TY - GEN
T1 - A Game-Theoretic Perspective for Efficient Modern Random Access
AU - Hansen, Andreas Peter Juhl
AU - Münster, Jeppe Roden
AU - Villadsen, Rasmus Erik
AU - Segaard, Simon Bock
AU - Rasmussen, Søren Pilegaard
AU - Biscio, Christophe
AU - Leyva-Mayorga, Israel
PY - 2025/3/24
Y1 - 2025/3/24
N2 - Modern random access mechanisms combine packet repetitions with multi-user detection mechanisms at the receiver to maximize the throughput and reliability in massive Internet of Things (IoT) scenarios. However, optimizing the access policy, which selects the number of repetitions, is a complicated problem, and failing to do so can lead to an inefficient use of resources and, potentially, to an increased congestion. In this paper, we follow a game-theoretic approach for optimizing the access policies of selfish users in modern random access mechanisms. Our goal is to find adequate values for the rewards given after a success to achieve a Nash equilibrium (NE) that optimizes the throughput of the system while considering the cost of transmission. Our results show that a mixed strategy, where repetitions are selected according to the irregular repetition slotted ALOHA (IRSA) protocol, attains a NE that maximizes the throughput in the special case with two users. In this scenario, our method increases the throughput by 30% when compared to framed ALOHA. Furthermore, we present three methods to attain a NE with near-optimal throughput for general modern random access scenarios, which exceed the throughput of framed ALOHA by up to 34%.
AB - Modern random access mechanisms combine packet repetitions with multi-user detection mechanisms at the receiver to maximize the throughput and reliability in massive Internet of Things (IoT) scenarios. However, optimizing the access policy, which selects the number of repetitions, is a complicated problem, and failing to do so can lead to an inefficient use of resources and, potentially, to an increased congestion. In this paper, we follow a game-theoretic approach for optimizing the access policies of selfish users in modern random access mechanisms. Our goal is to find adequate values for the rewards given after a success to achieve a Nash equilibrium (NE) that optimizes the throughput of the system while considering the cost of transmission. Our results show that a mixed strategy, where repetitions are selected according to the irregular repetition slotted ALOHA (IRSA) protocol, attains a NE that maximizes the throughput in the special case with two users. In this scenario, our method increases the throughput by 30% when compared to framed ALOHA. Furthermore, we present three methods to attain a NE with near-optimal throughput for general modern random access scenarios, which exceed the throughput of framed ALOHA by up to 34%.
KW - Costs
KW - Decoding
KW - Game theory
KW - Internet of Things
KW - Internet of Things (IoT)
KW - Learning systems
KW - Multiuser detection
KW - Nash equilibrium
KW - Protocols
KW - Receivers
KW - Reliability
KW - Throughput
KW - irreg- ular repetition slotted ALOHA (IRSA);
KW - random access
KW - irregular repetition slotted ALOHA (IRSA)
UR - http://www.scopus.com/inward/record.url?scp=105006444023&partnerID=8YFLogxK
U2 - 10.1109/WCNC61545.2025.10978189
DO - 10.1109/WCNC61545.2025.10978189
M3 - Article in proceeding
SN - 979-8-3503-6837-6
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2025 IEEE Wireless Communications and Networking Conference (WCNC)
PB - IEEE (Institute of Electrical and Electronics Engineers)
T2 - 2025 IEEE Wireless Communications and Networking Conference (WCNC)
Y2 - 24 March 2025 through 27 March 2025
ER -