Finite Blocklength Analysis for SWIPT-Enabled RSMA Networks Under Realistic Assumptions

Abstract

Abstract

Efficient connectivity for energy constrained massive Internet of Things (IoT) nodes is among the key design challenges for future wireless networks. In this work, we analyze the downlink performance of a massive IoT network considering simultaneous wireless information and power transfer (SWIPT). We consider the rate-splitting multiple access (RSMA) scheme in the finite blocklength (FBL) regime under realistic assumptions such imperfect channel state information (CSI), imperfect successive interference cancellation (SIC), and hardware impairments in the energy harvesting circuitry. The system performance is assessed by evaluating closed-form expressions for the block-error rate (BLER) and goodput. We also derive analytical expressions for the average harvested energy considering linear and non-linear characteristics of the energy-constrained IoT nodes. The effect of the power splitting (PS) factor under linear and non-linear regimes on the BLER is also discussed. Monte Carlo simulations corroborate the accuracy of the derived expressions, which highlight the impact of increasing the blocklength and demonstrate the performance degradation generated by imperfect CSI, imperfect SIC, and hardware impairment. The results reveal that the integration of PS-SWIPT in RSMA networks can offer around 28% ~ 33% performance improvement in terms of BLER over SWIPT-enabled non-orthogonal multiple access networks.