Satellite communication systems can provide seamless wireless coverage directly or through complementary groundterrestrial components and are projected to be incorporated into future wireless networks, particularly 5G and beyond networks. Increased capacity and flexibility in telecom satellite payloads based on classic radio frequency technology have traditionally translated into increased power consumption and dissipation. Much of the analog hardware in a satellite communications payload can be replaced with highly integrated digital components that are often smaller, lighter, and less expensive, as well as software reprogrammable. Digital beamforming of thousands of beams simultaneously is not practical due to the limited power available onboard satellite processors. Reduced digital beamforming power consumption would enable the deployment of a full digital payload, resulting in comprehensive user applications. Beamforming can be implemented using matrix multiplication, hybrid methodology, or a discrete Fourier transform (DFT). Implementing DFT via fast Fourier transform (FFT) reduces the power consumption, process time, hardware requirements, and chip area. Therefore, in this paper, area-power efficient FFT architectures for digital beamforming are analyzed. The area in terms of look up tables (LUTs) is estimated and compared among conventional FFT, fully unrolled FFT, and a 4-bit quantized twiddle factor (TF) FFT. Further, for the typical satellite scenarios, area, and power estimation are reported.
This paper jointly designs linear precoding (LP) and codebook-based beamforming implemented in a satellite with massive multiple-input multiple-output (mMIMO) antenna technology. The codebook of beamforming weights is built using the columns of the discrete Fourier transform (DFT) matrix, and the resulting joint design maximizes the achievable throughput under limited transmission power. The corresponding optimization problem is first formulated as a mixed integer non-linear programming (MINP). To adequately address this challenging problem, an efficient LP and DFT-based beamforming algorithm are developed by utilizing several optimization tools, such as the weighted minimum mean square error transformation, duality method, and Hungarian algorithm. In addition, a greedy algorithm is proposed for benchmarking. A complexity analysis of these solutions is provided along with a comprehensive set of Monte Carlo simulations demonstrating the efficiency of our proposed algorithms.
The Industry 4.0 paradigm conceives a cyber-physical supporting framework for the manufacturing processes in smart factories. In this context, solutions concerning the wired communications at the field-level have been reported which utilize either fieldbuses, which exhibit a huge distance range but a reduced data rate in a bus topology, or Ethernet-based technologies, which provide an increased data rate but reduced distance in a ring topology. To overcome this shortage, we propose the use of orthogonal frequency division multiplexing (OFDM) to significantly increase the achievable data rates over large distances in industrial bus systems. Also, we establish a novel methodology to compute the signal-tonoise ratio between arbitrary pairs of nodes, which in turn allows to compute the communication capacity. Our wideband system was validated by connecting up to 32 nodes in the distance range 100 m-1 km. Compared to fieldbuses, the results of the proposal exhibit an amazing improvement in data rate of about fifty times for 100 m distance and more than ten times for 0.5 km. Moreover, with respect to Ethernetbased solutions, the results show a relevant improvement in the data rate of around five times for 100 m distance, but Ethernet-based systems cannot go beyond this distance, to which our proposal is not limited.
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