Opportunistic Splitting Algorithms for Wireless Networks with Fairness Constraints

In wireless networks, it is well established that the throughput can be increased by opportunistically scheduling transmissions to users that have good channel conditions. Several “opportunistic” medium access control protocols have been developed, which enable distributed users to opportunistically transmit without requiring a centralized scheduler. In this paper, we consider opportunistic splitting algorithms, where a sequence of mini-slots is used to determine the appropriate user to schedule at each time. In prior work, this type of algorithm has been developed for homogeneous systems in which all users have independent and identically distributed (i.i.d.) channel statistics. Here, we specify new splitting algorithms for a heterogeneous environment that may also include fairness constraints. The performance of the splitting algorithms are characterized via analysis and simulations. In particular, we show that in certain cases, a heterogeneous algorithm will perform at least as well as the homogeneous algorithm in a system with the same total number of users.