This paper investigates the performance of multi-user covert communications over a fixed bandwidth in a multi-cell scenario with both eavesdroppers and malicious jammers. We propose an intelligent spectrum control (ISC) scheme that combines high-accuracy spectrum sensing with AI-assisted real-time decision-making to generate time-frequency dynamic occupation patterns for multiple legitimate users. The scheme can proactively avoid external interference and intra-system co-channel collisions, thereby improving covertness and reliability. Within this framework, we derive closed-form expressions for the detection error probability (DEP) of the eavesdropper and the reliable transmission probability (RTP) of legitimate users under multi-user joint detection. We then analytically optimize the transmission power that can maximize the covert rate (CR), as well as the maximum number of users that can access the system covertly and concurrently under given covertness and reliability constraints. Simulation results confirm the tight match between the analytical and Monte Carlo curves, and show that the proposed scheme can achieve a higher DEP, a larger RTP, and a greater multi-user capacity than the benchmark scheme.

翻译：本文研究了多小区场景下存在窃听者和恶意干扰者时，固定带宽内的多用户隐蔽通信性能。我们提出了一种智能频谱控制（ISC）方案，该方案将高精度频谱感知与人工智能辅助的实时决策相结合，为多个合法用户生成时频动态占用模式。该方案能够主动规避外部干扰和系统内同信道冲突，从而提高隐蔽性和可靠性。在此框架下，我们推导了窃听者在多用户联合检测下的检测错误概率（DEP）以及合法用户的可靠传输概率（RTP）的闭式表达式。随后，我们通过解析方法优化了能够最大化隐蔽速率（CR）的发射功率，以及在给定隐蔽性和可靠性约束下可隐蔽并发接入系统的最大用户数量。仿真结果证实了解析曲线与蒙特卡洛曲线的高度吻合，并表明所提方案相较于基准方案能够实现更高的DEP、更大的RTP以及更强的多用户容量。