Mobile high-definition video intelligent bidirectional detection bandwidth control system

Abstract

According to the mobile high-definition video intelligent bidirectional detection bandwidth control method provided by the invention, a target end frame-level time delay trend extraction method and an extended RTP / RTCP driven source end rapid adaptive method are fused, so that the accuracy of the target end frame-level time delay trend extraction method is reserved; according to the method, the coding rate can fully use the available video bandwidth of the link to achieve the best subjective effect, meanwhile, the characteristic of high speed of the RTP / RTCP is fused, the packet loss phenomenon before congestion is detected due to the fact that the link cache of mobile high-definition video communication is too small is avoided, the experience of the mobile high-definition video is improved. A video bandwidth control architecture is provided on the basis, so that the video bandwidth control architecture has a better video effect for a fluctuating mobile network, is high in feasibility in practical application, is simple, efficient and high in practicability, serves as the most important link for guaranteeing the quality of a mobile high-definition video, and plays an extremely important role in mobile high-definition video communication.

Description

technical field [0001] The invention relates to a mobile video bandwidth control system, in particular to a mobile high-definition video intelligent bidirectional detection bandwidth control system, which belongs to the technical field of mobile video bandwidth. Background technique [0002] In recent years, the mobile Internet industry has developed rapidly, the number of users has increased rapidly, and the intensity of use has also increased significantly. More and more mobile terminals are helping work, life, and entertainment, resulting in rapid economic and social development, and people's life satisfaction and sense of gain are constantly improving. . At the same time, the demand for mobile high-definition video continues to rise. According to the white paper on global mobile data traffic forecast released by Cisco, video traffic currently accounts for more than 70% of global Internet network traffic consumption, and the proportion is still increasing. As a component ...

AI Technical Summary

Problems solved by technology

The PGM model estimates the available bandwidth by detecting packet-to-interval changes. When the detection packet sending rate is greater than the available bandwidth of the link, the received packet interval becomes larger. The PGM algorithm is simpler to implement, faster and less computationally complex, but obviously The problem is that the algorithm needs to meet the requirement that the sending rate is greater than the available bandwidth of the link, and the compact link and its bandwidth must be known. The capacity of the link under test in the PGM model is known, and the narrow link of the link under test must be satisfied. It coincides with the bottleneck link, and if this condition is not met, the measurement results will deviate; the idea of ​​the PRM algorithm is to inject a large number of detection packets into the link under test, and the maximum detection packet sending rate of the uncongested link is the available video bandwidth of the link , the PRM model is the same as the PGM model. The active measurement needs to congest the link under test through detection packets, so the measurement process will affect the existing state of the link and internal data flow, reducing the transmission capacity of the link and increasing the instability of the link. possibility of the situation

[0008] First, the complexity of the mobile network environment has caused mobile high-definition video calls to fail to fully meet people's daily needs. Due to signal coverage, complex environments, and too many users, bandwidth competition and bandwidth changes easily caused by high-speed mobility have caused A series of problems such as packet loss, delay increase, and jitter reduce the reliability and subjective experience of users using mobile high-definition video. These problems are a great test for video transmission, and also seriously restrict the quality and fluency of high-definition video call video. In view of the particularity of mobile high-definition video, the existing technology has no excellent performance, intelligent detection bandwidth control solution;

[0009] Second, the available video bandwidth estimation methods in the prior art have the problems of high time delay, low accuracy and low versatility. The bandwidth detection at the source end mainly collects the current link status from the source end of the link, and the active measurement method is through sending The detection packet packet pair or detection packet string is sent in the link, and the detection packet data flow after the tested link is received at the target end, the transmission rate of the detection packet changes due to the change of the connection state of the tested link, and then the loss occurs. When network indicators such as packet rate and delay change, the PGM model of the prior art estimates the available bandwidth by detecting the change of the packet pair interval, but the obvious problem is that the algorithm needs to meet the requirement that the sending rate is greater than the available bandwidth of the link, and it is necessary to know the and its bandwidth, the measured link capacity of the PGM model is known, and the narrow link of the tested link needs to coincide with the bottleneck link. Failure to meet this condition will cause deviations in the measurement results; the PRM algorithm measurement process will Affect the existing state of the link and internal data flow, reduce the transmission capacity of the link, and increase the possibility of instability;

[0010] Third, due to the imbalance between HD video bandwidth requirements and actual mobile network bandwidth and the unreliability of actual wireless networks, the detection of available video bandwidth for mobile HD video communication links faces various difficulties: First, low-latency requirements are difficult to obtain Satisfied, when the available video bandwidth of the link changes, it is necessary to obtain the detection results in real time, so that the encoding source can change the encoding parameters in time; second, the accuracy of the estimation of the available video bandwidth is not high, and the accurate estimation of the available video bandwidth value can ensure that in Under the premise of not exceeding its value, select the encoding parameters to make the subjective effect the best; third, the universality of the method is not enough, there are different standards for video encoding, and the lack of universal algorithms is convenient for providing reliable detection of available video bandwidth for different video encodings. It cannot provide effective and rapid detection of the available video bandwidth of the transmission link, and cannot solve the bottleneck of mobile high-definition video quality assurance, hindering the rapid development of the mobile high-definition video industry;

Although the target-side algorithm can fully use the available video bandwidth of the link, it has the disadvantage of slow detection speed;

[0012] Fifth, the real-time performance and dynamics of mobile high-definition video bandwidth control in the prior art are poor, the packet loss rate and delay are high, and the available video bandwidth of the link cannot be maximized. Due to the shortcomings of easy packet loss and long judgment time, the scalability of RTP cannot be used, the synchronization speed of RTCP cannot be reduced, the speed of RTCP message transmission link available video bandwidth data cannot be increased, and the available video bandwidth of the link cannot be fully utilized. , when the transmission rate exceeds the available video bandwidth of the link, it cannot be detected and adjusted in time, which cannot meet the real-time requirements; at the same time, there is a lack of feasible technical solutions for building a complete mobile high-definition video communication framework, and the effect for fluctuating mobile networks is relatively poor. Difference

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