Spectral and Energy Efficiency Maximization of MISO STAR-RIS-assisted URLLC Systems
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This paper proposes a general optimization framework to improve the spectral and energy efficiency (EE) of ultra-reliable low-latency communication (URLLC) reconfigurable intelligent surface (RIS)-assisted interference-limited systems with finite block length (FBL). This framework can be applied to any interference-limited system with treating interference as noise as the decoding strategy at receivers. Additionally, the framework can solve a large variety of optimization problems in which the objective and/or constraints are linear functions of the rates and/or EE of users. We consider a multi-cell broadcast channel as an example and show how this framework can be specialized to solve the minimum-weighted rate, weighted sum rate, global EE and weighted EE of the system. In addition to regular RIS, we consider simultaneous-transfer-and-receive (STAR)-RIS in which each passive RIS component can simultaneously reflect and transmit signals. We make realistic assumptions regarding the (STAR-)RIS by considering three different feasibility sets for the components of either regular RIS or STAR-RIS. We show that RIS can substantially increase the spectral and EE of RIS-assisted URLLC systems if the reflecting coefficients are properly optimized. Moreover, we show that STAR-RIS can outperform a regular RIS when the regular RIS cannot cover all the users.
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