A Chaotic Q-learning-Based Licensed Assisted Access Scheme Over the Unlicensed Spectrum
A Chaotic Q-learning-Based Licensed Assisted Access Scheme Over the Unlicensed Spectrum
复制标题
非授权频谱上基于混沌 Q 学习的授权辅助接入方案
DOI：
10.1109/tvt.2019.2936510
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发表时间：
2019-08
影响因子：
6.8
通讯作者：
Zhang Zhizhong
中科院分区：
文献类型：
--
作者：
Pei Errong;Jiang Junjie;Liu Lilan;Li Yonggang;Zhang Zhizhong
为了满足对移动的数据业务的不断增长的需求，移动的运营商正在寻求利用未许可频谱作为许可频谱的补充。因此，LTE和未授权频谱上的现任用户之间的和谐和频谱高效的共存方案是强制性的。目前，先进的智能技术被期望在未来的通信系统中发挥至关重要的作用。因此，我们将Q学习（QL）框架引入LTE授权辅助接入（LAA）方案中，从而形成基于QL的LAA方案。首先对非授权频谱共享中的公平性进行了重新定义，然后根据预定义的吞吐量和公平性阈值将状态空间划分为6个状态，接着定义了动作集和奖励函数。在所提出的方案中，收敛Q表的基础上，其中每个元素是用来评估的利弊采取行动，代理可以重复与环境，直到它达到终端状态，即选择最佳的行动（即竞争窗口大小）。此外，首次将具有遍历性、规律性和随机性的混沌运动引入到动作决策策略中，在兼顾探索和开发的同时，加快了训练速度。仿真结果表明，所提出的$\N $-混沌贪婪选择策略与$\N $-贪婪、纯贪婪、Bolzmann和随机选择策略相比，具有更快的收敛速度;所提出的混沌QL LAA方案在吞吐量、碰撞概率、吞吐量、碰撞概率等方面均优于3GPP、线性、固定LAA和先听后说（LBT）自适应LAA方案，公平和延迟。
To meet the ever-increasing demand for mobile data traffic, mobile operators are seeking to utilize unlicensed spectrum as a supplement to the licensed spectrum. The harmonious and spectrum-efficient coexistence scheme between LTE and incumbent users on the unlicensed spectrum is thus mandatory. Currently, advanced intelligent technologies are being expected to play the crucial role in the future communication system. We thus introduce the Q-learning (QL) framework into LTE licensed assisted access (LAA) scheme in the paper, thereby forming a QL based LAA scheme. We first redefine the fairness in the sharing of unlicensed spectrum and then divide the state space into six states based on the predefined throughput and fairness thresholds, followed by the definition of the action set and reward function. In the proposed scheme, based on the convergent Q table, where each element is used to evaluate the pros and cons of taking an action, the agent can repeatedly interact with the environment until it reaches the terminal state, i.e. selects the optimal action (i.e. contention window size). Additionally, the chaotic motion with ergodicity, regularity and randomness is first introduced into the action-decision strategy to accelerate the training velocity with the balance consideration of exploration and exploitation. The simulation results prove that the proposed $\epsilon$-chaotic greedy selection strategy has faster convergence velocity compared with other methods such as $\epsilon$-greedy, pure greedy, Bolzmann and random selection strategy, and that the proposed chaotic QL LAA scheme outperforms the other LAA schemes such as the 3GPP, linear, fixed LAA and Listen Before Talk (LBT) adaptive schemes in terms of throughput, collision probability, fairness and delay.
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DOI：
10.1109/iccnc.2015.7069344
发表时间：
2014-03
期刊：
2015 International Conference on Computing, Networking and Communications (ICNC)
影响因子：
--
作者：
Ahmed El Shane;T. Khattab;H. Saad;Amr M. Mohamed
通讯作者：
Ahmed El Shane;T. Khattab;H. Saad;Amr M. Mohamed
DOI：
10.1145/2973750.2973781
发表时间：
2016-10
期刊：
Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking
影响因子：
--
作者：
Eugene Chai;K. Sundaresan;M. Khojastepour;S. Rangarajan
通讯作者：
Eugene Chai;K. Sundaresan;M. Khojastepour;S. Rangarajan
影响因子：
11.2
作者：
Fengxiao Tang;Bomin Mao;Z. Fadlullah;N. Kato
通讯作者：
Fengxiao Tang;Bomin Mao;Z. Fadlullah;N. Kato
DOI：
10.1109/tccn.2016.2594780
发表时间：
2016-07
影响因子：
8.6
作者：
Apostolos Galanopoulos;Fotis Foukalas;T. Tsiftsis
通讯作者：
Apostolos Galanopoulos;Fotis Foukalas;T. Tsiftsis
小蜂窝网络的负载感知动态频谱访问：图形游戏方法
影响因子：
6.8
作者：
Yuhua Xu;Chenggui Wang;Junhong Chen;Jinlong Wang;Yitao Xu;Qihui Wu;Alagan Anpalagan
通讯作者：
Alagan Anpalagan