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We study joint end-to-end congestion control and Per-link medium access control (MAC) in ad-hoc networks. We use a network utility maximization formulation, where the goal is to find optimal end-to-end source rates at the transport layer and per-link persistence probabilities at the medium access control (MAC) layer to maximize the aggregate source utility. Under certain conditions, by applying appropriate transformations and introducing new variables, we obtain a decoupled and dual-decomposable convex formulation. We develop a novel dual-based distributed algorithm using the sub gradient method. In this algorithm, sources at the transport layer adjust their log rates to maximize their net benefits, while links at the MAC layer select transmission probabilities proportional to their conceived contribution to the system reward. The two layers are connected and coordinated by link prices.