Wireless communication technology is one of the key technologies to achieve the key requirements of high reliability, low latency and mass connectivity in the Internet of Things (IoT). To meet these requirements, we apply the reconfigurable intelligent surface (RIS) in the wireless IoT networks. Specifically, we study a scheme that combines the joint beamforming design with RIS selection strategy for multi-RIS aided multi-cell wireless networks. In the joint beamforming design, we propose the control mode of “each base station (BS) controls its local RISs” for non-free propagation scenarios in wireless IoT networks, such as smart city and intelligent transportation system. Specifically, we give the details of algorithm for this control mode, and prove that it can achieve the performance comparable to the “all BSs jointly control all RISs” mode in the non-free propagation scenario, with lower algorithm complexity and control signaling overhead. Moreover, based on the joint beamforming design, we further propose a genetic algorithm-based RIS selection strategy to maximize the sum-rate under the constraint of limited RIS deployment. Finally, simulation results show that the proposed RIS selection strategy is effective and outperforms the existing schemes.

In this paper, we propose a security-enhanced integrated sensing and communication (ISAC) system enabled by phase-coupled Intelligent Omni-Surfaces (IOS). The IOS, without the need for additional sensors, divides the entire space into two parts: a communication part and a sensing part. The IOS serves multiple users by providing communication services while also creating a virtual line-of-sight (LOS) link for target sensing. Moreover, the IOS is utilized to ensure physical layer security. Due to the possibility of the sensing target intercepting communication information, it is crucial to limit the information leakage rate. To achieve this, we jointly design the communication beamformers, sensing beamformer, and the IOS’s two phase-shift matrices. This joint design maximizes the sensing beam pattern gain towards the target, while meeting the requirements of the minimum signal-to-interference-plus-noise ratio (SINR) for communications and the maximum information leakage to possible malicious targets. To address this problem, we propose two types of alternative algorithms. The first type utilizes an independent phase-controlling model, while the second incorporates a coupled-phase model. Both algorithms aim to optimize the IOS’s phase-shift matrices.

Reconfigurable Intelligent Surfaces (RISs) have been considered as a promising technology for next generation communications. The existing works mainly focused on the single-connected RIS, which is always mathematically characterized as diagonal phase shift matrices, because that each element of traditional RIS separately controls its status and would not like to apply influence to any other elements. Although there exist some research on sub-array RIS, the grouping conception is based on the controlling strategy level but not on the hardware realization level. Fortunately, a new type of beyond diagonal RIS (BD-RIS) is proposed with its mathematical expression is symmetric and not limited to traditional diagonal phase shift matrices. BD-RIS model can fully cover the previous various types of RIS like: reflective RIS, refractive RIS, IOS (Intelligent Omni-Surfaces) or STAR-RIS (Simultaneously Transmitting And Reflecting RIS). In this work, a new model of BD-RIS is proposed to explain its working principle. Then, the quantization strategy for the new model BD-RIS is analyzed. Finally, the optimization algorithms for BD-RIS in single-user multi-input-multi-output (SU-MISO) systems and in multi-user multi-input-multi-output (MU-MISO) systems are proposed. Simulation results verifies the effectiveness of the the algorithms’ performance.

Very large multiple input multiple output (MIMO) system (referred to as massive MIMO) is currently investigated as a novel technology to enhance system throughput for future cellular systems. In this paper, we study a practical implementation of massive MIMO technology in LTE-Advanced systems. Firstly, two three dimensional(3D) dynamic beamforming schemes are proposed to realize full spatial resolution of the elevation as well as the traditional azimuth domain. These schemes are implemented through combining a couple of precoder matrix indictor (horizontal PMI and vertical PMI) during the channel state information (CSI) feedback stage. Furthermore, we also propose a limited feedback precoding algorithm named PMI-based regularized zero-forcing precoding (P-RZF) to achieve multi-user MIMO (MU-MIMO). System level simulation is performed to evaluate the proposed schemes.

In this paper, the original Multiple Input Multiple Output (MIMO) Y channel is extended into a more generalized circumstance, called a generalized MIMO Y channel with general signal demands. The model consists of K(K≥2) nodes each equipped with Mkantennas and an intermediate relay equipped with N antennas. There is no direct link between the nodes. Therefore, supposing that node i and node j (i ≠ j∈{1,2,···, K}) exchange nijsignals, each node has to transmit mk(mk=Σi ≠ kknki, mk≤Mk) signals for other nodes in the MAC phase, and then receive mksignals in the BC phase, via the relay. Then, it's proved that Σk=1Kmkdegrees of freedom (DoF) can be achieved by making use of signal space alignment (SSA) and interference nulling beamforming in this model, when N ≥ 1/2(Σk=1Kmk) and (Mi+Mj) ≥ (N+nij).