Wideband channel sensing with holographic interference surfaces

The Holographic Interference Surface (HIS) opens up a new prospect for building a more cost-effective wireless communication architecture by performing Radio Frequency (RF) domain signal processing. In this paper, we establish a wideband channel sensing architecture for electromagnetic wave reception and channel estimation based on the principle of holographic interference theory. Dute to the nonlinear structure of holograms, interferential fringes composed of wideband RF signals exhibit severe self-interference effects in the time-frequency domain, which are inherently resistant to the classical signal processing tools. To overcome the self-interference, we propose a holographic channel recovery method, which analyzes the time-domain variation of holograms from a geometrical perspective and constructs an inverse mapping from wideband holograms to object waves. Based on the Wirtinger partial derivative and Armijo condition, we then develop a wideband hologram-based maximum likelihood (WH-ML) estimation method for estimating the channel state information (CSI) from holograms. We also propose a geometric rotation-based object wave sensing (GROWS) algorithm to address the complicated computation of ML estimation. Furthermore, we derive the Cram\'er-Rao lower bound (CRLB) for investigating the achievable performance of wideband holographic channel estimation. Simulation results show that under the wideband channel sensing architecture, our proposed algorithm can accurately estimate the CSI in wideband scenarios.

Channel sensing for holographic MIMO surfaces based on interference principle

The Holographic Multiple-Input and Multiple-Output (HMIMO) provides a new paradigm for building a more cost-effective wireless communication architecture. In this paper, we derive the principles of holographic interference theory for electromagnetic wave reception and transmission, whereby the optical holography is extended to communication holography and a channel sensing architecture for holographic MIMO surfaces is established. Unlike the traditional pilot-based MIMO channel estimation approaches, the proposed architecture circumvents the complicated processes like filtering, analog to digital conversion (ADC), down conversion. Instead, it relies on interfering the object waves with a pre-designed reference wave, and therefore reduces the hardware complexity and requires less time-frequency resources for channel estimation. To address the self-interference problem in the holographic recording process, we propose a phase shifting-based interference suppression (PSIS) method according to the structural characteristics of communication hologram and interference composition. We then propose a Prony-based multi-user channel segmentation (PMCS) algorithm to acquire the channel state information (CSI). Our theoretical analysis shows that the estimation error of the PMCS algorithm converges to zero when the number of HMIMO surface antennas is large enough. Simulation results show that under the holographic architecture, our proposed algorithm can accurately estimate the CSI in multi-user scenarios.