Resource Allocation Design for Next-Generation Multiple Access: A Tutorial Overview

TL;DR

The paper provides a comprehensive tutorial on resource allocation design for Next-Generation Multiple Access (NGMA) across three channel families: natural, reconfigurable, and functional. It establishes unified NGMA models, surveys representative schemes (e.g., OFDMA, NOMA, RSMA, DDMA) and channel-reconfiguration techniques (UAV, IRS, M/FA), and delineates rate-, power-, and reliability-oriented optimization problems. A broad toolkit of optimization methods is presented, from global approaches (SDR, BnB, MO) to low-complexity schemes (SCA, BCD), along with simulation insights and practical considerations for robustness and complexity. The article also outlines future directions, including task-oriented resource allocation, machine learning-enabled designs, and distributed optimization, to guide researchers in advancing NGMA. Overall, the work provides a structured framework and concrete problem formulations to enable efficient and robust resource allocation in next-generation wireless networks.

Abstract

Multiple access is the cornerstone technology for each generation of wireless cellular networks and resource allocation design plays a crucial role in multiple access. In this paper, we present a comprehensive tutorial overview for junior researchers in this field, aiming to offer a foundational guide for resource allocation design in the context of next-generation multiple access (NGMA). Initially, we identify three types of channels in future wireless cellular networks over which NGMA will be implemented, namely: natural channels, reconfigurable channels, and functional channels. Natural channels are traditional uplink and downlink communication channels; reconfigurable channels are defined as channels that can be proactively reshaped via emerging platforms or techniques, such as intelligent reflecting surface (IRS), unmanned aerial vehicle (UAV), and movable/fluid antenna (M/FA); and functional channels support not only communication but also other functionalities simultaneously, with typical examples including integrated sensing and communication (ISAC) and joint computing and communication (JCAC) channels. Then, we introduce NGMA models applicable to these three types of channels that cover most of the practical communication scenarios of future wireless communications. Subsequently, we articulate the key optimization technical challenges inherent in the resource allocation design for NGMA, categorizing them into rate-oriented, power-oriented, and reliability-oriented resource allocation designs. The corresponding optimization approaches for solving the formulated resource allocation design problems are then presented. Finally, simulation results are presented and discussed to elucidate the practical implications and insights derived from resource allocation designs in NGMA.

Figures (10)

• Figure 1: Conceptual framework and sectional outline of the paper.
• Figure 2: NGMA in natural channels.
• Figure 3: NGMA in reconfigurable channels.
• Figure 4: NGMA in functional channels.
• Figure 5: Illustration of a BnB-based tree structure for solving a BIP problem involving two binary optimization variables. The solid-line arrows and dashed-line arrows denote the two cases where the optimization variable is set to $0$ and $1$, respectively. The yellow-colored and red-colored nodes denote the optimal and non-optimal solutions to the BIP problem, respectively. Here, block A denotes the root node of the search tree, and blocks B and C denote the subnodes of the search tree.