Interference is the major bottleneck for the performance of the two-way K-user interference channel. In this paper, we demonstrate that by employing a reconfigurable intelligent surface (RIS), we can indeed achieve the interference-free degree of freedom (DoF). Mathematically, achieving interference-free DoF amounts to finding the solutions of a linear system with the modulus-1 constraint. To address this challenging problem, we take a geometric perspective and leverage the tools of high-dimensional probability. As a result, we are able to provide the nearly exact characterizations of both the maximal and the minimal number of RIS elements required for the interference-free DoF. Simulation results match our theoretical prediction quite well.

Analog self-interference cancellation (A-SIC) plays a crucial role in the implementation of in-band full-duplex (IBFD) radios, due to the fact that the inherent transmit (Tx) noise can only be addressed in the analog domain. It is thus natural to ask what the performance limit of A-SIC is in practical systems, which is still quite underexplored so far. In this paper, we aim to close this gap by characterizing the fundamental performance of A-SIC which employs the common multi-tap delay (MTD) architecture, by accounting for the following practical issues: 1) Nonstationarity of the Tx signal; 2) Nonlinear distortions on the Tx signal; 3) Multipath channel corresponding to the self-interference (SI); 4) Maximum amplitude constraint on the MTD tap weights. Our findings include: 1) The average approximation error for the cyclostationary Tx signals isequal tothat for thestationarywhiteGaussianprocess, thus greatly simplifying the performance analysis and the optimization procedure. 2) The approximation error for the multipath SI channel can bedecomposedas the sum of the approximation error for the single-path scenario. By leveraging these structural results, the optimization framework and algorithms which characterize the fundamental limit of A-SIC, by taking into account all the aforementioned practical factors, are provided.

Abstract An intelligent‐reflecting‐surface aided multigroup multicast communication system is investigated in this paper. We develop energy‐efficient designs for both the precoding matrix at the base station and passive reflecting beamforming at intelligent‐reflecting‐surface, subject to the minimum signal‐to‐interference‐plus‐noise ratio constraint of each user and the unit‐modulus constraint imposed by passive intelligent‐reflecting‐surface. This leads to a complex non‐convex problem for which to tackle we propose two novel algorithms based on alternating optimization techniques. Specifically, one algorithm employs semi‐definite relaxation to obtain the suboptimal reflection coefficient vector and suboptimal precoding vector for each group. In order to reduce the computational complexity, the second algorithm transforms this non‐convex problem into two second‐order cone programming problems. Numerical results show that intelligent‐reflecting‐surface can significantly reduce the power consumption of the base station.