Dynamic Spectrum Access: From the Concept to the Implementation

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A Blind Beam Tracking Scheme for Millimeter Wave Systems

Millimeter-wave is one of the technologies powering the new generation of wireless communication systems. To compensate the high path-loss, millimeter-wave devices need to use highly directional antennas. Consequently, beam misalignment causes strong performance degradation reducing the link throughput or even provoking a complete outage. Conventional solutions, e.g. IEEE 802.11ad, propose the usage of additional training sequences to track beam misalignment. These methods however introduce significant overhead especially in dynamic scenarios. In this paper we propose a beamforming scheme that can reduce this overhead. First, we propose an algorithm to design a codebook suitable for mobile scenarios. Secondly, we propose a blind beam tracking algorithm based on particle filter, which describes the angular position of the devices with a posterior density function constructed by particles. The proposed scheme reduces by more than 80% the overhead caused by additional training sequences.Comment: 6 pages, 7 figure

Smart antennas: state of the art

Aim of this contribution is to illustrate the state of the art of smart antenna research from several perspectives. The bow is drawn from transmitter issues via channel measurements and modeling, receiver signal processing, network aspects, technological challenges towards first smart antenna applications and current status of standardization. Moreover, some future prospects of different disciplines in smart antenna research are given.Peer Reviewe

Fusing Event-based Camera and Radar for SLAM Using Spiking Neural Networks with Continual STDP Learning

This work proposes a first-of-its-kind SLAM architecture fusing an event-based camera and a Frequency Modulated Continuous Wave (FMCW) radar for drone navigation. Each sensor is processed by a bio-inspired Spiking Neural Network (SNN) with continual Spike-Timing-Dependent Plasticity (STDP) learning, as observed in the brain. In contrast to most learning-based SLAM systems%, which a) require the acquisition of a representative dataset of the environment in which navigation must be performed and b) require an off-line training phase, our method does not require any offline training phase, but rather the SNN continuously learns features from the input data on the fly via STDP. At the same time, the SNN outputs are used as feature descriptors for loop closure detection and map correction. We conduct numerous experiments to benchmark our system against state-of-the-art RGB methods and we demonstrate the robustness of our DVS-Radar SLAM approach under strong lighting variations

Active Inference in Hebbian Learning Networks

This work studies how brain-inspired neural ensembles equipped with local Hebbian plasticity can perform active inference (AIF) in order to control dynamical agents. A generative model capturing the environment dynamics is learned by a network composed of two distinct Hebbian ensembles: a posterior network, which infers latent states given the observations, and a state transition network, which predicts the next expected latent state given current state-action pairs. Experimental studies are conducted using the Mountain Car environment from the OpenAI gym suite, to study the effect of the various Hebbian network parameters on the task performance. It is shown that the proposed Hebbian AIF approach outperforms the use of Q-learning, while not requiring any replay buffer, as in typical reinforcement learning systems. These results motivate further investigations of Hebbian learning for the design of AIF networks that can learn environment dynamics without the need for revisiting past buffered experiences

A White Paper on Broadband Connectivity in 6G

Executive Summary This white paper explores the road to implementing broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, from extreme capacity with peak data rates up to 1 Tbps, to raising the typical data rates by orders-of-magnitude, to support broadband connectivity at railway speeds up to 1000 km/h. To achieve these goals, not only the terrestrial networks will be evolved but they will also be integrated with satellite networks, all facilitating autonomous systems and various interconnected structures. We believe that several categories of enablers at the infrastructure, spectrum, and protocol/algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric and scalable cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be used for pushing the peak rates of point-to-point links. The latter path will lead to THz communications complemented by visible light communications in specific scenarios. At the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latencies, higher reliability, and reduced complexity. Different options will be needed to optimally support different use cases. The resource efficiency can be further improved by using various combinations of full-duplex radios, interference management based on rate-splitting, machine-learning-based optimization, coded caching, and broadcasting. Finally, the three levels of enablers must be utilized not only to deliver better broadband services in urban areas, but also to provide full-coverage broadband connectivity must be one of the key outcomes of 6G

Digital compensation for analog front ends: a new approach to wireless transceiver design

The desire to build lower cost analog front-ends has triggered interest in a new domain of research. Consequently the joint design of the analog front-end and of the digital baseband algorithms has become an important field of research. It enables the wireless systems and chip designers to more effectively trade the communication performance with the production cost. Digital Compensation for Analog Front-Ends provides a systematic approach to designing a digital communication system. It covers in detail the digital compensation of many non-idealities, for a wide class of emerging broadband standards and with a system approach in the design of the receiver algorithms. In particular, system strategies for joint estimation of synchronization and front-end non-ideality parameters are emphasized. The book is organized to allow the reader to gradually absorb the important information and vast quantity of material on this subject. The first chapter is a comprehensive introduction to the emerging wireless standards which is followed by a detailed description of the front-end non-idealities in chapter two. Chapter three then uses this information to explore what happens when the topics introduced in the first two chapters are merged. The book concludes with two chapters providing an in-depth coverage of the estimation and compensation algorithms. This book is a valuable reference for wireless system architects and chip designers as well as engineers or managers in system design and development. It will also be of interest to researchers in industry and academia, graduate students and wireless network operators. Presents a global, systematic approach to the joint design of the analog front-end compensation, channel estimation, synchronization and of the digital baseband algorithms Describes in depth the main front-end non-idealities such as phase noise, IQ imbalance, non-linearity, clipping, quantization, carrier frequency offset, sampling clock offset and their impact on the modulation Explains how the non-idealities introduced by the analog front-end elements can be compensated digitally Methodologies are applied to the emerging Wireless Local Area Network and outdoor Cellular communication systems, hence covering OFDM(A), SC-FDE and MIMO Written by authors with in-depth expertise developed in the wireless research group of IMEC and projects covering the main broadband wireless standards.SCOPUS: bk.binfo:eu-repo/semantics/publishe

Comparison of the sensitivity of OFDM and SC-FDE to CFO, SCO and IQ imbalance

To better answer the user needs, new air interfaces are currently being selected for the emerging wireless communication systems. OFDM and SC-FDE are two interesting alternatives that support both the low complexity equalization of the multi-path channels. Even if the two systems benefit approximately from the same performance, they behave significantly differently in the presence of synchronization errors and front-end non-idealities. The goal of this paper is to assess the impact of CFO, SCO and IQ imbalance on the performance of the OFDM and SC-FDE systems.info:eu-repo/semantics/publishe