FBC-Enhanced {\epsilon}-Effective Capacity Optimization for NOMA

TL;DR

This paper develops an optimization framework for uplink FBC-enhanced NOMA systems to maximize capacity and energy efficiency while ensuring strict delay and error-rate QoS constraints, addressing a critical challenge in next-generation wireless networks.

Contribution

It formulates and solves { extquoteright}{ extquoteright}epsilon{ extquoteright}{ extquoteright}-effective capacity problems for uplink FBC-enhanced NOMA, introducing optimal power allocation policies under statistical QoS constraints.

Findings

Optimized power allocation improves capacity and energy efficiency.

Proposed schemes meet strict delay and error-rate QoS requirements.

Simulation results validate the effectiveness of the optimization methods.

Abstract

The advent of massive ultra-reliable and low-latency communications (mURLLC) has introduced a critical class of time- and reliability-sensitive services within next-generation wireless networks. This shift has attracted significant research attention, driven by the need to meet stringent quality-of-service (QoS) requirements. In this context, non-orthogonal multiple access (NOMA) systems have emerged as a promising solution to enhance mURLLC performance by providing substantial enhancements in both spectral efficiency and massive connectivity, particularly through the development of finite blocklength coding (FBC) techniques. Nevertheless, owing to the dynamic nature of wireless network environments and the complex architecture of FBC-enhanced NOMA systems, the research on the efficient design of optimizing the system performance for maximizing system capacity while guaranteeing the tail distributions in terms of new statistical QoS constraints for delay and error-rate is still in its infancy. In an effort to address these challenges, we put forth the formulation and solution of {\epsilon}-effective capacity problems tailored for uplink FBC-enhanced NOMA systems, specifically catering to ensure statistical delay and error-rate bounded QoS requirements. In particular, we establish uplink two-user FBC-enhanced NOMA system models by applying the hybrid successive interference cancellation (SIC). We also develop the concept of the {\epsilon}-effective capacity and propose the optimal power allocation policies to maximize the {\epsilon}-effective capacity and {\epsilon}-effective energy efficiency while upper-bounding both delay and error-rate. We conduct a set of simulations to validate and evaluate our developed optimization schemes over FBC-enhanced NOMA systems.