Joint Sum Rate and Blocklength Optimization in RIS-aided Short Packet URLLC Systems

TL;DR

This paper introduces a multi-objective optimization framework for RIS-assisted short packet communication systems, balancing finite blocklength rate maximization and channel blocklength minimization to improve ultra-reliable low-latency communication.

Contribution

It formulates a novel multi-objective optimization problem for RIS-aided systems and proposes an effective solution method to optimize power, blocklengths, and beamforming.

Findings

Trade-off between achievable rate and transmission duration identified.

RIS technology significantly improves rate and reduces channel blocklengths.

Proposed optimization method effectively balances system performance objectives.

Abstract

In this paper, a multi-objective optimization problem (MOOP) is proposed for maximizing the achievable finite blocklength (FBL) rate while minimizing the utilized channel blocklengths (CBLs) in a reconfigurable intelligent surface (RIS)-assisted short packet communication system. The formulated MOOP has two objective functions namely maximizing the total FBL rate with a target error probability, and minimizing the total utilized CBLs which is directly proportional to the transmission duration. The considered MOOP variables are the base station (BS) transmit power, number of CBLs, and passive beamforming at the RIS. Since the proposed non-convex problem is intractable to solve, the Tchebyshev method is invoked to transform it into a single-objective OP, then the alternating optimization (AO) technique is employed to iteratively obtain optimized parameters in three main sub-problems. The numerical results show a fundamental trade-off between maximizing the achievable rate in the FBL regime and reducing the transmission duration. Also, the applicability of RIS technology is emphasized in reducing the utilized CBLs while increasing the achievable rate significantly.