Implementation of Deep-Learning-Based CSI Feedback Reporting on 5G NR-Compliant Link-Level Simulator

Advances in machine learning have widened the range of its applications in many fields. In particular, deep learning has attracted much interest for its ability to provide solutions where the derivation of a rigorous mathematical model of the problem is troublesome. Our interest was drawn to the application of deep learning for channel state information feedback reporting, a crucial problem in frequency division duplexing (FDD) 5G networks, where knowledge of the channel characteristics is fundamental to exploiting the full potential of multiple-input multiple-output (MIMO) systems. We designed a framework adopting a 5G New Radio convolutional neural network, called NR-CsiNet, with the aim of compressing the channel matrix experienced by the user at the receiver side and then reconstructing it at the transmitter side. In contrast to similar solutions, our framework is based on a 5G New Radio fully compliant simulator, thus implementing a channel generator based on the latest 3GPP 3-D channel model. Moreover, realistic 5G scenarios are considered by including multi-receiving antenna schemes and noisy downlink channel estimation. Simulations were carried out to analyze and compare the performance with current feedback reporting schemes, showing promising results for this approach from the point of view of the block error rate and throughput of the 5G data channel

Regenerative approaches for V/UHTS feeder links: system analysis and on-board complexity reduction

The dramatically increasing demand for high data rates necessitates the proper dimensioning of the feeder links of very or ultra high throughput satellite (V/UHTS) systems. However, because most of the current solutions rely on transparent payloads, the deployment of a very large number of spatially separated ground stations is necessary to support the total system bandwidth by enabling a full reuse of the scarce available uplink bandwidth. This approach has a significant impact on the complexity and the costs of the ground segment infrastructure. Regenerative payloads could be considered to avoid this design bottleneck. By allowing demodulation and decoding on-board the satellite, the favourable link budget conditions of feeder links compared to the user links can be exploited. Using a spectral efficient transmission technique, the number of ground stations required to support a target sum throughput can be notably reduced. Meanwhile, regenerative solutions have until now barely been used in V/UHTS payloads due to their high on-board power consumption. As a consequence, candidate solutions are proposed in this work to overcome this limitation. A non-coherent modulation technique, known as Differential Amplitude Phase Shift Keying (DAPSK), is introduced to avoid on-board carrier synchronization. Moreover, polar codes are considered to minimize the power consumption of the channel decoder. A preliminary analysis of the expected on-board power consumption compared to that of a standard DVB-S2 approach is conducted using available results in the open literature. Link performance is also evaluated via numerical simulations

SOT-MRAM 300mm integration for low power and ultrafast embedded memories

We demonstrate for the first time full-scale integration of top-pinned perpendicular MTJ on 300 mm wafer using CMOS-compatible processes for spin-orbit torque (SOT)-MRAM architectures. We show that 62 nm devices with a W-based SOT underlayer have very large endurance (> 5x10^10), sub-ns switching time of 210 ps, and operate with power as low as 300 pJ.Comment: presented at VLSI2018 session C8-

Fieldlike and antidamping spin-orbit torques in as-grown and annealed Ta/CoFeB/MgO layers

We present a comprehensive study of the current-induced spin-orbit torques in perpendicularly magnetized Ta/CoFeB/MgO layers. The samples were annealed in steps up to 300 degrees C and characterized using x-ray absorption spectroscopy, transmission electron microscopy, resistivity, and Hall effect measurements. By performing adiabatic harmonic Hall voltage measurements, we show that the transverse (field-like) and longitudinal (antidamping-like) spin-orbit torques are composed of constant and magnetization-dependent contributions, both of which vary strongly with annealing. Such variations correlate with changes of the saturation magnetization and magnetic anisotropy and are assigned to chemical and structural modifications of the layers. The relative variation of the constant and anisotropic torque terms as a function of annealing temperature is opposite for the field-like and antidamping torques. Measurements of the switching probability using sub-{\mu}s current pulses show that the critical current increases with the magnetic anisotropy of the layers, whereas the switching efficiency, measured as the ratio of magnetic anisotropy energy and pulse energy, decreases. The optimal annealing temperature to achieve maximum magnetic anisotropy, saturation magnetization, and switching efficiency is determined to be between 240 degrees and 270 degrees C