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.
翻译:本文提出一个多目标优化问题(MOOP),以便在可调整的智能表面(RIS)辅助短包通信系统中最大限度地降低可实现的有限区长(FBL)率,同时最大限度地减少已使用的频道区长(CBL),同时最大限度地减少已使用的频道区长(CBL)率。已拟订的MOOP有两个客观功能,即:在目标误差概率下最大限度地提高FBL总比率,并尽量减少直接与传输时间相称的已使用CBL总量。考虑的MOOP变量是基站传输功率、CBL数量和RIS被动波段。由于拟议的非CBL问题难以解决,因此将Tchebyshev方法用于将其转化为单一目标的OP,然后采用交替优化(AO)技术,以迭接方式获得三个主要子问题的优化参数。数字结果显示,在尽量提高FBL系统中可实现的速率和缩短传输时间长度之间有着根本的利弊。此外,在减少已使用的CBBLS技术的适用性方面强调了RIS技术的适用性,同时大幅度提高可实现率。