论文标题
大型MIMO系统中M2M通信的基于动态光束的随机访问方案
Dynamic Beam-Based Random Access Scheme for M2M Communications in Massive MIMO Systems
论文作者
论文摘要
由机器对机器（M2M）通信支持的物联网是未来第六代（6G）系统的最重要应用之一。 6G面临的一个重大挑战是使大量的M2M设备及时访问网络。因此，本文利用了大量多输入多输出（MIMO）的空间选择性，以减少巨大的M2M设备同时启动随机访问时的碰撞问题。特别是，首先提出了基于光束的随机访问协议，以有效利用有限的高度链路资源来用于大量M2M设备。为了解决在空间和时间维度中M2M设备的不均匀分布，马尔可夫决策过程（MDP）问题的目的是最小化平均访问延迟的目的。接下来，我们提出基于双重Q网络（DDQN）算法的基于动态光束的访问方案，以解决最佳策略。最后，进行模拟以证明所提出的方案的有效性，包括模型训练和随机访问性能。
Internet of things, supported by machine-to-machine (M2M) communications, is one of the most important applications for future 6th generation (6G) systems. A major challenge facing by 6G is enabling a massive number of M2M devices to access networks in a timely manner. Therefore, this paper exploits the spatial selectivity of massive multi-input multi-output (MIMO) to reduce the collision issue when massive M2M devices initiate random access simultaneously. In particular, a beam-based random access protocol is first proposed to make efficient use of the limited uplink resources for massive M2M devices. To address the non-uniform distribution of M2M devices in the space and time dimensions, an Markov decision process (MDP) problem with the objective of minimizing the average access delay is then formulated. Next, we present a dynamic beam-based access scheme based on the double deep Q network (DDQN) algorithm to solve the optimal policy. Finally, simulations are conducted to demonstrate the effectiveness of the proposed scheme including the model training and random access performance.
