دانلود رایگان مقاله MCS مشترک و قدرت تخصیص برای ویدئوی چندپخشی SVC بر شبکه تلفن همراه ناهمگن

Abstract

Scalable video coding (SVC) and adaptive modulation and coding (AMC) are key issues for video multicast in broadband wireless networks, which could improve users’ received video quality by encoding the video stream into different layers and assigning appropriate modulation and coding schemes (MCSs) to each layer. With the development of mobile communication, various types of cellular networks such as 4 G LTE and 3 G co-exist at the same place. This type of network is named heterogeneous cellular networks in this paper. Given one ISP usually owns different types of base stations (BSs) at the same place and different BSs may have different traffic loads and transmission capabilities, cooperative transmission among the heterogeneous BSs becomes possible, e.g. a 4 G LTE BS could help offload a 3 G BS if the 4 G LTE BS has extra bandwidth and the devices have the corresponding network interface. As far as the authors understand, how to schedule this cooperation has not been solved in any formal way in literature. This paper presents a joint MCS and power allocation problem in multi-base-station heterogeneous cellular networks for SVC video multicast with the objective to maximize the defined system utility. This problem is NP-hard and in order to solve this, we first decompose this problem into two sub-problems. We present a dynamic programming algorithm to optimize the problem without optimizing the power allocation. Then we take power allocation for each sub-channel into account and propose a multi-base joint dynamic programming and greedy algorithm (MDPGA) algorithm for this joint power and MCS allocation problem in heterogeneous cellular networks. Simulation results show that our algorithms can outperform other competing schemes significantly.

6. Conclusion

This paper discusses the scalable video multicast in heterogeneous cellular networks considering the video layer selection, MCS assignment and power allocation, where different types of BSs cooperate for better defined system utility. The objective is to maximize the total system utility of all users under the limited system resource constraints, and we propose different algorithms to solve this problem. The simulation results show that the proposed multi-base MCS dynamic programming algorithm is superior than the single-base optimal algorithm and multi-BS greedy algorithm in typical network scenarios. This shows the advantage of the cooperation’s between different BSs and the performances of the proposed algorithms.