Open-set recognition (OSR) is a realistic problem in wireless signal recognition, which means that during the inference phase there may appear unknown classes not seen in the training phase. The method of intra-class splitting (ICS) that splits samples of known classes to imitate unknown classes has achieved great performance. However, this approach relies too much on the predefined splitting ratio and may face huge performance degradation in new environment. In this paper, we train a multi-task learning (MTL) network based on the characteristics of wireless signals to improve the performance in new scenes. Besides, we provide a dynamic method to decide the splitting ratio per class to get more precise outer samples. To be specific, we make perturbations to the sample from the center of one class toward its adversarial direction and the change point of confidence scores during this process is used as the splitting threshold. We conduct several experiments on one wireless signal dataset collected at 2.4 GHz ISM band by LimeSDR and one open modulation recognition dataset, and the analytical results demonstrate the effectiveness of the proposed method.

This paper considers outdoor fingerprinting localization in LTE cellular Networks, which can localize non-cooperative user equipment (UEs) that is unwilling to provide Global Positioning System (GPS) information. We propose a low-cost fingerprinting localization scheme that can improve the localization accuracy while reducing the computational complexity. Firstly, a data filtering strategy is employed to filter the fingerprints which are far from the target UE by using the Cell-ID, Timing Advance (TA) and eNodeB environment information, and the distribution of TA difference is analyzed to guide how to use TA rationally in the filtering strategy. Then, improved Weighted K Nearest Neighbors (WKNN) are implemented on the filtered fingerprints to give the final location prediction, and the WKNN is improved by removing the fingerprints that are still far away from the most of the K neighbors. Experiment results show that the performance is improved by the proposed localization scheme, and positioning errors corresponding to Cumulative Distribution Function (CDF) equaling to 67% and 95% are declined to 50 m and 150 m.

To meet the booming development of diversified services and new applications in the future, the fifth-generation mobile communication system (5G) has arisen. Resources are increasingly scarce in the dynamic time-varying of 5G networks. Allocating resources effectively and ensuring quality of service (QoS) requirements of multi-services come to be a research focus. In this paper, we utilize effective capacity to build a utility function with multi-QoS metrics, including rate, delay bound and packet loss ratio. Taking advantage of opportunity cost (OC), we also propose a multi-QoS guaranteed resource allocation algorithm for multi-services to consider the future condition of system. In the algorithm, according to different business characteristics and the theory of OC, we propose different selection conditions for QoS users and best effort (BE) users to choose more reasonable resources. Finally, simulation results show that our proposed algorithm achieves superior system utility and relatively better fairness in multi-service scenarios.

Coordinated Multi-Point (CoMP ) transmission/ reception technology has been the focus of much attention recently and has becom a key research interest in 3GPP LTE-Advanced due to its ability to improve both cell-edge and average system performance. However, CoMP technology requires brand-new handover mechanism, or else its real performance will be limited. This paper proposes a novel handover mechanism supporting CoMP based on the handover scenario in CoMP communication system architecture, including information sharing and signaling transmission procedure of CoMP cooperating sets handover and CoMP transmission points selection/update. The proposed scheme could not only support CoMP well, but also reduce the overhead of information exchange and signaling transmission.