AMR Voice Quality Improvement Based on PLVA(RAN15.0_Draft a)

AMR Voice Quality Improvement Based on PLVA RAN15.0

Feature Parameter Description

Issue Draft A

Date 2013-01-30

HUAWEI TECHNOLOGIES CO., LTD.

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WCDMA RAN

AMR Voice Quality Improvement Based on PLVA Contents

Issue Draft A (2013-01-30) Huawei Proprietary and Confidential

Copyright Huawei Technologies Co., Ltd

i

Contents

1 About This Document .............................................................................................................. 1-1

1.1 Scope ............................................................................................................................................ 1-1

1.2 Intended Audience......................................................................................................................... 1-1

1.3 Change History .............................................................................................................................. 1-1

2 Overview...................................................................................................................................... 2-1

3 Technical Description .............................................................................................................. 3-1

3.1 AMR Speech Encoding and Decoding .......................................................................................... 3-1

3.2 AMR Speech Decoding Using the Viterbi Algorithm ...................................................................... 3-2

3.3 AMR Speech Decoding Using the PLVA ....................................................................................... 3-3

4 Network Impact .......................................................................................................................... 4-1

5 Engineering Guidelines ........................................................................................................... 5-1

5.1 When to Use AMR Voice Quality Improvement Based on PLVA .................................................. 5-1

5.2 Planning ........................................................................................................................................ 5-1

5.2.1 RF Planning .......................................................................................................................... 5-1

5.2.2 Network Planning ................................................................................................................. 5-1

5.2.3 Hardware Planning ............................................................................................................... 5-1

5.3 Deployment ................................................................................................................................... 5-1

5.3.1 Requirements ....................................................................................................................... 5-1

5.3.2 Activation .............................................................................................................................. 5-2

5.3.3 Activation Observation .......................................................................................................... 5-2

5.3.4 Deactivation .......................................................................................................................... 5-2

5.4 Performance Monitoring ................................................................................................................ 5-2

5.5 Parameter Optimization ................................................................................................................ 5-3

5.6 Troubleshooting ............................................................................................................................. 5-4

6 Parameters.................................................................................................................................. 6-1

7 Counters ...................................................................................................................................... 7-1

8 Glossary ...................................................................................................................................... 8-1

9 References Documents ........................................................................................................... 9-1

WCDMA RAN

AMR Voice Quality Improvement Based on PLVA 1 About This Document

Draft A (2013-01-30) Huawei Proprietary and Confidential


1-1

1 About This Document

1.1 Scope

This document describes the feature WRFD-140201 AMR Voice Quality Improvement Based on PLVA.

1.2 Intended Audience

This document is intended for personnel who:

Are familiar with WCDMA basics

Need to understand the AMR Voice Quality Improvement Based on PLVA feature

Work with Huawei WCDMA products

1.3 Change History

This section provides information about the changes in different document versions.

There are two types of changes, which are defined as follows:

Feature change: refers to a change in the AMR Voice Quality Improvement Based on PLVA feature of a specific product version.

Editorial change: refers to a change in wording or the addition of information that was not described in the earlier version.

Document Versions

The document version is Draft A (2013-01-30).

Draft A (2013-01-30)

This is the draft of the document for RAN15.0.

Compared with issue 02 (2012-07-20) for RAN14.0, this issue incorporates the changes described in the following table.

Change Type

Change Description Parameter Change

Feature change

None None

Editorial change

Optimized engineering guidelines. For details, see chapter 5 "Engineering Guidelines."

None

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AMR Voice Quality Improvement Based on PLVA 2 Overview



2-1

2 Overview

Adaptive Multi-rate(AMR) audio codec is a patented speech coding scheme adopted by the 3GPP as the standard codec for UMTS. Channel encoding for AMR voice services uses convolutional codes. In RAN14.0, Huawei introduces the Parallel List Viterbi Algorithm (PLVA) to decode convolutional codes. The PLVA outperforms the Viterbi algorithm used by most vendors and previous Huawei production, and it improves the voice service quality without affecting power control or compromising system capacity. The feature introduces more robustness to the voice service which is more noticeable in poor radio condition.

AMR Voice Quality Improvement Based on PLVA does not depend on any other feature and can be used with any other feature.

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AMR Voice Quality Improvement Based on PLVA 3 Technical Description



3-1

3 Technical Description

3.1 AMR Speech Encoding and Decoding

At the UMTS physical layer, convolutional codes are used to perform channel encoding for AMR voice services and power control is used to ensure AMR voice quality. Figure 3-1 shows channel encoding and power control for UMTS AMR voice services in the uplink.

