TY - GEN
T1 - Decentralized Deep Reinforcement Learning-based Dynamic Uplink Band Selection in Enhanced Licensed-Assisted Access
AU - Tilahun, Fitsum Debebe
AU - Kang, Chung G.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - Enhanced licensed-assisted access (eLAA) is an operational mode that allows the use of unlicensed band to support long-term evolution (LTE) service via carrier aggregation technology. The extension of additional bandwidth is beneficial to meet the demands of the growing mobile traffic. In the uplink eLAA, which is prone to unexpected interference from WiFi access points, resource scheduling by the base station, and then performing listen-before-talk by the users can seriously affect the resource utilization. In this paper, we present a decentralized deep reinforcement learning (DRL)-based approach in which each user independently learns dynamic band selection strategy that maximizes its own rate. Through extensive simulations, we showed that the proposed DRL-based band selection scheme not only improves resource utilization, but also guarantee certain minimum Quality of Service (QoS).
AB - Enhanced licensed-assisted access (eLAA) is an operational mode that allows the use of unlicensed band to support long-term evolution (LTE) service via carrier aggregation technology. The extension of additional bandwidth is beneficial to meet the demands of the growing mobile traffic. In the uplink eLAA, which is prone to unexpected interference from WiFi access points, resource scheduling by the base station, and then performing listen-before-talk by the users can seriously affect the resource utilization. In this paper, we present a decentralized deep reinforcement learning (DRL)-based approach in which each user independently learns dynamic band selection strategy that maximizes its own rate. Through extensive simulations, we showed that the proposed DRL-based band selection scheme not only improves resource utilization, but also guarantee certain minimum Quality of Service (QoS).
KW - deep reinforcement learning (DRL)
KW - dynamic band selection
KW - enhanced licensed-assisted access (eLAA)
KW - long short-term memory (LSTM)
UR - http://www.scopus.com/inward/record.url?scp=85082102286&partnerID=8YFLogxK
U2 - 10.1109/ICOIN48656.2020.9016460
DO - 10.1109/ICOIN48656.2020.9016460
M3 - Conference contribution
AN - SCOPUS:85082102286
T3 - International Conference on Information Networking
SP - 477
EP - 480
BT - 34th International Conference on Information Networking, ICOIN 2020
PB - IEEE Computer Society
T2 - 34th International Conference on Information Networking, ICOIN 2020
Y2 - 7 January 2020 through 10 January 2020
ER -