Unequal Error Protection for Video Transmission over Wireless ChannelsOutlineUEP/ULPUEPProblem FormulationSlide 6Channel ModelReed-Solomon (RS) codeAnalysisTheory results-BSCTheory results-BSC (contd.)Simulation results (1)Simulation results (2)Simulation results (3)Simulation results (4)Conclusion1Unequal Error Protection for Video Transmission over Wireless ChannelsECE738 Project PresentationChang, Hong Hong05/09/20032OutlineUnequal Error Protection/ Unequal Loss ProtectionProblem FormulationChannel ModelRS codeTheoretical ResultsSimulation ResultsConclusion3UEP/ULPVideo quality is determined by the packet loss behavior observed at the video decoder. Time varying wireless channelsTime varying networking conditionsLimited transmission rate Different priority source data4UEPGoal of UEPAssign unequal amounts of error correction /protection bitsTo gain optimal quality in the receiver sideSome of algorithmsRate Compatible Punctured Convolutional codes Multiple description Priority encoding transmission - unequal amount of FEC packets5Problem FormulationUse Reed-Solomon code as the channel codingGiven a fixed size of packet, how many protection bits/symbols can be added in the RS codeword to get the optimal quality in the receiver side?6Problem FormulationOptimization criteriaMaximize expected PSNRMinimize expected distortionMaximize expected effective source rate (used in this project)Work need to doChannel model + RS coding -> Packet loss ratePacket loss rate -> effective source rate7Channel ModelGoodBadPGBPBGTwo state Markov Channel Model GBBGB BGPPP P=+8Reed-Solomon (RS) codeThe RS (n, k) channel code converts every k information symbols into an n-symbol block by appending n-k parity symbols. Any error pattern with less than symbol errors can be corrected. nk2tdata parity2n kt-� �=� �� �9AnalysisSymbol error probability PB Probability of i symbol errors within a block of n successively transmitted symbols Packet loss rate Effective source rate for one packet k*(1-PL) Calculate expected effective source rate over several packets( , ) (1 )i n iD B BnP n i P Pi-��= -����1( , )nL Di tP P n i=+=�10Theory results-BSC50 100 150 200 250 300050100150200250kEfective source rateEfective source rate as function of k, n = 255PB =0.05PB =0.1PB =0.15PB =0.211Theory results-BSC (contd.)100 150 200 250 300 350 400 450 500 550050100150200250300350400450kEfective source rateEfective source rate as function of k, n = 511PB =0.05PB =0.1PB =0.15PB =0.212Simulation results (1)200 205 210 215 220 225185190195200205210215kEfective source rateEfective source rate as function of k, n = 255 PB = 0.05TheoreticalSimulation13Simulation results (2)170 175 180 185 190 195170172174176178180182kEfective source rateEfective source rate as function of k, n = 255 PB = 0.1TheoreticalSimulation14Simulation results (3)150 155 160 165 170 175120125130135140145150155kEfective source rateEfective source rate as function of k, n = 255 PB = 0.15TheoreticalSimulation15Simulation results (4)120 125 130 135 140 145112114116118120122124126128130kEfective source rateEfective source rate as function of k, n = 255 PB = 0.2TheoreticalSimulation16ConclusionPB is smaller -> k is larger, better optimal effective source rate.The simulation results are basically match with the theoretical