
`Coder
`
`G.723
`
`
`
`100
`90
`80
`70
`60
`50
`40
`30
`20
`10
`0
`
` Number of Calls
`
`R-Value
`
`
`
`
`
`
`
`Fig. 3. R Value, Number of Calls vs. Coder – case (1)
`B. Case 2 - Optimizing for Coder and Packet Loss Level
`Selection
`
`
`The goal of this case is to find the optimal voice coder
`and the optimal packet loss level given link bandwidth and
`background link utilization.
`Table V contains the parameters used for case 2 of the
`simulation which is according to the ITU-T recommenda-
`tion G.113
`
`Table V Codec Parameters for case 2 [9]
`
`
`
`
`
`
`
`The OPNET simulation is configured by the above pa-
`rameters like the codec bit rate and the packet size and the
`number of voice frames per packet but other values like Ie
`and Bpl are coming from ITU-T G.107 and G.113 for the
`mentioned codecs. The simulation was run for 1 hour, 2
`hours and 4 hours and for the 3 coders G.711, G.729 and
`G.723 with different values of packet loss ratio.
`
`
`
`
`
`
`V. RESULTS
`
`The results are divided into three general cases. For all
`cases, the aim is to maximize the number of calls that can
`be carried on a link while maintaining a minimum voice
`quality level (R > 70).If two combinations produce the
`same number of calls, the highest R value will be consi-
`dered the best selection.
`A. Case 1 - Optimizing for Coder Selection
`
`The goal of this case is to find the optimal voice coder
`given link bandwidth, packet loss level, and background
`link utilization level.
`Table III and Table IV are containing the coding para-
`meters used in Case1 1 of the simulation. OPNET is con-
`figured by these parameters which are according to the
`ITU-T G.107
`
`
`TABLE III Codec Parameters for case1-1 [2] [9]
`
`
`
`For Case 1 with a link speed of 1.544 Mbps, The simu-
`lation was run for 2 hours and 4 hours and in all cases
`G.723.1 gave the max. Number of calls with R value more
`than 70, so G.723.1 was selected as the optimum Coder.
`For G.711 gave the max. Quality of service (Highest R
`value) but the lowest number of calls, G.729 gave middle
`number of calls between G.711 and G.723 and also middle
`R value. As shown in Table 7
`The results of this case are shown in Figure3 not sur-
`prising, as G.723.1 is a more efficient but lower quality of
`voice.
`
`
`
`
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`For the 3 coders G.711, G.729 and G.723 with different
`values of packet loss ratio (0.5 %, 1 %, 1.5 %, 2 % and 5
`%) knowing that the maximum allowable ratio is 2% but
`the simulation was run for PL% equal 5% to observe the
`network behavior in case of big crisis as shown in Figure
`6.The test was run with a link speed of 1.544 Mbps. The
`maximum number of calls was 29 calls. G.723.1 with
`packet loss of 0.5% was the combination chosen and the
`same combination was chosen till packet loss of 1.5 %.
`When packet loss ratio reached 2 %, G.723.1 became
`not feasible as its R value is less than 70 and G.729 with
`packet loss 2% was the combination chosen.
`For packet loss more than 2 % G.723.1 and G.729 be-
`came not feasible and the only feasible coder
`is
`G.711.G.711 with packet loss more than 2 % was the
`combination chosen.
`It is noticed that the most affected parameter in this
`case is the Ie which is expected as the PL is affecting the
`Ie parameters as shown in Figure5.
`
`
`y = 0.084x3 - 0.74x2 + 5.2348x + 15 (10)
`
` Figure 6, Figure 7 and Figure 8 show a graph of the ob-
`served versus the curve fit.
`
`Fig. 6. G.711 Polynomial Fit
`
`Fig. 4. R Value and PL % vs. Coder – case (2)
`
`
`
`
`Fig .7. G.729A Polynomial Fit
`
`
`
`
`
`
`
`
`Fig.10. G.723.1 Polynomial Fit
`
`
`The optimization Results for case (2) is listed in Table
`VI
`
`
`TABLE VI Results of E-Model Optimization Case (2)
`
`
`
`
`500550550
`
`
`
`
`
`Fig.5. PL % and Ie vs. Coder – case (2)
`The following equations were driven and could be add-
`ed to enhance E-Model for some codecs.
