Nowadays, real-time wireless video transmission has become increasingly popular and important. However, the uncertainty of wireless channel often causes errors, leading to a loss of freshness in the video transmission. The state-of-the-art video transmission systems overcome this problem by transmitting I-frames periodically to ensure freshness. Unfortunately, I-frames occupy more channel resources, for they do not utilize the information from previous frames. On the other hand, another coding mode named P-frame can save channel resources, but it may cause loss in frame freshness. Therefore, there exists a tradeoff between freshness and channel resources. Most traditional optimization methods only consider bitrate and distortion. In this paper, we propose a novel optimization method that takes information freshness into account. The proposed method employs the Rate-Distortion-Freshness (RDF) function which combines traditional Rate-Distortion (RD) function and information freshness. We analyze using the RDF function for video transmission in multi-state erasure channels and adopting Q-learning to achieve online frame mode selection based on the RDF function. Simulations show that for real-time wireless video transmission, our proposed method reduces channel occupancy without decreasing the quality of video.


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    Titel :

    RL-based Freshness-aware Frame Mode Selection for Real-time Wireless Video Transmission


    Beteiligte:
    Hou, Jie (Autor:in) / Chen, Xiaohui (Autor:in) / Zhang, Wenyi (Autor:in)


    Erscheinungsdatum :

    01.06.2023


    Format / Umfang :

    1782143 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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