嵌入式多通道无线视频传输的码率自适应算法

Rate adaption algorithm for embedded multi-channel wireless video transmission

无线视频传输和视频压缩技术是当前众多物联网(IoT)应用和嵌入式系统的基础和核心。而在多通道传输时无线网络状态的不断变化,会导致视频丢帧和延时抖动问题。虽然自适应算法能够在一定程度上解决在PC或服务器平台下的视频传输问题,但在嵌入式平台和无线网络下仍不能满足实时性和服务质量(QoS)要求。为此,基于DM368芯片设计了一从视频采集、压缩、WiFi传输、控制单元接收到上位机显示的完整平台。同时充分考虑了嵌入式平台的特点,提出一种结合信号质量、网络带宽、缓存状态和拥塞控制的码率自适应算法。该算法利用高斯函数统计网络带宽,使用分段反比例函数调整缓存状态,利用加权移动法对码率进行平滑,并使用极值抑制法进行码率均衡。该算法实现了码率的平滑调整,并被应用于所提平台来实现控制单元对多个WiFi相机的管理、多通道传输和负载均衡。以QoS为评价指标进行实验验证,结果表明:该算法在设计的嵌入式平台上性能良好,平滑性和缓存稳定性都有很大提升,多通道状态下的公平性和带宽利用率也有显著提高。在单相机信号质量动态变化或多相机竞争带宽等多种情况下,相对于MDI(McGinely Dynamic Indicator)算法,该算法的平滑性提升了16%~59%;相对于BBA(Buffer-Based Algorithm),该算法的缓存抖动降低了15%~72%,时延抖动降低了12%~76%。

Wireless video transmission and video compression technology are the foundations and cores of many Internet of Things(IoT)applications and embedded systems in these days.However,multi-channel transmission always causes video frame loss and delay jitter because of the continuous change of wireless network state.Although the adaption algorithm can solve the video transmission problem under PC or server platform to a certain extent,the real-time performance and Quality of Service(QoS)requirement cannot be satisfied under the embedded platform and wireless network.Therefore,based on the DM368 chip,a complete platform was designed from video capture,compression,WiFi transmission,control unit reception to host computer display.At the same time,with the full consideration of the characteristics of embedded platform,a rate adaption algorithm that combines signal quality,network bandwidth,buffer status and congestion control was proposed.In this algorithm,the Gaussian function was used to calculate network bandwidth,the segmented inverse proportional function was used to adjust buffer status,the weighted moving method was adopted to smooth rate,and the extreme value suppression method was used for rate balancing.The smooth rate adjustment was realized by this algorithm,and the algorithm was applied to the proposed platform to realize the management of the control unit on multiple WiFi cameras,multi-channel transmission and load balancing.The QoS was used as the evaluation index for experimental verification.The results show that the algorithm performs well on the embedded platform with great improvements of smoothness and buffer stability,and has significantly fairness and bandwidth utilization improvements under multi-channel condition.In a variety of situations,such as single camera signal quality dynamic change or multi-camera bandwidth competition,compared with the McGinely Dynamic Indicator(MDI)algorithm,the proposed algorithm has the smoothness improved by 16%to 59%;compared with the Buffer-Based Algorithm(BBA),the proposed algorithm has the cache jitter reduced by 15%to 72%,and the delay jitter reduced by 12%to 76%.