AI赋能的实时音频信源信道联合编码研究

周通; 陈宏智; 许佳龙; 孙鹏; 姜大洁; 刘健康

doi:10.11999/JEIT260379

AI赋能的实时音频信源信道联合编码研究

doi: 10.11999/JEIT260379 cstr: 32379.14.JEIT260379

维沃软件技术有限公司北京 100015

详细信息

作者简介:
周通：女，研究方向为通信与AI融合技术

陈宏智：男，研究方向为通信与AI融合技术、AI感知辅助通信

许佳龙：男，研究方向为基于AI的联合信源信道编码、基于AI的无线通信物理层技术

孙鹏：男，高级工程师，研究方向为massive MIMO、AI等

姜大洁：男，高级工程师，研究方向为通感一体化、AI与通信结合等

刘健康：男，研究方向为数据面、IoT-NTN、语音AI Codec等

通讯作者:
周通　tong.zhou@vivo.com

中图分类号: TN926.1
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出版历程
- 收稿日期: 2026-03-31
- 修回日期: 2026-07-08
- 录用日期: 2026-07-08
- 网络出版日期: 2026-07-22

Research on AI-Enabled Real-Time Audio Joint Source-Channel Coding

vivo Mobile Communication Co. Ltd., Beijing 100015, China

摘要

摘要: 目前，第3代合作伙伴计划(3rd Generation Partnership Project, 3GPP)的业务与系统技术规范组第4工作组(TSG SA working group 4, SA4) 已经开始研究基于人工智能(Artificial Intelligence, AI)的语音编解码器。该文首次以3GPP地球静止轨道(Geostationary Earth Orbit, GEO)语音典型的物理层参数配置与目前SA4正在研究的Descript音频编解码器(Descript Audio Codec, DAC)作为评估基线，保证了基线结果的公平性，并首次提出了总功率限制的DAC信源信道调制联合优化方案、恒模限制的DAC信源信道调制联合优化方案和DAC信源信道联合编解码方案。在语音质量可接受的前提下，所提方案相比于基线方案有2.5～4 dB的覆盖增益。以期为GEO语音的后续研究提供有益思路。
- GEO语音 /
- 信源信道联合编码 /
- 联合信源信道编码调制 /
- AI
Abstract: The 3rd Generation Partnership Project (3GPP) Technical Specification Group Service and System Aspects Working Group 4 (TSG SA Working Group 4, SA4) is currently investigating Artificial Intelligence (AI)-based speech codecs. Based on the Descript Audio Codec (DAC) under investigation by SA4, this paper proposes three AI-enabled transmission schemes: a Total Power Constrained (TPC) DAC Joint Source-Channel Coding and Modulation (DAC-JSCCM) scheme, a Constant-Envelope Constrained (CEC) DAC-JSCCM scheme, and a DAC Joint Source-Channel Coding (DAC-JSCC) scheme. The proposed schemes are evaluated using the typical physical-layer parameter configuration for 3GPP Geostationary Earth Orbit (GEO) voice communications. The results provide useful guidance for future research on GEO voice communications. Objective Joint Source-Channel Coding (JSCC) has attracted increasing attention in both academia and industry. Academic research has primarily focused on video, image, and audio transmission, whereas industrial research has mainly considered Channel State Information (CSI) as the source. The limited industrial interest in JSCC for video and image transmission is mainly attributed to two factors. First, video and image coding standards are generally developed by external organizations, such as the Moving Picture Experts Group (MPEG) and the Joint Photographic Experts Group (JPEG), rather than by 3GPP. Second, application-layer JSCC is limited by architectural challenges because the channel information available at the application layer is often outdated, reducing its potential gain. Audio differs from video and images because speech coding is developed within 3GPP, and SA4 is currently investigating AI-based speech codecs. In GEO voice communications, satellites remain nearly stationary relative to ground stations, resulting in slowly varying channels. Therefore, physical-layer CSI can be reliably delivered to the application layer, avoiding outdated channel information. These characteristics make JSCC for audio a promising research direction within 3GPP. Methods The typical physical-layer parameter configuration for 3GPP GEO voice communications and the DAC under investigation by SA4 are first adopted as the evaluation baseline to ensure a fair performance comparison. Three AI-enabled transmission schemes are then proposed for low-bitrate audio communications. First, the TPC DAC-JSCCM scheme jointly optimizes source coding, channel coding, and modulation to maximize transmission gain. Second, to reduce the high Peak-to-Average Power Ratio (PAPR) associated with the TPC scheme, the CEC DAC-JSCCM scheme is proposed. Finally, because transmitting modulation symbols within the Real-time Transport Protocol (RTP) payload requires substantial modifications to the existing protocol, the DAC-JSCC scheme is proposed to retain bit-sequence transmission in the RTP payload while remaining compatible with the current protocol architecture. Results and Discussions Baseline scheme 1 is first evaluated through physical-layer link-level simulations to establish the relationship between Signal-to-Noise Ratio (SNR) and Block Error Rate (BLER) for 64-bit packets encoded with a rate-1/3 Turbo code. Assuming that the error rate of an audio frame is equal to the corresponding BLER, the transmission error rate of an RTP packet containing L audio frames is calculated. According to the existing transmission mechanism, an RTP packet is discarded if any audio frame within the packet is received incorrectly. In real-time communication, Voice over Internet Protocol (VoIP), and speech enhancement applications, a Perceptual Evaluation of Speech Quality (PESQ) score of 2.5 is generally regarded as the minimum acceptable speech quality threshold. Therefore, PESQ = 2.5 is selected as the reference point for GEO voice communications. At this threshold, both the TPC DAC-JSCCM and CEC DAC-JSCCM schemes achieve an approximately 4 dB coverage gain over baseline scheme 1 (Fig. 4), whereas the DAC-JSCC scheme achieves a 2.5 dB coverage gain. These gains result from application-layer JSCC, which eliminates the cliff effect associated with Turbo coding at the physical layer. At a Complementary Cumulative Distribution Function (CCDF) of 10⁻³, the Peak-to-Average Power Ratio (PAPR) of the TPC DAC-JSCCM scheme is approximately 4 dB higher than that of Quadrature Phase Shift Keying (QPSK), resulting in sharper signal peaks, stricter linearity requirements for the power amplifier, and greater susceptibility to nonlinear distortion. By contrast, the CEC DAC-JSCCM scheme exhibits a PAPR comparable to that of QPSK. Conclusions Based on the DAC under investigation by SA4, three AI-enabled transmission schemes are proposed. Simulations are performed using the typical physical-layer parameter configuration for 3GPP GEO voice communications. At the minimum acceptable speech quality threshold (PESQ = 2.5), the proposed TPC DAC-JSCCM and CEC DAC-JSCCM schemes each provide an approximately 4 dB coverage gain over the conventional DAC-based transmission scheme, whereas the DAC-JSCC scheme provides a 2.5 dB coverage gain. As SA4 continues to investigate more advanced GEO speech codecs, future work will extend the proposed framework to these next-generation codecs.
- GEO voice /
- Joint Source-Channel Coding (JSCC) /
- Joint Source-Channel Coding and Modulation (JSCCM) /
- AI

