New technologies such as pervasive computing, ambient environment, and communication avid applications such as multimedia streaming are expected to impact the way people live and communicate in the wireless networks of the future. The introduction of these new technologies and applications is, however, a challenging task in wireless networks because of their high bandwidth requirements and Quality of Service (QoS) demands. A significant recent advance in wireless communication technology, known as Multiple-Input Multiple-Output (MIMO) provides unprecedented increase in link capacity, link reliability and network capacity. The main features of MIMO communication are spatial multiplexing, point-to-multipoint and multipoint-to-point transmission as well as interference suppression in contrast to the conventional single antenna (Single-In Single-Output, SISO) networks. In this thesis, we investigate the problem of scheduling flows for fair stream allocation (or, stream scheduling) in ad hoc networks utilizing MIMO antenna technology. Our main contributions include: i) the concept of stream allocation to flowsbased on their traffic demands or class, ii) stream allocation to flows in the network utilizing single user or multiuser MIMO communication, iii) achieving the proportional fairness of the stream allocation in the minimum possible schedule length, and iv)performance comparison of the stream scheduling in the network for single user and multiuser communication and the tradeoff involved therein. We first formulate demand based fair stream allocation as an integer linear programming (ILP) problem whose solution is a schedule that is guaranteed to be contention-free. We then solve this ILP in conjunction with binary search to find a minimum length contention-free schedule that achieves the fairness goals. Performance comparison results show the benefit of multiuser MIMO links over single user links which is predominant at higher traffic workloads in the network. We also implement a greedy heuristic for stream scheduling and compare its performance with the ILP-based algorithm in terms of the fairness goals achieved in a given schedule length. OPNET-based stochastic simulation confirms the benefits of MIMO-based stream scheduling over single antenna links, as shown by our theoretical analysis.