TY - JOUR

T1 - Bandit-Based Power Control in Full-Duplex Cooperative Relay Networks with Strict-Sense Stationary and Non-Stationary Wireless Communication Channels

AU - Nomikos, Nikolaos

AU - Talebi, Mohammad Sadegh

AU - Charalambous, Themistoklis

AU - Wichman, Risto

N1 - Publisher Copyright: © 2020 IEEE.

PY - 2022

Y1 - 2022

N2 - Full-duplex relaying is an enabling technique of sixth generation (6G) mobile networks, promising tremendous rate and spectral efficiency gains. In order to improve the performance of full-duplex communications, power control is a viable way of avoiding excessive loop interference at the relay. Unfortunately, power control requires channel state information of source-relay, relay-destination and loop interference channels, thus resulting in increased overheads. Aiming to offer a low-complexity alternative for power control in such networks, we adopt reward-based learning in the sense of multi-armed bandits. More specifically, we present bandit-based power control, relying on acknowledgements/negative-acknowledgements observations by the relay. Our distributed algorithms avoid channel state information acquisition and exchange, and can alleviate the impact of outdated channel state information. Two cases are examined regarding the channel statistics of the wireless network, namely, strict-sense stationary and non-stationary channels. For the latter, a sliding window approach is adopted to further improve the performance. Performance evaluation highlights a performance-complexity trade-off, compared to optimal power control with full channel knowledge and significant gains over cases considering channel estimation and feedback overheads, outdated channel knowledge, no power control and random power level selection. Finally, it is shown that the sliding-window bandit-based algorithm provides improved performance in non-stationary settings by efficiently adapting to abrupt changes of the wireless channels.

AB - Full-duplex relaying is an enabling technique of sixth generation (6G) mobile networks, promising tremendous rate and spectral efficiency gains. In order to improve the performance of full-duplex communications, power control is a viable way of avoiding excessive loop interference at the relay. Unfortunately, power control requires channel state information of source-relay, relay-destination and loop interference channels, thus resulting in increased overheads. Aiming to offer a low-complexity alternative for power control in such networks, we adopt reward-based learning in the sense of multi-armed bandits. More specifically, we present bandit-based power control, relying on acknowledgements/negative-acknowledgements observations by the relay. Our distributed algorithms avoid channel state information acquisition and exchange, and can alleviate the impact of outdated channel state information. Two cases are examined regarding the channel statistics of the wireless network, namely, strict-sense stationary and non-stationary channels. For the latter, a sliding window approach is adopted to further improve the performance. Performance evaluation highlights a performance-complexity trade-off, compared to optimal power control with full channel knowledge and significant gains over cases considering channel estimation and feedback overheads, outdated channel knowledge, no power control and random power level selection. Finally, it is shown that the sliding-window bandit-based algorithm provides improved performance in non-stationary settings by efficiently adapting to abrupt changes of the wireless channels.

KW - Full-duplex relaying

KW - multi-armed bandits

KW - non-stationary wireless channels

KW - outdated CSI

KW - power control

KW - reinforcement learning

KW - sliding-window

KW - upper confidence bound policies

UR - http://www.scopus.com/inward/record.url?scp=85125746150&partnerID=8YFLogxK

U2 - 10.1109/OJCOMS.2022.3154292

DO - 10.1109/OJCOMS.2022.3154292

M3 - Journal article

AN - SCOPUS:85125746150

VL - 3

SP - 366

EP - 378

JO - IEEE Open Journal of the Communications Society

JF - IEEE Open Journal of the Communications Society

SN - 2644-125X

ER -