Grant-free access, in which channels are accessed without undergoing assignment through a handshake process, is a promising solution to support massive connectivity needed for Internet-of-Things (IoT) networks. In this paper, we consider uplink grant-free massive access for an IoT network with multiple channels. To be specific, the IoT devices generate short packets and have grant-free non-orthogonal access to a channel to transmit the generated packets to a base station (BS). With the aim of keeping the information fresh at the BS, we first derive the age of information (AoI) for grant-free short-packet communications, and then formulate the AoI minimization problem. However, the problem is challenging as the number of users involved is large, and to tackle this problem efficiently, we propose a mean-field evolutionary game-based approach. In this approach, the average behavior of the IoT devices is considered rather than their individual behaviors, and the dynamics of the strategies of the IoT devices are modeled by an evolutionary process. Simulation results verify the effectiveness of the proposed mean-field evolutionary game-based approach.

中文翻译：

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使用平均场博弈的无授权非正交大规模访问的信息最小化时代

免授权访问，其中通道无需通过握手过程进行分配，是支持物联网 (IoT) 网络所需的大规模连接的有前途的解决方案。在本文中，我们考虑了具有多个通道的物联网网络的上行链路免授权大规模访问。具体而言，物联网设备生成短数据包，并具有对信道的无授权非正交访问，以将生成的数据包传输到基站 (BS)。为了使 BS 的信息保持新鲜，我们首先推导出无授权短数据包通信的信息年龄 (AoI)，然后制定 AoI 最小化问题。然而，由于涉及的用户数量很大，这个问题具有挑战性，为了有效地解决这个问题，我们提出了一种基于平均场演化博弈的方法。在这种方法中，考虑的是 IoT 设备的平均行为而不是它们的个体行为，并且 IoT 设备的策略动态通过进化过程建模。仿真结果验证了所提出的基于平均场演化博弈的方法的有效性。