| 引用本文: | 赵东来,王钢,郑黎明,周若飞.超密集网络中非合作博弈的功率分配算法[J].哈尔滨工业大学学报,2020,52(5):30.DOI:10.11918/201910027 |
| ZHAO Donglai,WANG Gang,ZHENG Liming,ZHOU Ruofei.Optimal power allocation strategy in ultra-dense networks with non-cooperative game[J].Journal of Harbin Institute of Technology,2020,52(5):30.DOI:10.11918/201910027 |
|
| 摘要: |
| 为了抑制超密集网络中小小区基站的密集化部署带来的干扰,并提高系统的吞吐量,本文研究了频谱共享超密集网络中的功率分配策略.首先,针对非凸的系统和速率最大化问题,采用非合作博弈模型将其转化为每个用户效益函数最大化的凸子问题,并通过设计一种动态定价使得非合作博弈模型的纳什均衡点（NE）是原优化问题的驻点.其次,为了保证宏小区用户的服务质量（QoS）,模型中引入了干扰功率约束条件来抑制宏小区受到的干扰.最后,在此非合作博弈论框架下,设计了一种迭代式的基于全局信息的功率分配算法.每次迭代通过求解KKT条件获得每个用户的最优发射功率,通过理论推导证明了迭代算法可收敛到博弈模型的NE.此外,为了减少迭代算法的信令开销、提高资源利用率,还提出了一种基于局部信息的功率分配算法.仿真结果表明,所提出的基于全局信息的功率分配算法比对比方法具有更好的传输性能,所提出的基于局部信息的功率分配算法在保证较好的传输性能的前提下有效地减少了信令开销. |
| 关键词: 功率分配 超密集网络 非合作博弈论 信令开销 服务质量（QoS） |
| DOI：10.11918/201910027 |
| 分类号:TN929.5 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(4,7,61401120) |
|
| Optimal power allocation strategy in ultra-dense networks with non-cooperative game |
|
ZHAO Donglai,WANG Gang,ZHENG Liming,ZHOU Ruofei
|
|
(Communication Research Center, Harbin Institute of Technology, 150001 Harbin, China)
|
| Abstract: |
| In order to suppress interference caused by the dense deployment of small cell base stations in an ultra-dense network (UDN) and improve system throughput, this paper investigates the power allocation strategy for a spectrum sharing UDN. Firstly, the noncooperative game was adopted to transform the non-convex system sum-rate maximization problem into several convex subproblems that maximize the utility function of each user. By designing a dynamic pricing, each Nash equilibrium point (NE) of the game was a stationary point of the original optimization problem. Secondly, an interference power constraint was applied to guarantee the quality-of-service (QoS) of the macrocell. Finally, under the game theory framework, an iterative global information-based power allocation algorithm was designed. The optimal transmit power of each user could be obtained by solving KKT condition during each iteration, and the proposed iterative algorithm was proved to be convergent to the NE of the game model. In addition, in order to reduce the signaling overhead and improve the resource utilization, a power allocation algorithm based on local information was also proposed. Simulation results show that the proposed global information-based power allocation algorithm achieved a better transmission performance than benchmark methods and the proposed local information-based power allocation algorithm effectively reduced signaling overhead while guaranteed good transmission performance. |
| Key words: power allocation ultra-dense network (UDN) non-cooperative game signaling overhead quality-of-service(QoS) |