` For G.711, the following polynomial was generated,
`where x represents the level of packet loss and y
`represents the level of impairment (Ie).
`
` y
`
` = 0.0046 x3 - 0.156x2 + 3.8x - 0.00035 (8)
`
`
` For G.729A, the following polynomial was generated:
`
` y
`
` = 0.0081x3 - 0.22x2 + 4.4x + 11 (9)
`
`
` For G.723.1, the following polynomial was generated:
`
`
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`

`C. Case 3 – Optimizing for Coder and Background Link
`Utilization
`
`
`The goal of this case is to find the optimal voice coder
`and the optimal background link utilization level given
`link bandwidth and packet loss level.
`The simulation was run for link speed T1 1.544 Mbps
`with variable background link utilization (90%, 92%, 94%
`and 95%) and different coders; the packet loss ratio was
`considered 0 % in all cases. G.711 with Back ground link
`utilization 90 % was the combination chosen as the all
`coders gave the same number of calls and G.711 gave the
`highest R-value which means the highest quality.
` With Back ground link utilization 92%, 94% and 95%,
`G.723.1 became the chosen coder. With back ground link
`utilization 95% G.711 became not feasible as its R value
`was below 70 and the feasible coders were G.729 and
`G.723.1.Looking at Figure11 we can see that all three
`coders were in a feasible range until background link utili-
`zation reached approximately 94%.In Figure11 R remains
`constant for all coders until a point where R declines ra-
`pidly. This is important because it suggest that there is
`optimal link utilization where the system can be operated
`prior to the R value decline. The sudden decrease in R is
`due to the fact that as utilization values approach 100%,
`the delay becomes unbounded, which negatively affects
`the R value.
`It is noticed that at 90% background Link utilization
`that all coders give the same number of calls, so the selec-
`tion in this case is based on the R-Value which is the
`highest for G.711.It is also noticed that the most affected
`parameter in this case is the Id which is expected as the
`Background Link Utilization is affecting the Delay (Id)
`parameters as shown in Figure12.The optimization Result
`for case (3) is listed in Table VII
`
`
`TABLE VII Results of E-Model Optimization Case (3)
`
`
`
`
`D. Discussion of E-Model Optimization Results
`
` All three cases found that G.723.1 is optimal depending
`on the Circumstances. G.723.1 looks more favorable due
`to the fact that G.723.1 uses less bandwidth per audio
`stream.
` Case 2 found that G.723.1 with 0.5%, 1% and 1.5%
`packet loss was optimal but with packet loss 2 % it was
`not feasible and G.729 was the optimum coder.
` Case3 G.711 coder was selected in case of background
`link utilization of 90% but in all other cases till 95%
`G.723.1 was the optimal coder giving the maximum
`number of calls with R Value more than 70%.
` The ability to analyze various coders, delay, packets
`loss and the effect of background link utilization is vital
`to the QoS of VoIP in IMS network. The optimization of
`the E-Model provides a tool that is useful for this pur-
`pose.
`
`
`Table VIII reviews the total results of the optimization
`in the mentioned three cases.
`
`TABLE VIII The total results of the optimization problem
`
`
`
`Fig. 11. R Value, Background link Utilization % vs. Coder – case (3)
`
` Fig. 12. Background Link Utilization % and Id vs. Coder – case (3)
`
`
`
`
`
`
`
`VI. CONCLUSIONS AND FUTURE WORK
`
`
`IP Multimedia Subsystem (IMS) is very important due
`to the critical role it plays in the Next Generation Network
`(NGN) of the Fixed and Mobile Networks. Voice traffic in
`IMS will be served using Internet protocol (IP) which is
`called Voice over IP (VoIP). This paper uses the "E-
`Model" developed by ITU-T as an optimization tool to
`select network and voice parameters like coding scheme,
`packet loss limitations, and link utilization level in IMS
`Network. The goal is to deliver guaranteed Quality of
`Service for voice while maximizing the number of users
`served.This optimization can be used to determine the
`optimal configuration for a voice over IP in IMS network.
