Cloud gaming systems allow users to play games that require high-performance computational capability on their mobile devices at any location. However, playing games through cloud gaming systems increases the Round-Trip Time (RTT) due to increased network delay. To simulate a local gaming experience for cloud users, we must minimize RTTs, which include network delays. The speculative video transmission pre-generates and encodes video frames corresponding to all possible user inputs and sends them to the user before the user’s input. The speculative video transmission mitigates the network, whereas a simple solution significantly increases the video traffic. This paper proposes tile-wise delta detection for traffic reduction of speculative video transmission. More specifically, the proposed method determines a reference video frame from the generated video frames and divides the reference video frame into multiple tiles. We calculate the similarity between each tile of the reference video frame and other video frames based on a hash function. Based on calculated similarity, we determine redundant tiles and do not transmit them to reduce traffic volume in minimal processing time without implementing a high compression ratio video compression technique. Evaluations using commercial games showed that the proposed method reduced 40-50% in traffic volume when the SSIM index was around 0.98 in certain genres, compared with the speculative video transmission method. Furthermore, to evaluate the feasibility of the proposed method, we investigated the effectiveness of network delay reduction with existing computational capability and the requirements in the future. As a result, we found that the proposed scheme may mitigate network delay by one to two frames, even with existing computational capability under limited conditions.

In order to further reduce the transmission rate of multi-channel satellite broadcast signals, whose carrier-to-noise ratio (CNR fluctuates due to rainfall attenuation, we propose a novel digitized radio-over-fiber (DRoF) -based optical re-transmission system based on adaptive combination compression for ultra-high definition (UHD) broadcasting satellite (BS)/communications satellite (CS) broadcast signals. The proposed system reduces the optical re-transmission rate of BS/CS signals as much as possible while handling input CNR fluctuations. Therefore, the transmission rate of communication signals in time-division multiplexing (TDM) transmission is ensured, and network sharing of communication signals and broadcast signals via passive optical network (PON) is realized. Based on the ITU-R P.618-13 prediction model, an experimental evaluation is performed using estimates of the long-term statistics of attenuation due to rainfall. The attenuation is evaluated as a percentage of the time that long-term re-transmission service is available. It is shown that the proposed system is able to accommodate a wide range of rainfall attenuation and achieve a 99.988% time percentage for the duration of service provision. In order to show the rate reduction effect of the proposed system, the quantization bit reduction effect as a function of the input CNR, which depends on rainfall attenuation, is experimentally confirmed. Experiments show that service operation time of 99.978% can be achieved by 3-bit transmission. This means a 62.5% reduction in transmission rate is realized compared to conventional fixed quantization. Furthermore, the average quantization bit number in our system for service operation times is 3.000, indicating that most service operation times are covered by just 3-bit transmission.

When an access point transmits multi-view video over a wireless network with subcarriers, bit errors occur in the low quality subcarriers. The errors cause a significant degradation of video quality. The present paper proposes Significance based Multi-view Video Streaming with Subcarrier Allocation (SMVS/SA) for the maintenance of high video quality. SMVS/SA transmits a significant video frame over a high quality subcarrier to minimize the effect of the errors. SMVS/SA has two contributions. The first contribution is subcarrier-gain based multi-view rate distortion to predict each frame's significance based on the quality of subcarriers. The second contribution is heuristic algorithms to decide the sub-optimal allocation between video frames and subcarriers. The heuristic algorithms exploit the feature of multi-view video coding, which is a video frame is encoded using the previous time or camera video frame, and decides the sub-optimal allocation with low computation. To evaluate the performance of SMVS/SA in a real wireless network, we measure the quality of subcarriers using a software radio. Evaluations using MERL's benchmark test sequences and the measured subcarrier quality reveal that SMVS/SA achieves low traffic and communication delay with a slight degradation of video quality. For example, SMVS/SA improves video quality by up to 2.7 [dB] compared to the multi-view video transmission scheme without subcarrier allocation.