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To deal with the resource competition among satellites in the multi-satellite space-ground computing network, a space-ground heterogeneous resource cooperative game mechanism was designed in terms of the computing and spectrum domains.Each satellite published a computing task which was independent of other tasks and relied on UE to generate raw data.By competing the resources of user terminals and UE, the task offloading and processing was achieved.To provide real-time data services, a distributed scheme was proposed based on multi-agent reinforcement learning to coordinate the computing and spectrum resource competition among satellites, thereby minimizing the system latency.Simulation results indicated that, compared with the existing schemes, the proposed algorithm achieves a lower system latency by fully utilizing the computing and spectrum resources and coordinating the resource competition.

Ultra-dense low earth orbit (LEO) satellite communication networks can overcome the scarcity of spectrum resources and the limited coverage of traditional terrestrial networks, and thus have the potential to provide high data rate services and global massive connectivity for terrestrial users.However, due to the high mobility of the satellites, LEO satellite networks put more stringent requirements on antenna technologies in terms of accurate beam steering and high antenna gain.Reconfigurable holographic surface (RHS), as a new type of metamaterial antenna, is investigated to assist LEO satellite communications.The RHS can electronically control the metamaterial units by leveraging the holographic principle to generate desired directional beams.Based on the hardware structure and holographic working principle of RHS, an RHS-assisted multi-satellite communication scheme was proposed, which considered both the LEO satellite tracking scheme and the data transmission scheme.A holographic beamforming optimization algorithm was also designed to maximize the sum rate.Simulation results verify the effectiveness of the proposed scheme and demonstrat that the RHS provids a more cost-effective way to support satellite communications than the conventional phased array antennas.

Abstract Reconfigurable intelligent surface (RIS) has drawn great attention as a promising technique that triggers a revolution in multi‐antenna systems. It can intelligently reconstruct the propagation environments passively without extra hardware or power consumption. In this paper, the multi‐RIS aided downlink multi‐cell communication systems are considered. Adjacent base stations (BSs) are allowed to share and jointly control the same RISs to mitigate the influence brought by the inter‐cell interference. For the sum‐rate maximisation, a distributed negotiation mechanism is designed where each BS only communicates with its neighbours to reach a consensus on the RIS‐based analogue beamforming. Meanwhile, given the incomplete knowledge of other cells, each BS independently optimises its digital beamformer based on its iteratively updated estimates over the other cells without revealing any location and channel information of its own serving users. Simulation results show that the proposed scheme achieves a close performance compared to the centralised scheme, and much better than the traditional no‐RIS system. The influence of the discrete phase shifts and the RIS size on the system performance are also evaluated.

At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) in combination with leading-edge technologies, methodologies, and architectures are poised to be a cornerstone technology. Capitalizing on its successful integration and scalability within 5G and beyond, massive MIMO has proven its merits and adaptability. Notably, a series of evolutionary advancements and revolutionary trends have begun to materialize in recent years, envisioned to redefine the landscape of future 6G wireless systems and networks. In particular, the capabilities and performance of future massive MIMO systems will be amplified through the incorporation of cutting-edge technologies, structures, and strategies. These include intelligent omni-surfaces (IOSs)/intelligent reflecting surfaces (IRSs), artificial intelligence (AI), Terahertz (THz) communications, and cell-free architectures. In addition, an array of diverse applications built on the foundation of massive MIMO will continue to proliferate and thrive. These encompass wireless localization and sensing, vehicular communications, non-terrestrial communications, remote sensing, and inter-planetary communications, among others.

With the development of the Internet of things,multiple real-time applications will emerge in future 6G communication network.Driven by demands on low-latency services of multiple real-time applications,mobile edge computing (MEC) will become an important technology to improve the user experience and reduce the network cost.However,the computing capacity of a single MEC server is limited,which induces that it is difficult to meet the low-latency requirement of data processing for the computation-intensive applications.A heterogeneous multi-layer mobile edge computing (HetMEC) network architecture was proposed to jointly utilize the computing and transmission resources of both the cloud computing center and multi-layer MEC servers.By reasonably dividing and offloading computing tasks,reliable and efficient computing services were provided for edge applications.Simulation results show that the proposed algorithm could effectively reduce the processing latency,improve the network processing rate and robustness.