Abstract—In this paper, a network-aware and source-aware video streaming system is proposed to support interactive multiuser communications within single-cell and multicell IEEE 802.11 networks. Unlike the traditional streaming video services, the strict delay constraints of an interactive video streaming system pose more challenges. These challenges include the heterogeneity of uplink and downlink channel conditions experienced by different users, the multiuser resource allocation of limited radio resources, the incorporation of the cross-layer design, and the diversity of content complexities exhibited by different video sequences. With the awareness of video content and network resources, the proposed system integrates cross-layer error protection mechanism and performs dynamic resource allocation across multiple users. We formulate the proposed system as to minimize the maximal end-to-end expected distortion received by all users, subject to maximal transmission power and delay constraints. To reduce the high dimensionality of the search space, fast multiuser algorithms are proposed to find the near-optimal solutions. Compared to the strategy without dynamically and jointly allocating bandwidth resource for uplinks and downlinks, the proposed framework outperforms by 2.18 7.95 dB in terms of the average received PSNR of all users and by 3.82 11.50 dB in terms of the lowest received PSNR among all users. Furthermore, the proposed scheme can provide more uniform video quality for all users and lower quality fluctuation for each received video sequence. Index Terms—Cross-layer design, joint uplink and downlink optimization, multiuser video communication, network-aware, wireless local area networks. I.

In this paper, we propose a framework to transmit multiple scalable video programs over downlink multiuser OFDM networks in real time. The framework explores the scalability of the video codec and multi-dimensional diversity of multiuser OFDM systems to achieve the optimal service objectives subject to constraints on delay and limited system resources. We consider two essential service objectives, namely, the fairness and efficiency. Fairness concerns the video quality deviation among users who subscribe the same quality of service, and efficiency relates to how to attain the highest overall video quality using the available system resources. We formulate the fairness problem as minimizing the maximal end-to-end distortion received among all users and the efficiency problem as minimizing total end-to-end distortion of all users. Fast suboptimal algorithms are proposed to solve the above two optimization problems. The simulation results demonstrated that the proposed fairness algorithm outperforms a time division multiple (TDM) algorithm by 0.5∼3dB in terms of the worst received video quality among all users. In addition, the proposed framework can achieve a desired tradeoff between fairness and efficiency. For achieving the same average video quality among all users, the proposed framework can provide fairer video quality with 1∼1.8dB lower PSNR deviation than a TDM algorithm.

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