C-Band 53.76 Tbit/s Transmission Based on Bit Allocation Optimization with Raman Amplification

We experimentally demonstrate an 80-channel wavelength division multiplexing(WDM)transmission system over a 400 km fiber link.Raman amplification results in a non-flat WDM signal spectrum.Therefore,bit allocation optimization is used to enable different channels to carry different order quadrature amplitude modulation signals according to their optical signal-noise-ratios.A neural network equalizer based on a convolutional neural network(CNN),long shortterm memory(LSTM)network,and fully connected(FC)layer structure is adopted in Rx digital signal processing,in which CNN is used for characteristic extraction,LSTM is used for equalization and demodulation,and FC layers are used for output.After transmission,the bit error rate of all channels is below the 25%soft-decision forward error correction threshold,and the line rate reaches 53.76 Tbit/s.

多视点视频编码的码率控制优化算法(英文)

Rate control is one of the key factors influencing the multi-view video transmission.However,there is not a rate control algorithm in the existing Joint Multi-view Video Coding Model.In this paper,an efficient rate control algorithm and a bit allocation strategy for multi-view video coding are proposed.In order to obtain the consistent view quality,a bit allocation model based on the Lagrange optimum algorithm is firstly proposed.Secondly,considering the encoding statistical characteristics of different view types,a view weighting factor is introduced,and it will help improve the precision of bit allocation among views.Compared with the fixed QP control strategy,experiment results show that the proposed algorithm can efficiently control the bit rate and obtain more consistent views,with video visual quality improved.

Energy Optimization for Cellular-Connected Multi-UAV Mobile Edge Computing Systems with Multi-Access Schemes

In this paper,a cellular-connected unmanned aerial vehicle(UAV)mobile edge computing system is studied where several UAVs are associated to a terrestrial base station(TBS)for computation offloading.To compute the large amount of data bits,a part of computation task is migrated to TBS and the other part is locally handled at UAVs.Our goal is to minimize the total energy consumption of all UAVs by jointly adjusting the bit allocation,power allocation,resource partitioning as well as UAV trajectory under TBS’s energy budget.For deeply comprehending the impact of multi-UAV access strategy on the system performance,four access schemes in the uplink transmission is considered,i.e.,time division multiple access,orthogonal frequency division multiple access,one-by-one access and non-orthogonal multiple access.The involved problems under different access schemes are all formulated in non-convex forms,which are difficult to be tackled optimally.To solve this class of problem,the successive convex approximation technique is employed to obtain the suboptimal solutions.The numerical results show that the proposed scheme save significant energy consumption compared with the benchmark schemes.