Introducing stacked intelligent metasurfaces for low-delay computing and MU-MISO near-field systems

This paper investigates the impact of #flexible #intelligent #metasurface (#FIM) on #wireless #sensing performance. Specifically, the authors focus on the maximization of the cumulated power of the probing signals at the target locations under the per-antenna power constraint by jointly optimizing the transmit covariance matrix and the surface shape of the transmitting FIM. They propose a #block #coordinate #descend (#BCD) algorithm to find a locally optimal solution, by alternatively updating the FIM surface shape and the transmit covariance matrix, while keeping the other one fixed at each step. Furthermore, they analyze the computational complexity and convergence properties of the proposed algorithm and demonstrate that FIM enhances wireless sensing by providing a new design degree-of-freedom to coordinate the correlation between steering vectors at different angles. ---- Zihao Teng, Jiancheng An, Lu Gan, Naofal Al-Dhahir, Zhu Han More details can be found at this link: https://lnkd.in/d_2vHASP

In this work, the authors explore the performance of a #stacked #intelligent #metasurfaces (#SIM)-#aided #cell-#free #massive #multiple-#input #multiple-#output (#CF-#mMIMO) system that incorporates #joint #beamforming and #power #allocation. Specifically, they jointly design the transmit power allocation at #access #points (#APs) and the wave-based beamforming at SIMs for maximizing the system sum rate. An #alternating #optimization (#AO)-based iterative algorithm is proposed for solving the complex #non-#convex problem, which is decomposed into two subproblems. For the transmit power allocation subproblem, #maximum #ratio #transmission (#MRT) is employed to maximize signal receiving power. For the optimization subproblem of SIM #phase #shifts, a proficient gradient ascent algorithm is deployed to ensure convergence to a local optimum. ---- Yating Hu; Jiayi Zhang; @Enyu Shi; Yu Lu; Jiancheng An; Chau Yuen More details can be found at this link: https://lnkd.in/ehbX_M9v

I am happy to share that our recent paper has just been published in IEEE Transactions on Aerospace and Electronic Systems ( Early Access ). This work proposes an efficient, robust adaptive beamforming technique to deal with steering vector estimation mismatches and data covariance matrix reconstruction problems. In particular, the direction-of-arrival of interfering sources is estimated with available snapshots in which the angular sectors of the interfering signals are computed adaptively. Then, we utilize the well-known general linear combination algorithm to reconstruct the interference-plus-noise covariance matrix using preprocessing-based spatial sampling. We demonstrate that the sample covariance matrix in the shrinkage method can replace the preprocessing matrix. A power spectrum sampling strategy is then devised based on a preprocessing matrix computed with the estimated angular sectors' information. Moreover, the covariance matrix for the signal is formed for the angular sector of the signal of interest, which enables the calculation of a steering vector for the signal of interest using the power method. An analysis of the array beampattern in the proposed technique is carried out, and a study of the computational cost of competing approaches is conducted A big thank you to our amazing co-authors, Rodrigo de Lamare, Kanapathippillai Cumanan, and Yuriy Zakharov, for their dedication, insights, and collaboration throughout this work. #Robustadaptivebeamforming https://lnkd.in/ec3sX8yY

This paper introduces a novel #stacked #intelligent #metasurface (#SIM) design. Specifically, they investigate the integration of SIM into the #downlink of a #multiuser #multiple-#input #single-#output (#MISO) #communication #system, where an SIM, consisting of a #multilayer #metasurface #structure, is deployed at the #base #station (#BS) to facilitate #transmit #beamforming in the #electromagnetic #wave #domain. This eliminates the need for conventional digital beamforming and high-resolution #digital-#to-#analog #converters at the BS. To this end, an optimization problem is formulated to maximize the sum rate of all user equipments by jointly optimizing the transmit power allocation at the BS and the wave-based beamforming at the SIM, subject to constraints on the transmit power budget and discrete #phase #shifts. Furthermore, they propose a computationally efficient algorithm for solving the formulated joint optimization problem and elaborate on the potential benefits of employing SIM in wireless networks. ---- Jiancheng An; Marco Di Renzo; Merouane Debbah; Janne H.; Chau Yuen More details can be found at this link: https://lnkd.in/gw42C4-q

