###### Abstract  
Integrated Sensing and Communications (ISAC) has attracted increasing attention due to more efficient utilization of both radio spectrum and hardwares. However, ISAC can only relieve the shortage of the spectrum, especially in the situation of exponential growth of wireless terminals. Efficient spectrum utilization strategy is still an important direction for the continuous evolution of wireless communication technology. As such, spectrum sensing (SS) is discussed in ISAC scenarios, and a novel cooperative SS scheme is proposed by as an improved auto-encoder for more efficient spectrum utilization. More specifically, the parameters of each local spectrum spectrum-sensing network are encoded and sent to the central server, and the local network parameters are decoded, fused, and returned to each local node at the central server. The simulations are designed, and the experiment results demonstrate the effectiveness of the proposed scheme. Integrated Sensing and Communications; spectrum sensing; denoising auto-encoder 202 two basic indicators to evaluate the performance of SS. Generally, detection probability denotes the ability of protecting to protect anotherized users, while false alarm probability is positively related to the system throughput of cognitive users. On the other hand, with the development of 5G and Beyond, the radio spectrum continues to evolve to high frequency, resulting in the increasing spectrum overlap between wireless sensing and wireless communication. This provides the possibility of spectrum sharing for wireless sensing and wireless communication, namely ISAC. Currently, the focus of ISAC consists inconsists of ISAC waveform design and signal processing, communication-assisted sensing, and sensing-empowered communication [10; 11; 12], where ISAC waveform design mainly focuses on the waveform design of sensing and communication information in the same frequency band. Distributed sensing is mainly considered for communication-assisted sensing, where the sensing performance of each node is enhanced by mutual information sharing. In addition, sensing-empowered communication is devoted to the sensing of wWireless channels by the echo of the wireless signal, thereby providing a more reasonable configuration of RF parameters and improving the communication performance as a consequence. Although SS and ISAC ISAC, respectivelyrespectively, show the ability to improve spectrum efficiency, the contradiction between the growing frequency demand and the limited spectrum resources is still the bottleneck of wireless services [13]. Motivated by this, this paper considers the fusion of ISAC and SS, and provides an opportunistic available spectrum for ISAC services. More specifically, an improved denoising auto-encoder is considered for cooperative spectrum sensing to discover an available spectrum of ISAC service, where the encoder is deployed on the local nodes, and the decoder is deployed on the central server. At the local node, the observed signal is input to the designed convolutional neural network (CNN) [14] to decide the status of observed spectrum bands, and then the network parameters are encoded and sent to the central server. At the central server, the encoded network parameters of local nodes are decoded and fused to the weighted network parameters, and then the weighted network parameters are distributed to local nodes. Note that the federated learning (FL) framework [15; 16; 17] is considered for this cooperative SS scenario, and the denoising auto-encoder is trained locally in advance. The main contributions of this paper are concluded as follows. 1. A more efficient spectrum utilization scheme is discussed by the fusion of SS and ISAC, and this scheme may provide more available spectrum for ISAC services, especially for 5G and beyond [18]. 2. An improved denoising auto-encoder is proposed for joint spectrum detection based on FL, where the local network parameters of this improved scheme are encoded locally.