Abstract
In this paper, a procedure is proposed to estimate the drone-small-cells (DSC) doubly selective channels, which are sparse in 5G communications, for multiple-input-multiple-output (MIMO) orthogonal-frequency-division-multiplexing (OFDM) systems and reconstruct the transmitted data at the receiver accurately with low overhead and low computational complexity. In contrast to the previous compressed-sensing (CS)-based MIMO channel estimation (CE) methods, we propose the employment of Golden sequences instead of Bernoulli random codes to optimize the pilot amplitudes and their locations in order to increase the accuracy of the CE approach. The estimated channel is utilized for our proposed 2 dimensional (2D) adaptive channel coding procedure which consists of a Reed-Solomon (RS) code that is applied vertically, and a low-density-parity-check (LDPC) code which is applied horizontally on the transmitted data. The simulation results indicate the high accuracy of our proposed data reconstruction scheme which is achieved with low overhead and low computational complexity.
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