This letter proposes a novel system design for #downlink #rate #splitting #multiple #access (#RSMA) using #stacked #intelligent #metasurfaces (#SIM) technology. Specifically, installing the SIM at the #base #station and directly implementing #multi-#user #beamforming in the wave domain, compared to traditional digital beamforming, can simplify the transmitter structure and reduce computational load. To fully utilize the advantages of SIM and maximize user sum rate under the constraints of #base #station transmit power and #QoS rate requirements, this letter customizes an #alternating #optimization (#AO) algorithm based on the coati optimization algorithm and iterative projection gradient ascent algorithm to achieve optimization results by jointly optimizing the #common #rate, #transmit #power, and #phase #shift in the wave domain. ---- Qiwei Huai; Yuanyi Liang; Weina Yuan More details can be found at this link: https://lnkd.in/gzY_gbmn

🚀 Excited to share our latest publication in IEEE Transactions on Quantum Engineering! In this work, we address a key challenge in automating qubit tuning: the reliable detection of charge transitions in semiconductor quantum dots. We benchmark both machine learning methods and classical algorithms, trained on simulated data from the SimCATS framework, and evaluate their performance on experimental GaAs and SiGe qubit samples. Our results provide a quantitative comparison with future hardware implementations in mind — an important step toward scalable, fully automated qubit control. Read the full paper here: https://lnkd.in/eZFC8UbV Fabian Hader | Fabian Fuchs | Sarah Fleitmann | Lotte Geck | Stefan van Waasen | Forschungszentrum Jülich

In this paper, the authors propose a #hybrid #beamforming design for #stacked #intelligent #metasurfaces (#SIM) aided #wideband wireless systems relying on the #near-#field #channel model. Specifically, the holographic beamformer is designed based on configuring the #phase #shifts in each layer of the SIM for maximizing the sum of the baseband eigen-channel gains of all users. To optimize the SIM phase shifts, they propose a layer-by-layer iterative algorithm for optimizing the phase shifts in each layer alternately. Then, the #minimum #mean #square #error (#MMSE) transmit precoding method is employed for the digital beamformer to support multi-user access. Furthermore, the mitigation of the SIM phase tuning error is also taken into account in the digital beamformer by exploiting its statistics. The power sharing ratio of each user is designed based on the iterative waterfilling power allocation algorithm. ---- Qingchao Li; Mohammed El-Hajjar; Chao Xu; Jiancheng An; Chau Yuen; Lajos Hanzo More details can be found at this link: https://lnkd.in/g5_eSW3Q

This paper proposes a #stacked #intelligent #metasurfaces (#SIM)-aided #downlink #multiuser transmission scheme, where the SIM at the #base #station (#BS) is designed by combining nearly passive layers, i.e., with phase-only reconfiguration capabilities, and active layers integrated with amplifier chips to enable amplitude control. Their design aims at maximizing the sum rate for the best group of users by jointly optimizing the transmit #power #allocation at the BS and the #wave-#based #beamforming at the SIM. ---- Donatella Darsena, Francesco Verde, Ivan Iudice, Vincenzo Galdi More details can be found at this link: https://lnkd.in/eZ9CPXkb

In this paper, the authors harness a #stacked #intelligent #metasurface (#SIM) for #two-#dimensional (#2D) #direction-#of-#arrival (#DOA) #estimation. In contrast to conventional designs, an advanced SIM in front of a receiver array can be designed to automatically compute the #2D #discrete #Fourier #transform (#DFT) as the incident waves propagate through it. As a result, a receiver array can directly observe the angular spectrum of the incoming signal, and it can estimate the DOA by simply using probes to detect the energy distribution on the receiver array. This avoids the need for power inefficient #radio #frequency #chains. To enable an SIM to perform the 2D DFT in the wave domain, we formulate an optimization problem that #minimizes the #mean #square #error (#MSE) between the SIM’s #electromagnetic (#EM) response and the 2D DFT matrix. Then, a gradient descent algorithm is customized for iteratively updating the phase shift applied by each #meta-#atom of the SIM. To further improve the DOA estimation accuracy, they configure the #phase #shifts of the input layer of the SIM to generate a set of 2D DFT matrices associated with orthogonal spatial frequency bins. Additionally, they analytically evaluate the performance of the proposed SIM-based DOA estimator by deriving a tight upper bound for the MSE. ---- Jiancheng An; Chau Yuen; Yong Liang GUAN; Marco Di Renzo; Merouane Debbah; Janne H. More details can be found at this link: https://lnkd.in/gK9V84gw