Research On Transmission And Access Techniques Of LEO Satellite Internet Of Things

In recent years,low-earth orbit(LEO)satellite Internet of Things(IoT)has attracted extensive attention and research due to its wide coverage.However,due to limited spectrum and energy resources,LEO satellite IoT cannot support massive device access and data transmission,and thus is difficult to meet the needs of further development of IoT.In this case,according to the characteristics and requirements of the IoT for LEO satellites,this paper proposes three feasible transmission and access schemes with high energy efficiency and high spectral efficiency.Firstly,for downlink transmission,a non-orthogonal transmission framework is designed for LEO satellite IoT to support efficient transmission of massive data packets.Considering the finite energy of LEO satellites and the uncertainty of channel state information,an optimization problem was formulated to maximize the energy efficiency of non-orthogonal transmission under the constraints of power and signal-to-interference-plus-noise ratio.By converting the fractional form problem into an equivalent subtractive form optimization problem,a robust joint beamforming and power allocation algorithm is obtained.Both theoretical analysis and simulation results verify the effectiveness and robustness of the proposed algorithm.Secondly,for uplink access,a grant-free random access architecture of LEO satellite IoT is proposed to support low-delay access of massive devices.Each activated device maps the data to a codeword in a codebook,which is then sent to a LEO satellite.By using a joint device detection and data recovery algorithm,the satellite detects the active codeword and then obtains the activated device and the corresponding data.Simulation results show that the proposed algorithm has wider applicability and better performance than baseline algorithms.Next,for uplink reception,a low-resolution equalization scheme is proposed for LEO satellite IoT to support low-cost signal decoding.The dimension of the received signal is first reduced by preprocessing based on discrete Fourier transformation.Then,the optimal element is selected from a finite number of equalization coefficient value set by using a grouping-based branch and bound method to construct the low-resolution equalization matrix.Simulation results show that the proposed algorithm can effectively reduce the resolution of the equalizer and decrease the power consumption of the satellite while ensuring the equalization performance.