Figure 3-1 Channel encoding and power control for UMTS AMR voice services in the uplink

As shown in Figure 3-1, the UE uses convolutional codes to encode AMR voice data and sends the encoded data to the NodeB. The NodeB decodes the received data and performs a cyclic redundancy check (CRC) on the decoded data. The NodeB then sends the decoded data and a CRC indicator (CRCI) to the RNC. The RNC calculates the block error rate (BLER) for outer-loop power control based on all the CRCIs received. The RNC also sends the decoded data and the CRCI to the Core Network (CN) for AMR voice data decoding (source decoding).

The RNC calculates the BLER for outer-loop power control based on the ratio of CRCIs indicating CRC failures to all CRCIs.

AMR voice services include narrowband and wideband AMR voice services. There are three classes of narrowband AMR voice services: A, B, and C. There are two classes of wideband AMR voice services: A and B. The Viterbi algorithm and PLVA apply to both narrowband and wideband AMR voice services. The following description is based on narrowband AMR voice services. Of the three classes of narrowband AMR voice services, class A is of high importance and includes a 12-bit number used for CRC. The other classes are of low importance and CRC is not performed on them. Figure 3-2 shows the separate channel encoding for classes A, B, and C of narrowband AMR services.

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3-2

Figure 3-2 Channel encoding for classes A, B, and C of narrowband AMR services

3.2 AMR Speech Decoding Using the Viterbi Algorithm

The Viterbi algorithm is adopted by most vendors to decode convolutional codes. Figure 3-3 shows the working mechanism of the Viterbi algorithm.

Figure 3-3 Working mechanism of the Viterbi algorithm

The Viterbi algorithm selects the optimal path based on the maximum likelihood theory and exports the data decoded on the optimal path. If the data decoded on the optimal path fails the CRC, the AMR speech codec discards the data. As a result, voice quality deteriorates.

Figure 3-4 shows the narrowband AMR speech decoding using the Viterbi algorithm.

Figure 3-4 Narrowband AMR speech decoding using the Viterbi algorithm

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3-3

As shown in Figure 3-4, the three AMR voice classes are separately decoded by the Viterbi decoder, and the CRC is performed only on the decoded data of class A. The CRCI is used as a reference for outer-loop power control and is also sent as a bad frame indication (BFI) to the AMR speech codec on the CN. If a BFI indicates that a speech frame is erroneous, the AMR speech codec on the CN discards the speech frame to prevent noise.

3.3 AMR Speech Decoding Using the PLVA

The Huawei PLVA is an enhanced CRC-assisted Viterbi algorithm. Figure 3-5 shows the working mechanism of the PLVA.

Figure 3-5 Working mechanism of the PLVA

Instead of selecting only the most optimal path, the PLVA selects the top N optimal paths and performs CRC on the data decoded on these paths. The PLVA only exports data that passes the CRC. If the data decoded on these paths fails the CRC, the PLVA exports the data decoded on the optimal path, which is the same path selected by the Viterbi algorithm. The PLVA outperforms the Viterbi algorithm because it chooses the data decoded on multiple paths, which include the optimal one selected by the Viterbi algorithm. Therefore, when the data decoded by the Viterbi algorithm is correct, the data decoded by the PLVA is also correct. However, when the data decoded by the PLVA is correct, the data decoded by the Viterbi algorithm is not necessarily correct because there are occasions when the data decoded on the optimal path is incorrect whereas the data decoded on other paths selected by the PLVA is correct. In simulations where the PLVA selects four paths, the signal-to-noise ratio (SNR) is 0.2 to 0.8 dB better than that produced by the Viterbi algorithm.

Figure 3-6 shows the narrowband AMR speech decoding using the PLVA.

Figure 3-6 Narrowband AMR speech decoding using the PLVA

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3-4

As shown in Figure 3-6, CRC is performed on the AMR voice data of class A and therefore the data can be decoded using the PLVA. The mean opinion score (MOS) of class A AMR voice data is improved by reducing the BLER. CRC is not performed on classes B and C AMR voice data and therefore classes B and C AMR voice data can only be decoded by using the Viterbi algorithm. The PLVA exports and sends the decoded data, Viterbi CRCI, and PLVA CRCI to the RNC. The Viterbi CRCI is used for outer-loop power control. The PLVA CRCI serves as the BFI, indicating whether a speech frame is erroneous.

