Mobile Coded Caching in Small Cell Networks:Algorithm Design and Performance Analysis

In coded caching,users cache pieces of files under a specific arrangement so that the server can satisfy their requests simultaneously in the broadcast scenario via e Xclusive OR(XOR)operation and therefore reduce the amount of transmission data.However,when users’locations are changing,the uploading of caching information is frequent and extensive that the traffic increase outweighed the traffic reduction that the traditional coded caching achieved.In this paper,we propose mobile coded caching schemes to reduce network traffic in mobility scenarios,which achieve a lower cost on caching information uploading.In the cache placement phase,the proposed scheme first constructs caching patterns,and then assigns the caching patterns to users according to the graph coloring method and four color theorem in our centralized cache placement algorithm or randomly in our decentralized cache placement algorithm.Then users are divided into groups based on their caching patterns.As a benefit,when user movements occur,the types of caching pattern,rather than the whole caching information of which file pieces are cached,are uploaded.In the content delivery phase,XOR coded caching messages are reconstructed.Transmission data volume is derived to measure the performance of the proposed schemes.Numerical results show that the proposed schemes achieve great improvement in traffic offloading.

Multilayer Satellite Network Collaborative Mobile Edge Caching:A GCN-Based Multi-Agent Approach

With the explosive growth of highdefinition video streaming data,a substantial increase in network traffic has ensued.The emergency of mobile edge caching(MEC)can not only alleviate the burden on core network,but also significantly improve user experience.Integrating with the MEC and satellite networks,the network is empowered popular content ubiquitously and seamlessly.Addressing the research gap between multilayer satellite networks and MEC,we study the caching placement problem in this paper.Initially,we introduce a three-layer distributed network caching management architecture designed for efficient and flexible handling of large-scale networks.Considering the constraint on satellite capacity and content propagation delay,the cache placement problem is then formulated and transformed into a markov decision process(MDP),where the content coded caching mechanism is utilized to promote the efficiency of content delivery.Furthermore,a new generic metric,content delivery cost,is proposed to elaborate the performance of caching decision in large-scale networks.Then,we introduce a graph convolutional network(GCN)-based multi-agent advantage actor-critic(A2C)algorithm to optimize the caching decision.Finally,extensive simulations are conducted to evaluate the proposed algorithm in terms of content delivery cost and transferability.

Adaptive Delay Optimization of Multicast-Enabled Coded Caching in Device-to-Device Networks

This letter investigates a delay optimization problem in device-to-device(D2D)networks where users have pre-downloaded subfiles following a coded caching rule.Due to acquiring rest subfiles,users may suffer both receiving and transmitting delays.To achieve the delay minimization,we first propose a delay-aware mode-selection strategy to adaptively choose multicast or D2D communications mode to reduce the receiving-caused delay.By matching these transmit modes with distinct subfile sizes,we further formulate a min-max optimization problem to minimize the delivery delay.Finally,numerical results prove that the proposed scheme outperforms existing ones in terms of both receiving and transmitting delays.

Multi-Source Spinal Coding for Coded Caching Multicast Transmissions in Wireless Networks

Recently,coded caching has been treated as a promising technique to alleviate the traffic burden in wireless networks.To support high efficient coded caching multicast transmissions,the time-varying heterogeneous channel conditions need to be considered.In this paper,a practical and novel multi-source spinal coding(MSSC)scheme is developed for coded caching multicast transmissions under heterogeneous channel conditions.By exploring joint design of network coding and spinal coding(SC),MSSC can achieve unequal link rates in multicast transmissions for different users.Moreover,by leveraging the rateless feature of SC in our design,MSSC can well adapt the link rates of all users in multicast transmissions without any feedback of time-varying channel conditions.A maximum likelihood(ML)based decoding process for MSSC is also developed,which can achieve a linear complexity with respect to the user number in the multicast transmission.Simulation results validate the effectiveness of the MSSC scheme.Compared to the existing scheme,the sum rate of MSSC in multicast transmissions is improved by about 20%.When applying MSSC in coded caching systems,the total transmission time can be reduced by up to 48% for time-varying channels.