%0 Journal Article
%A 段雪飞
%A 黄韬
%A 刘旭
%A 唐琴琴
%A 谢人超
%T <span class="fontstyle0">Dynamic computation offloading in time-varying environment for ultra-dense networks: a stochastic game approach</span>
%D 2021
%R 10.19682/j.cnki.1005-8885.2021.1003
%J 中国邮电高校学报（英文）
%P 24-37
%V 28
%N 2
%X <span class="fontstyle0">To meet the demands of large-scale user access with computation-intensive and delay-sensitive applications,<br>
combining ultra-dense networks (UDNs) and mobile edge computing (MEC)are considered as important solutions.<br>
In the MEC enabled UDNs, one of the most important issues is computation offloading. Although a number of work<br>
have been done toward this issue, the problem of dynamic computation offloading in time-varying environment,<br>
especially the dynamic computation offloading problem for multi-user, has not been fully considered. Therefore, in<br>
order to fill this gap, the dynamic computation offloading problem in time-varying environment for multi-user is<br>
considered in this paper. By considering the dynamic changes of channel state and users queue state, the dynamic<br>
computation offloading problem for multi-user is formulated as a stochastic game, which aims to optimize the delay<br>
and packet loss rate of users. To find the optimal solution of the formulated optimization problem, Nash </span><span class="fontstyle2">Q-l</span><span class="fontstyle0">earning<br>
(NQLN) algorithm is proposed which can be quickly converged to a Nash equilibrium solution. Finally, extensive<br>
simulation results are presented to demonstrate the superiority of NQLN algorithm. It is shown that NQLN algorithm<br>
has better optimization performance than the benchmark schemes.</span> <br>
%U https://jcupt.bupt.edu.cn/CN/10.19682/j.cnki.1005-8885.2021.1003