semi-distributed framework where the base station helps resolve contention with feedback.

Outline
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In Section \[sec:network\_model\], we describe the network model and the opportunistic resolution problem. In Section \[sec:osa\], we briefly describe the opportunistic splitting algorithm from [@qin-berry-osa] and motivate our formulation. In Section \[sec:source\_coding\], we present contention resolution problem for opportunistic scheduling as a source coding problem. In Section \[sec:osa\_source\_coding\], we characterize OSA using a maximal probability allocation scheme and study its performance. In Section \[sec:two\_examples\], we discuss the applicability of our framework for other network scenarios and in Section \[sec:conclusion\], we conclude the paper and discuss future work.

Network Model {#sec:network_model}
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We consider the downlink wireless channel of a single cell of a cellular data network (or of a single cell WLAN in an infrastructure setup). A fixed number of users, $N$, share the slotted wireless channel over time. We assume that the channel gain between the base station and the wireless users is independent and identically distributed with a common continuous distribution $F(\cdot)$. We also assume that the users have knowledge of the common channel distribution $F(\cdot)$ and the number of users in the network, $N$.

Let $(H_{n,1}, H_{n,2}, \cdots, H_{n,N})$ represent the vector channel gain 