Array & Multi-Sensor Processing

The A&MSP department gives signal and big data processing solutions to satellite communication systems and to hybrid satellite/terrestrial systems. Special expertise is in Interference Management • AI & ML • MIMO and multi-user beamforming for spatial sharing • Mmw and Thz beamforming • RF/PHY/MAC dynamic cross-layer resource allocation • Multicarrier transmission • Multi-user detection • Optical wireless modems • Large-scale optimization • Graph processing on networks

AI for Satellites

We are the inventors of latest solutions for SatComs based on the most promising tools for AI & ML.

Optical Wireless Communications

We are pioneers in the area of optical wireless, and has developed one of the first Visible Light Communications demonstrator in the world based on IEEE 802.15.7 standard.

CASTLE Platform®

CASTLE Platform®

CASTLE Platform® is a solution where standards (5G-NR, LTE, DVB-S2X, ETSI 102-744, IEEE 802.15.7) can be developed to provide futuristic solutions for solving new trends and challenges.

Hybrid Terrestrial/Satellite Air Interface for 5G and Beyond

The explosive growth of the mobile data traffic over the past few years along with the 5G targeted 1000-fold capacity improvement goal motivates the significant need for innovative solutions. These solutions should not include only the cellular, but also the optical fiber and the satellite infrastructures.

Considering these future requirements, A&MSP aims at developing hybrid terrestrial/satellite air interface for future networks. The focus is mainly on three main areas, satellite system enhancement, large-scale antenna design and signal processing schemes for hybrid satellite/terrestrial systems, and improvement of the visible light communications (VLC) schemes and optical-wireless convergence.

For the satellite system enhancement, we are developing advanced techniques for multi-beam satellite with centralized and distributed gateways. GEO and Non-GEO constellations are considered. These techniques include scheduling and radio resource management (RRM) schemes to take advantage of the payload flexibility. Moreover, the techniques include non-orthogonal superposition transmitting and receiving strategies to efficiently use the available resources. In order to reduce the deployment cost, A&MSP is investigating gate virtualization which aim at relocating most of the gateway link and physical layer functions to remote data center . Additionally, the department is developing efficient satellite content delivery techniques will be taking into account the particularity of the satellite system as well as the caching capability of some of the terrestrial network elements.

Regarding the large-scale antenna design and signal processing schemes, A&MSP is developing solutions for both below 6GHz and millimeter wave (mmWave) frequencies. Different hybrid analog-digital beamforming solutions is currently investigated. In addition, the developed antenna solutions is taking into account providing a cost-affordable solutions for the mmWave frequency range and also  is consider providing super extended base station coverage at below 6 GHz frequency range. The target applications is for both the terrestrial and the satellite segment.

The investigation on the improvement of the VLC systems is focusing on overcoming the point-to-point optical wireless links challenges like multi-path propagation, optical noise or strong optical interference. Additionally, the feasibility of implementing an all-analog fronthaul that connects a large-number of low-cost remote antennas over a single-fiber passive optical network is currently under investigation.

Finally, cloud services as an overlaying technology to coordinate transmitters from different operators. These services are meant to deal with a large amount of data signaling and information which might eventually collapse the backhaul infrastructure and; thus, Big Data techniques must be employed for levering the communication overhead generated from the coordination. Big data constitutes also the solution for dealing with the amounts of data generated by Internet of things applications that will become an important part of future networks.

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