Before revision:  In this paper, we design fully distributed scheduling algorithms which are provably throughput optimal for general fading channels. When arbitrary backoff time is allowed, the proposed distributed algorithm achieves the same performance in terms of rate region and delay as that of a centralized system without requiring any message passing. For the case where backoff time is discrete, we show that our algorithm still maintains throughput-optimality and achieves good delay performance at the expense of low overhead for collision resolution .
After revision:  In this paper, we propose a learning based approach which aims to find the channel with the minimum load by measuring only limited number of channels. Our method uses Gaussian Process Regressing to accurately track the traffic load on each channel based on the previous measured load. We confirm the performance of our algorithm by using experimental data, and show that the time consumed for the load measurement can be reduced up to 46\% compared to the case where all channels are monitored .