  This paper considers a cooperative device-to-device (D2D) communication
system, where the D2D transmitters (DTs) act as relays to assist cellular users
(CUs) in exchange for the opportunities to use licensed spectrum. Based on the
interaction of each D2D pair and each CU, we formulate the pairing problem
between multiple cues and multiple D2D pairs as a one-to-one matching game.
Unlike most existing works, we consider a realistic scenario with incomplete
channel information. Thus, each CU lacks enough information to establish its
preference over D2D pairs. Therefore, traditional matching algorithms are not
suitable for our scenario. To this end, we convert the matching game to an
equivalent non-cooperative game, and then propose a novel learning algorithm,
which converges to a stable matching.
