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Field
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foundations in waveform design and advanced signal processing. In particular, energy-efficient precoding algorithms have been developed for distributed MIMO systems and are currently validated through numerical
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time delays need to be compensated [6]. Accurate channel estimation is known to be a difficult task in UM-MIMO settings [7,8] as it usually relies only on pilot symbols to estimate a large number of
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theoretical background for MIMO related research, and have attended courses such as Information Theory, Signal and Systems, Modulation and Detection. Experience with OFDM or single carrier baseband algorithms
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constant LoS between a base station (BS) and the user equipment (UE), illuminating shadow regions whilst being energy efficient [1]. Solutions such as cell-free massive MIMO [2] and Reconfigurable
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scheduling and asynchronous access strategies for future wireless systems, with particular attention to mobility, spatial non-stationarity, and scalable device connectivity in extra-large MIMO deployments
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covers the aspects of sensing, detection and classification in radar-based perception. Key competencies/skills required for the project: signal/array processing, machine learning/AI, MIMO/Radar systems
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processing and wireless communication systems (OFDM, MIMO, …) Proficiency in a hardware description language (VHDL or Verilog) Ideally, initial experience with FPGAs (Xilinx Vivado, Zynq Ultrascale
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is seeking a highly motivated PhD candidate to work in the field of Extra-Large MIMO (XL-MIMO) communications, also known as ultra-massive MIMO. This emerging technology dramatically scales up antenna
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, Communication Technology, or a similar field Knowledge or interest in digital signal processing and wireless communication systems (OFDM, MIMO, …) Proficiency in a hardware description language (VHDL or Verilog
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may refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . The successful candidate will conduct research on quantum MIMO systems, focusing on the development of theoretical models, communication