Automatic modulation classification (AMC) is becoming increasingly important in spectrum monitoring and cognitive radio. However, most existing modulation classification algorithms neglect the complementarities between different features and the importance of features fusion. To remedy these flaws, this paper presents a scheme of features fusion for AMC using convolutional neural network (CNN).The approach attempts to fuse different images and handcrafted features of signals to obtain more discriminating features. First, eight handcrafted features and different images features are both extracted. In the latter, signals are converted into two kinds of time-frequency images by smooth pseudo wigner-ville distribution (SPWVD) and Born-Jordan distribution (BJD), and a fine-tuned CNN model is utilized to extract image features. Second, the joint features are formed by combined of each of image and handcrafted features, and a multimodality fusion (MMF) model is applied to fuse the joint features to yield further improvement. Finally, simulation results reveal the superior performance of the proposed scheme. It is worth mentioning that the classification accuracy can reach 92.5\% with signal-to-noise ratio at -4dB.

Since 5G new radio comes with non-standalone (NSA) and standalone (SA) versions in 3GPP, research on 6G has been on schedule by academics and industries. Though 6G is supposed to have much higher capabilities than 5G, yet there is no clear description about what 6G is. In this article, a comprehensive discussion of 6G is given based on the review of 5G developments, covering visions and requirements, technology trends and challenges, aiming at tackling the challenge of coverage, capacity, the user data rate and movement speed of mobile communication system. The vision of 6G is to fully support the development of a Ubiquitous Intelligent Mobile Society with intelligent life and industries. Finally, the roadmap of the 6G standard is suggested for the future.

Non-orthogonal multiple access (NoMA) as an efficient way of radio resource sharing can root back to the network information theory. For generations of wireless communication systems design, orthogonal multiple access (OMA) schemes in time, frequency, or code domain have been the main choices due to the limited processing capability in the transceiver hardware, as well as the modest traffic demands in both latency and connectivity. However, for the next generation radio systems, given its vision to connect everything and the much evolved hardware capability, NoMA has been identified as a promising technology to help achieve all the targets in system capacity, user connectivity, and service latency. This article will provide a systematic overview of the state-of-the-art design of the NoMA transmission based on a unified transceiver design framework, the related standardization progress, and some promising use cases in future cellular networks, based on which the interested researchers can get a quick start in this area.

As one enabling technique of the future sixth generation (6G) network, ultra-massive multiple-input-multiple-output (MIMO) can support high-speed data transmissions and cell coverage extension. However, it is hard to realize the ultra-massive MIMO via traditional phased arrays due to unacceptable power consumption. To address this issue, reconfigurable intelligent surface-based (RIS-based) antennas are an energy-efficient enabler of the ultra-massive MIMO, since they are free of energy-hungry phase shifters. In this article, we report the performances of the RIS-enabled ultra-massive MIMO via a project called Verification of MmWave Multi-stream Transmissions Enabled by RIS-based Ultra-massive MIMO for 6G (V4M), which was proposed to promote the evolution towards IMT-2030. In the V4M project, we manufacture RIS-based antennas with 1024 one-bit elements working at 26 GHz, based on which an mmWave dual-stream ultra-massive MIMO prototype is implemented for the first time. To approach practical settings, the Tx and Rx of the prototype are implemented by one commercial new radio base station and one off-the-shelf user equipment, respectively. The measured data rate of the dual-stream prototype approaches the theoretical peak rate. Our contributions to the V4M project are also discussed by presenting technological challenges and corresponding solutions.