The Viterbi CRCI is used for outer-loop power control and the PLVA CRCI serves as the BFI. This dual-CRCI mechanism does not affect power control. Note that this feature decreases the uplink BLER and improves the MOS of AMR voice service by using PLVA, it has no impact on the downlink.

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AMR Voice Quality Improvement Based on PLVA 4 Network Impact



4-1

4 Network Impact

System Capacity

No impact.

Network Performance

This feature improves the MOS of AMR voice services, especially the MOS of AMR voice services in weak coverage areas.

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AMR Voice Quality Improvement Based on PLVA 5 Engineering Guidelines



5-1

5 Engineering Guidelines

5.1 When to Use AMR Voice Quality Improvement Based on PLVA

This feature can improve the AMR voice quality in the uplink, so it can be applied in any scenario that meets the deployment requirements. For details about deployment requirements, see section 5.3.1 "Requirements."

5.2 Planning

5.2.1 RF Planning

RF planning is not required.

5.2.2 Network Planning

Network planning is not required.

5.2.3 Hardware Planning

This feature sets the following requirements on NodeB hardware:

The BTS3812E, BTS3812A and BTS3812AE must be configured with the EULPd board.

The DBS3800 must be configured with the EBBCd board.

The 3900 series base station must be configured with the WBBPd or WBBPf board.

The BTS3902E and BTS3803E support this feature.

The BTS3902E supports this feature.

Currently, for baseband boards, only the EULPd, EBBCd, WBBPd and WBBPf boards support the PLVA feature. When the EULPd, EBBCd, WBBPd or WBBPf board is inserted together with the other types of baseband boards, AMR services cannot obtain the PLVA gain if the AMR services are set up on the other types of baseband boards.

5.3 Deployment

5.3.1 Requirements

Operating environment and hardware requirements

This feature depends on NodeB hardware. For details, see section 5.2.3 "Hardware Planning."

The uplink resource group of the cell must contain a baseband board that supports this feature. To check whether such a baseband board is contained, perform the following steps:

1. For the V200R015 NodeB, run the LST ULOCELL command to check UL Baseband Equipment ID to obtain the uplink resource group of the cell; for the V100R015 NodeB, run the LST LOCELL command to check UL BB Resource Group No. to obtain the uplink resource group of the cell.

2. For the V200R015 NodeB, run the LST BASEBANDEQM command to check Baseband Equipment ID, Cabinet No., Subrack No., and Slot No. to obtain the information about the target baseband board; for the V100R015 NodeB, run the LST ULGROUP command to check UL BB Resource Group No., Cabinet No. of UL Process Unit, Subrack No. of UL Process Unit, and Slot No. of UL Process Unit to obtain the information about the target baseband board.

3. Verify that the baseband board meets the requirements specified in section 5.2.3 "Hardware Planning."

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5-2

Dependencies on Other Features

None

License

The license has been activated. For details about how to activate the license, see License Management Feature Parameter Description.

Feature ID Feature Name License Control Item NE Dimension

WRFD-140201 AMR Voice Quality Improvement Based on PLVA

AMR Voice Quality Improvement Based on PLVA (Per Cell)

NodeB Per cell

Requirements for other devices

The UE must support this feature. Any UE is available. This feature does not have any special requirements for the UE.

5.3.2 Activation

After the license is activated, this feature has been activated.

5.3.3 Activation Observation

The VS.PLVA.User counter informs operators of the number of UEs using this feature. If the value of VS.PLVA.User counter is not 0, this feature is effective.

5.3.4 Deactivation

This feature can be disabled after the license for this feature has been deactivated.

5.4 Performance Monitoring

The gain produced by this feature is reflected by a noticeable increase in the MOS. Take 12.2 kbit/s AMR voice services as an example. In the uplink simulations, if the BLER is 1%, the MOS is increased by about 0.08; if the BLER is greater than 10%, the MOS is increased by about 0.35. (The BLER increase is generally caused by UE power limitation, fast channel change, or strong interference.) In addition, the MOS increase is generally the same under different channel fading conditions.

Figure 5-1 describes the MOS comparison for AMR 12.2k voice (Simulation Result in the uplink).

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5-3

Figure 5-1 MOS comparison for AMR 12.2k voice (Simulation Result in the uplink)

The MOS gain produced by this feature needs to be tested using the MOS test instrument. End-to-end MOS tests can be performed for this feature. However, this feature provides uplink gains. In this case, the test is recommended only for uplink MOS.