`OPNET is the optimization tool that is used in this paper.
`
`Authorized licensed use limited to: Parham Hendifar. Downloaded on September 29,2023 at 16:42:23 UTC from IEEE Xplore. Restrictions apply.
`
`501551551
`
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`
`

`

`[8]
`
`[9]
`
`ITU-T Recommendation G.723, " Dual rate speech coder for
`multimedia communications transmitting at 5.3 and6.3 kbit/s)",
`(05/2006)
` ITU-T Recommendation G.113, “Transmission impairments due
`to speech processing”, (11/2007).
`
`
` The paper also provides new equestrians can be added to
`enhance E-Model to relate packet loss to the level of
`Equipment Impairment (Ie) with different codecs.
` The objective function for all cases is to maximize the
`number of calls that can be active on a link while main-
`taining a minimum level of voice quality (R> 70).
`The cases considered are:
`1. Find voice coder given link bandwidth, packet
` loss level, and link utilization level.
`2. Find voice coder and packet loss level given link
`bandwidth and background link utilization.
`3. Find voice coder and background link utilization
`level given link bandwidth and packet loss level
`OPNET is the optimization tool that is used in this paper.
` In case 1, we found that G.723.1 is the optimized coder
`as it gives the maximum number of calls keeping its R
`factor more than 70. The quality of speech is generally
`higher with G.729A and G.711. But G.729A and G.711
`uses more bandwidth than G.723.1.
` In Case 2, both G.729A and G.723.1 were sensitive to
`changes in packet loss, but G.711 was not as sensitive.
` In Case 3, voice quality was not sensitive to changes in
`the link load until the link load grew above approximately
`94%.
` The tests applied in this paper used a well known codecs
` (G.711, G.729 and G.723.1) and in future we are looking
` forward to apply the same optimization model on Adap-
` tive multi-rate (AMR) codec.
` AMR has been chosen by 3GPP as a mandatory codec
`and is widely used in current 3G mobile handsets. AMR is
`a multi-mode codec with eight modes (AMR475 to
`MR122) with bit rates between 4.75 Kb/s to 12.2 Kb/s. In
`current 3G mobile handsets, a fixed bit rate AMR codec
`(e.g., 12.2 Kb/s) is normally used.
`
`
`ACKNOWLEDGMENT
`
` Thanks to Dr. Mohsen Tantawy from National Tele-
`communication Institute (NTI) in Egypt for his great help
`and support especially in OPNET program.
`
`
`[2]
`
`[5]
`
`REFERENCES
`
`[1] 3GPP, TSG SSA, IP Multimedia Subsystem (IMS) – Stage 2
`(Release 9), TS 23.228 V9.2.0 (2009-12).
`ITU T Recommendation G.107, “The E-model, a Computational
`Model for use in Transmission Planning”, Mar. 2005.
`[3] 3GPP, Internet Protocol (IP) multimedia call control protocol
`based on Session Initiation Protocol (SIP) and Session Description
`Protocol (SDP); Stage 3 (Release 9), TS 24.229 V9.2.0 (2009-12).
`[4] P. Calhoun, J. Loughney, E. Guttman, G. Zorn, and J. Arkko,
`“Diameter Base Protocol.” RFC 3588, Internet Engineering Task
`Force, Sep 2003.
`J. Rosenberg, H. Schulzrinne , G. Camarillo, A. Johnston, J. Peter-
`son, R. Sparks, M. Handley, E. Schooler, “SIP: Session Initiation
`Protocol.” Internet Engineering Task Force, RFC 3261, June 2002.
`ITU T Recommendation G.108, “Application of the E-model: A
`planning guide”, Sep., 1999
`ITU-T Recommendation G.729, "Coding of Speech at 8 kbit/s
`Using Conjugate-Structure Algebraic-Code-Excited Linear-
`Prediction (CS-ACELP)", (01/2007).
`
`[6]
`
`[7]
`
`Authorized licensed use limited to: Parham Hendifar. Downloaded on September 29,2023 at 16:42:23 UTC from IEEE Xplore. Restrictions apply.
`
`502552552
`
`Smart Mobile Technologies LLC, Exhibit 2036
`Page 7 of 7
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