Research On Network Coding Technology Based On Physical Layer Rate Adaptation

The development of network coding is changing rapidly,and various coding methods are emerging to continuously adapt to the needs of high reliability and low latency network development.However,most of the existing literature does not consider the physical layer complexity and by default uses the minimum link channel capacity of the receiving user in broadcast networks for data transmission,which undoubtedly simplifies the problem.Therefore,this paper considers the adaptive adjustment of the physical layer rate and a variety of communication scenarios,such as cellular networks,C-RAN,etc.,combined with network coding techniques to reduce the decoding delay and improve the network throughput,the main work is as follows.This paper proposes a rate-aware network coding method based on a cellular network.Different users in a cellular network experience different channel conditions,so different data transmission rates can be provided by the base station to meet user requirements,and the variability of data transmission rates affects the selection of transmission rates for coded packets and the selection of packets to be combined in each transmission,so this thesis fully incorporates dynamic transmission rates based on the instantaneous decodable network coding method,by designing a new rateperceptual IDNC graph,so that the current time-slot coding encoding data transmission completion time minimization problem is transformed into a maximum weight clique problem,and the restriction of the expected completion time lower bound for each user is used to select the vertices associated with the maximum expected completion time user,narrowing the maximum weight clique search range and reducing the algorithm search complexity.Simulation results show that the proposed method can effectively reduce the system transmission data completion time and improve the network data throughput compared with broadcast and traditional Instantly decodable network coding(IDNC).This paper proposes a rate-aware instantly decodable network coding method based on Cloud Radio Access Networks(C-RAN).In this paper,different Remote Radio Heads(RRHs)and different link capacities between different users are considered in the trade-off between the number of scheduled users and transmission rates,and the mapping scheduling between users and RRHs,the selection of coded groups and the selection of coded data transmission rates are jointly considered to reduce the system decoding delay.Considering the complexity of the optimization problem,this paper proposes an optimization method through online relaxation,which involves the expected version of the decoding delay,mapping the possible associations between users,RRHs,coded groupings and transmission rates to the vertices of the cloud wireless rate-aware IDNC graph.Subsequently,the online decoding delay reduction problem is shown to be equivalent to the maximum weight independent set problem on the proposed graph.Simulation results show that the cloud wireless rateaware IDNC network model is superior to previous research models and can obtain lower decoding delay.