  To provide Uplink Centric Broadband Communication (UCBC), New Radio
Unlicensed (NR-U) network has been standardized to exploit the unlicensed
spectrum using Listen Before Talk (LBT) scheme to fairly coexist with the
incumbent Wireless Fidelity (WiFi) network. Existing access schemes over
unlicensed spectrum are required to perform Clear Channel Assessment (CCA)
before transmissions, where fixed Energy Detection (ED) thresholds are adopted
to identify the channel as idle or busy. However, fixed ED thresholds setting
prevents devices from accessing the channel effectively and efficiently, which
leads to the hidden node (HN) and exposed node (EN) problems. In this paper, we
first develop a centralized double Deep Q-Network (DDQN) algorithm to optimize
the uplink system throughput, where the agent is deployed at the central server
to dynamically adjust the ED thresholds for NR-U and WiFi networks. Considering
that heterogeneous NR-U and WiFi networks, in practice, cannot share the raw
data with the central server directly, we then develop a federated DDQN
algorithm, where two agents are deployed in the NR-U and WiFi networks,
respectively. Our results have shown that the uplink system throughput
increases by over 100%, where cell throughput of NR-U network rises by 150%,
and cell throughput of WiFi network decreases by 30%. To guarantee the cell
throughput of WiFi network, we redesign the reward function to punish the agent
when the cell throughput of WiFi network is below the threshold, and our
revised design can still provide over 50% uplink system throughput gain.
