能量采集小基站中基于斯坦科尔伯格博弈的内容缓存算法
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摘要
为了提升用户对下载文献的满意度,提出了能量采集小基站中基于缓存的资源分配算法。算法建立了联合用户接入和小基站缓存内容更新的斯坦科尔伯格博弈,首先提出了基于联盟博弈的用户接入选择算法,算法以用户满意度为效用函数允许用户在各联盟(小基站)之间转移,当转移后的效用能满足转移准则时,用户转移被接受,算法允许多个用户接入同一基站,用户采用NOMA技术共享小基站信道;随后建立小基站缓存更新算法,小基站调整自身的缓存内容以最大化收益。随后两层算法多次迭代,最终获得均衡解。仿真结果证明本算法在用户满意度和能效上都比基于就近接入原则的算法有着更为出色的表现。
To improve the users' satisfaction of download files, a caching based resource allocation algorithm in energy-harvesting small cell networks was proposed, which was established as a Stackelberg game that jointly optimized user accessing and small cells' content updating. Firstly, a coalitonal game for users to transfer between coalitions(small cells) with user satisfaction being utility function was proposed, and the transition was accepted once the utility of user after transferring satisfies the transition rules. Several users were allowed to be served by a same cell, and users accessing the same small cell would share the same channel using NOMA. Then, to maximize the benefit, a cache updating scheme was put forward to update the files cached by small cells. The equilibrium solution could be achieved after finite iterations of the two algorithms. The simulation results show that the proposed novel algorithm performs better in user satisfaction and energy-saving comparing with algorithm using principle of proximity.
To improve the users' satisfaction of download files, a caching based resource allocation algorithm in energy-harvesting small cell networks was proposed, which was established as a Stackelberg game that jointly optimized user accessing and small cells' content updating. Firstly, a coalitonal game for users to transfer between coalitions(small cells) with user satisfaction being utility function was proposed, and the transition was accepted once the utility of user after transferring satisfies the transition rules. Several users were allowed to be served by a same cell, and users accessing the same small cell would share the same channel using NOMA. Then, to maximize the benefit, a cache updating scheme was put forward to update the files cached by small cells. The equilibrium solution could be achieved after finite iterations of the two algorithms. The simulation results show that the proposed novel algorithm performs better in user satisfaction and energy-saving comparing with algorithm using principle of proximity.
引文
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[3]RAMAMONJISON R,BHARGAVA V K.Energy allocation and cooperation for energy-efficient wireless two-tier networks[J].IEEE Transactions on Wireless Communications,2016,15(9):6434-6448.
[4]HE P,ZHAO L,VENKATESH B.Optimal power allocation for hybrid energy harvesting and power grid coexisting system with power upper bounded constraints[J].IEEE Transactions on Signal&Information Processing over Networks,2016(99):1.
[5]SONG J,SONG H,WAN C.Optimal content placement for wireless femto-caching network[J].IEEE Transactions on Wireless Communications,2016(99):1.
[6]章跃跃,夏玮玮,朱亚萍,等.超密集网络中基于能效最优的资源分配算法[J].电信科学,2017,33(10):26-33.ZHANG Y Y,XIA W W,ZHU Y P,et al.An optimal energy-efficient resource allocation algorithm in ultra-dense network[J].Telecommunications Science,2017,33(10):26-33.
[7]PAPPALARDO I,QUER G,RAO B D,et al.Caching strategies in heterogeneous networks with D2D,small BS and macro BScommunications[C]//IEEE International Conference on Communications,May 22-27,2016,Kuala Lumpur,Malaysia.Piscataway:IEEE Press,2016:1-6.
[8]HUANG X,ANSARI N.Content caching and distribution in smart grid enabled wireless networks[J].IEEE Internet of Things Journal,2016,4(2):513-520.
[9]CHEN J,ZHU Q,ZHAO S.Interference management algorithm based on coalitional game for energy-harvesting small cells[J].Ksii Transactions on Internet&Information Systems,2017,11(9):4220-4241.
[10]ZHOU Z,DONG M,OTA K,et al.Energy-efficient context-aware matching for resource allocation in ultra-dense small cells[J].IEEE Access,2015(3):1849-1860.
[11]YOU F,LI J,LU J,et al.On the auction-based resource trading for a small-cell caching system[J].IEEE Communications Letters,2017,(99):1.
[12]BRESLAU L,CAO P,FAN L,et al.Web caching and Zipf-like distributions:evidence and implications[C]//Eighteenth Joint Conference of the IEEE Computer and Communications Societies,March 21-25,1999,New York,NY,USA.Piscataway:IEEE Press,1999:126-134.
[13]VIEN Q T,LE T A,BARN B,et al.Optimising energy efficiency of non-orthogonal multiple access for wireless backhaul in heterogeneous cloud radio access network[J].Iet Communications,2016,10(18):2516-2524.
[14]WANG X T,ZHU Q.A coalitional game based user access algorithm in energy-harvesting small cell networks[C]//2018International Conference on Communications Technology(ICCT),Oct 8-11,2018,Chongqing,China.Piscataway:IEEEPress,2018:418-423.
[15]WU D,WU Q,XU Y,et al.QoE-based distributed multichannel allocation in 5G heterogeneous cellular networks:a matching-coalitional game solution[J].IEEE Access,2017,5(99):61-71.
[16]CLAUSSEN H,HO L T W,SAMUEL L G.Self-optimization of coverage for femtocell deployments[C]//Wireless Telecommunications Symposium,April 24-26,2008,Pomona,CA,USA.Piscataway:IEEE Press,2008:278-285.