نبذة مختصرة : In the current communications age, the capabilities of mobile devices are increasing. The mobiles are capable of communicating at data rates of hundreds of mbps on 4G networks. This enables playback of rich multimedia content comparable to internet and television networks. However, mobile networks need to be spectrum-efficient to be affordable to users. Multimedia Broadcast Multicast Systems (MBMS) is a wireless broadcasting standard that is being drafted to enable multimedia broadcast while focusing on being spectrum-efficient. The hybrid video coding techniques facilitate low bitrate transmission, but result in dependencies across frames. With a mobile environment being error prone, no error correction technique can guarantee error free transmission. Such errors propagate, resulting in quality degradation. With numerous mobiles sharing the broadcast session, any error resilient scheme should account for heterogeneous device capabilities and channel conditions. The current research on wireless video broadcasting focuses on network based techniques such as FEC and retransmissions, which add bandwidth overhead. There is a need to design innovative error resilient techniques that make video codec robust with minimal bandwidth overhead. This Dissertation introduces novel techniques in the area of MBMS systems. First, robust video structures are proposed in Periodic Intra Frame based Prediction (PIFBP) and Periodic Anchor Frame based Prediction (PAFBP) schemes. In these schemes, the Intra frames or anchor frames serve as reference frames for prediction during GOP period. The intermediate frames are independent of others; any errors in such frames are not propagated, thereby resulting in error resilience. In prior art, intra block rate is adapted based on the channel characteristics for error resilience. This scheme has been generalized in multicasting to address a group of users sharing the same session. Average packet loss is used to determine the intra block rate. This improves performance of the overall group and ...
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