With practical finite alphabet inputs, usually the throughput of a practical communication system cannot reach the capacity based on assumption of Gaussian inputs. In this paper, we study the resource… Click to show full abstract
With practical finite alphabet inputs, usually the throughput of a practical communication system cannot reach the capacity based on assumption of Gaussian inputs. In this paper, we study the resource allocation strategy for multiple-input multiple-output (MIMO) full-duplex backscatter assisted wireless-powered communication network (FD-BAWPCN) with finite alphabet inputs, to maximize the sum-throughput. Firstly, we propose a gradient-based resource allocation strategy (GBRA), which alternately optimizes the precoder and time allocation based on the two-block alternating direction method of multipliers (ADMM). Secondly, to reduce the computational complexity and improve the feasibility of the strategy in practical applications, we further propose a codebook-based resource allocation strategy (CBRA), which can run more than three orders of magnitude faster than GBRA at the expense of a small sum-rate degradation. Then, the performance of the full-duplex (FD) and half-duplex (HD) system with or without backscatter assistance using GBRA are compared and analyzed. Numerical results demonstrate that the GBRA strategy has great robustness under various conditions but suffers a high computational complexity, and the CBRA strategy is effective and converges speedily.
               
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