  This paper addresses cooperative link scheduling problems for base station
(BS) aided device-to-device (D2D) communications using limited channel state
information (CSI) at BS. We first derive the analytical form of ergodic
sum-spectral efficiency as a function of network parameters, assuming
statistical CSI at the BS. However, the optimal link scheduling, which
maximizes the ergodic sum-spectral efficiency, becomes computationally
infeasible when network density increases. To overcome this challenge, we
present a low-complexity link scheduling algorithm that divides the D2D network
into sub-networks and identifies the optimal link scheduling strategy per
sub-network. Furthermore, we consider the scenario when the statistical CSI is
not available to the BS. In such cases, we propose a quasi-optimal scalable
link scheduling algorithm that utilizes one-bit feedback information from D2D
receivers. The algorithm clusters the links and applies the UCB algorithm per
cluster using the collected one-bit feedback information. We highlight that
even with reduced scheduling complexity, the proposed algorithm identifies a
link scheduling action that ensures optimality within a constant throughput
gap. We also demonstrate through simulations that the proposed algorithm
achieves higher sum-spectral efficiency than the existing link scheduling
algorithms, even without explicit CSI or network parameters knowledge.