HTML全文

图 1 应用层DAC与物理层传输方案的处理流程

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图 2 提出3种方案的处理流程

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图 5 提出方案1、2与QPSK的PAPR CCDF对比

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图 3 基线方案2 DAC-物理层无信道编码方案的处理流程

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图 4 提出方案与基线方案的信噪比与PESQ对比

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表 1 仿真参数设置

参数	基线方案1	基线方案2	总功率限制 DAC- JSCCM	恒模限制 DAC- JSCCM	DAC- JSCC
应用层输出 (N=64)	N bit	3N bit	3N /2 复数	3N /2 复数	3N bit
物理层调制方式	QPSK	QPSK	无	无	QPSK
物理层信道编码	1/3 Turbo	1/3 无	无	无	无
训练信噪比 (dB)	无	无	[–5,10)	[–5,10)	[–5,10)
DAC下采样输出维度	1024	1024	192	96	192
RVQ码本数	8	24	无	无	无
码本大小	256	256	无	无	无

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表 2 信噪比与误块率表(64 bit长度，1/3 Turbo编码)

信噪比(dB)	误块率
–6	1
–5	1
–4	1
–3	0.925
–2	0.665
–1	0.236
0	0.0464
1	0.0039
2	0.0004
3	0
4	0
5	0
6	0
7	0

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