Shannon Wireless’ Post

#Stacked #intelligent #metasurfaces (#SIM) represents an advanced signal processing paradigm that enables over-the-air processing of electromagnetic waves at the speed of light. Its multi-layer structure exhibits customizable increased computational capability compared to conventional single-layer reconfigurable intelligent surfaces and metasurface lenses. In this paper, the authors deploy SIM to improve the performance of #multi-#user #multiple-#input #single-#output (#MISO) wireless systems with low complexity transmit #radio #frequency (#RF) chains. In particular, an optimization formulation for the joint design of the SIM phase shifts and the transmit power allocation is presented, which is efficiently solved via a customized #deep #reinforcement #learning (DRL) approach that continuously observes pre-designed states of the SIM-parametrized smart wireless environment. ---- Jiancheng An, George Alexandropoulos More details can be found at this link: https://lnkd.in/gBgs5aZe

Check this promising concept for further wireless functionalities with programmable metamaterials, more details to come very soon #6G #wirelesscommunications #metamaterials #metasurfaces #computing

This paper investigates the integration of #stacked #intelligent #metasurface (#SIM) into the downlink of a #multiuser #multiple-#input #single-#output (#MISO) communication system, where a 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, the authors formulate an optimization problem that aims to maximize the sum rate of all user equipment by jointly optimizing the transmit power allocation at the BS and the wave-based beamforming at the SIM, subject to both the transmit power budget and discrete phase shift constraints. Furthermore, they propose a computationally efficient algorithm for solving this joint optimization problem and elaborate on the potential benefits of employing SIM in wireless networks. ----Jiancheng An, @Marco Di Renzo, @H. Vincent Poor, Chau Yuen More details can be found at this link: https://lnkd.in/gRMQX2Wf

#Stacked #intelligent #metasurfaces (#SIM) is a revolutionary technology, which can outperform its single-layer counterparts by performing advanced signal processing relying on wave propagation. In this work, the authors exploit SIM to enable transmit precoding and receiver combining in #holographic #multiple-#input ##multiple-#output (#HMIMO) communications, and they study the achievable rate by formulating a joint optimization problem of the SIM phase shifts at both sides of the transceiver and the covariance matrix of the transmitted signal. Notably, they propose its solution by means of an iterative optimization algorithm that relies on the projected gradient method, and accounts for all optimization parameters simultaneously. They also obtain the step size guaranteeing the convergence of the proposed algorithm. ---- Anastasios Papazafeiropoulos, Ph.D., SMIEEE, Jiancheng An, Pandelis Kourtessis, Tharmalingam Ratnarajah, Symeon Chatzinotas More details can be found at this link: https://lnkd.in/evxgkQcy

#Stacked #intelligent #metasurfaces (#SIM) is a revolutionary technology, which can outperform its single-layer counterparts by performing advanced signal processing relying on wave propagation. In this work, the authors exploit SIM to enable transmit precoding and receiver combining in #holographic #multiple-#input #multiple-#output (#HMIMO) communications, and they study the achievable rate by formulating a joint optimization problem of the SIM phase shifts at both sides of the transceiver and the covariance matrix of the transmitted signal. Notably, the authors propose its solution by means of an iterative optimization algorithm that relies on the projected gradient method, and accounts for all optimization parameters simultaneously. They also obtain the step size guaranteeing the convergence of the proposed algorithm. ---- Anastasios Papazafeiropoulos, Ph.D., SMIEEE, Jiancheng An, Pandelis Kourtessis, Symeon Chatzinotas More details can be found at this link: https://lnkd.in/evxgkQcy

Who said that entropy search based Bayesian optimization is not as effective as local approaches such as expected improvement in the high dimensional regime? This approach suggests a method based on entropy search that is effective in the high dimensional scenario, assuming correlations between dimensions. Practical approach that may work for some high-dimensional problems, typically in engineering, where some variables, like sensors, are very correlated. https://lnkd.in/dRJ8MtXr

"Researchers have unveiled a technology that propels the field of wireless communication forward. This cutting-edge design, termed a reconfigurable transmissive metasurface, utilizes a synergistic blend of scissor and rotation actuators to independently manage beam scanning and polarization conversion. This introduces an innovative approach to boosting signal strength and efficiency within wireless networks. Reconfigurable metasurfaces are transforming wireless communication by adjusting electromagnetic (EM) wave characteristics such as amplitude, phase, and polarization. These planar arrays enhance wave control, boosting functionalities like polarization conversion and beam scanning. Polarization conversion modifies an EM wave's polarization state, and beam scanning enables directional adjustment of EM waves." #metasurface #wirelesssignals

Multi-User Multiple-Input Multiple Output (MU-MIMO) technology is an essential technique for wireless signal transmission for 5G technologies, that allows for an increase in transmission speed and the number of users that can be connected simultaneously. However, this technique presents some technical challenges, such as signal decoding, that require state-of-the-art hardware and algorithms to be tackled effectively and efficiently. 📌 With Quside’s RPUs and cutting-edge stochastic methods, we keep latency low and boost transmission reliability. These improvements can imply multiple benefits to MIMO technologies! 🚀 Do you want to know more?? Read the full case study 👇 https://lnkd.in/dexbW3hr

Our paper on adaptive trajectory synchronization for human-robot collaboration in the presence of time delayed information is accepted for publication to IEEE L-CSS. The controller synchronizes robot trajectory to the human trajectory by accounting for time delays that arise due to estimating human trajectory using image processing, or sensor fusion for trajectory intent estimation, or computational limitations while carrying out joint human-robot collaboration tasks in manufacturing settings.  #cybermanufacturing #cphs