Fixed-point test in the lab and drive test are available, which are described as follows:

Fixed-point test in the lab

To conduct a fixed-point test in the lab, perform the following steps:

1. Deactivate this feature and calculate the MOS.

2. Under the same conditions, reactivate this feature and calculate the MOS in the same way.

The MOS gain is obtained by the average value calculated in step 2 minus that calculated in step 1. The MOS gain is about 0.2.

Drive test

To conduct a drive test in the lab, perform the following steps:

3. Determine a test route, deactivate this feature, and calculate the MOS.

4. Under the same conditions, reactivate this feature and calculate the MOS in the same route.

The MOS gain is obtained by the average value calculated in step 2 minus that calculated in step 1. The MOS gain is over 0.1.

In a drive test, the BLER fluctuates significantly. Therefore, the MOS gain obtained in a drive test is different from that obtained in a fixed-point test in the lab.

5.5 Parameter Optimization

Parameter optimization is not required.

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5-4

5.6 Troubleshooting

None.

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AMR Voice Quality Improvement Based on PLVA 6 Parameters



6-1

6 Parameters

There are no specific parameters associated with this feature.

WCDMA RAN

AMR Voice Quality Improvement Based on PLVA 7 Counters



7-1

7 Counters

Table 7-1 Counter description

Counter ID Counter Name Counter Description

NE Feature ID Feature Name

50332258 VS.PLVA.User Numbers of plva user in one cell

NodeB WRFD-140201 AMR Voice Quality Improvement Based on PLVA

WCDMA RAN

AMR Voice Quality Improvement Based on PLVA 8 Glossary



8-1

8 Glossary

For the acronyms, abbreviations, terms, and definitions, see the Glossary.

WCDMA RAN

AMR Voice Quality Improvement Based on PLVA 9 References Documents



9-1

9 References Documents

[1] 3GPP TS 25.101, "User Equipment (UE) radio transmission and reception (FDD)"

[2] 3GPP TS 25.212, "Channel Coding and Multiplexing"

[3] 3GPP TS 26.090v900: "AMR Speech Codec; Speech transcoding," December 2009

1 About This Document1.1 Scope1.2 Intended Audience1.3 Change HistoryDocument VersionsDraft A (2013-01-30)

2 Overview3 Technical Description3.1 AMR Speech Encoding and DecodingFigure 3-1 Channel encoding and power control for UMTS AMR voice services in the uplinkFigure 3-2 Channel encoding for classes A, B, and C of narrowband AMR services

3.2 AMR Speech Decoding Using the Viterbi AlgorithmFigure 3-3 Working mechanism of the Viterbi algorithmFigure 3-4 Narrowband AMR speech decoding using the Viterbi algorithm

3.3 AMR Speech Decoding Using the PLVAFigure 3-5 Working mechanism of the PLVAFigure 3-6 Narrowband AMR speech decoding using the PLVA

4 Network ImpactSystem CapacityNetwork Performance

5 Engineering Guidelines5.1 When to Use AMR Voice Quality Improvement Based on PLVA5.2 Planning5.2.1 RF Planning5.2.2 Network Planning5.2.3 Hardware Planning

5.3 Deployment5.3.1 Requirements1. For the V200R015 NodeB, run the LST ULOCELL command to check UL Baseband Equipment ID to obtain the uplink resource group of the cell; for the V100R015 NodeB, run the LST LOCELL command to check UL BB Resource Group No. to obtain the uplink resourc...2. For the V200R015 NodeB, run the LST BASEBANDEQM command to check Baseband Equipment ID, Cabinet No., Subrack No., and Slot No. to obtain the information about the target baseband board; for the V100R015 NodeB, run the LST ULGROUP command to check U...3. Verify that the baseband board meets the requirements specified in section 5.2.3 "Hardware Planning."

5.3.2 Activation5.3.3 Activation Observation5.3.4 Deactivation

5.4 Performance MonitoringFigure 5-1 MOS comparison for AMR 12.2k voice (Simulation Result in the uplink)1. Deactivate this feature and calculate the MOS.2. Under the same conditions, reactivate this feature and calculate the MOS in the same way.3. Determine a test route, deactivate this feature, and calculate the MOS.4. Under the same conditions, reactivate this feature and calculate the MOS in the same route.

5.5 Parameter Optimization5.6 Troubleshooting

6 Parameters7 CountersTable 7-1 Counter description

8 Glossary9 References Documents[1] 3GPP TS 25.101, "User Equipment (UE) radio transmission and reception (FDD)"[2] 3GPP TS 25.212, "Channel Coding and Multiplexing"[3] 3GPP TS 26.090v900: "AMR Speech Codec; Speech transcoding," December 2009