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This study delves into the innovative landscape of metasurfaces, with a particular focus on their role in achieving EM illusion (EMI) a facet of paramount significance. The control of EM waves assumes a pivotal role in mitigating issues such as signal degradation, interference, and reduced communication range. Furthermore, the engineering of waves serves as a foundational element in achieving invisibility or minimized detectability. This survey unravels the theoretical underpinnings and practical designs of EMI coatings, which have been harnessed to develop functional metasurfaces. EMI, practically achieved through engineered coatings, confers a strategic advantage by either reducing the radar cross-section of objects or creating misleading footprints. In addition to illustrating the outstanding achievements in reconfigurable cloaking, this study culminates in the proposal of a novel approach, suggesting the emergence of EMI without the need for physically coating the device to conceal and thus proposing the concept of a smart EMI environment. This groundbreaking work opens a new way for engineers and researchers to unlock exotic and versatile designs that build on reconfigurable intelligent surfaces (RIS). Crucially the designs enabled by the proposed approach, present a wide array of applications, encompassing camouflaging, deceptive sensing, radar cognition control, and defence security, among others. In essence, this research stands as a beacon guiding the exploration of uncharted territories in wave control through smart EMI environments, with profound implications spanning basic academic research in RIS through advanced security technologies and communication systems.

This paper proposes a novel transmission policy for an intelligent reflecting surface (IRS) assisted wireless powered sensor network (WPSN). An IRS is deployed to enhance the performance of wireless energy transfer (WET) and wireless information transfer (WIT) by intelligently adjusting phase shifts of each reflecting elements. To achieve its self-sustainability, the IRS needs to collect energy from energy station to support its control circuit operation. Our proposed policy for the considered WPSN is called IRS assisted harvest-then-transmit time switching, which is able to schedule the transmission time slots by switching between energy collection and energy reflection modes. We study the achievable sum throughput of the proposed transmission policy and investigate a joint design of the transmission time slots, the power allocation, as well as the discrete phase shifts of the WET and WIT. This formulates the problem as a mixed-integer non-linear program, which is NP-hard and non-convex. We first relax it to one with continuous phase shifts, and then propose a two-step approach and decompose the original problem into two sub-problems. We solve the first sub-problem with respect to the phase shifts of the WIT in terms of closed-form expression. For the second sub-problem, we consider a special case without the circuit power of each sensor node, the Lagrange dual method and the KKT conditions are applied to derive the optimal closed-form transmission time slots, power allocation, and phase shift of the WET. Then we generalise the case with the circuit power of each sensor node, which can be solved via employing a semi-definite programming relaxation. The optimal discrete phase shifts can be obtained by quantizing the continuous values. Numerical results demonstrate the effectiveness of the proposed policy and validate the beneficial role of the IRS in comparison to the benchmark schemes., Comment: 16 pages, 13 figures

A low complexity massive multiple-input multiple-output (MIMO) technique is studied with a geometry-based stochastic channel model, called COST 2100 model. We propose to exploit the discrete-time Fourier transform of the antenna correlation function to perform user scheduling. The proposed algorithm relies on a trade off between the number of occupied bins of the eigenvalue spectrum of the channel covariance matrix for each user and spectral overlap among the selected users. We next show that linear precoding design can be performed based only on the channel correlation matrix. The proposed scheme exploits the angular bins of the eigenvalue spectrum of the channel covariance matrix to build up an "approximate eigenchannels" for the users. We investigate the reduction of average system throughput with no channel state information at the transmitter (CSIT). Analysis and numerical results show that while the throughput slightly decreases due to the absence of CSIT, the complexity of the system is reduced significantly., Comment: IEEE TVT 2019, 7 pages, 4 figures