The aim of this work is to understand the requirements behind Quality of Service (QoS) for Multihop Wireless Networks and evaluate the performance of different such strategies. This work starts by establishing the basis for requirement of QoS and evaluates different approaches for providing QoS. Bandwidth is selected as the most important resource amongst the resources identified for ensuring QoS. The problem is modeled as an optimization problem that tries to maximize the amount of bandwidth available in the system while providing bounds over the bandwidth available over a route. Other QoS parameters are bound by hard limits and are not involved in the optimization problem. The existence of spatial reuse rules has been established through simulations for a TCP based network. This establishes that the reuse rules are independent of the MAC and network layer protocols used. This idea is used in designing the simulations for strategies that use controlled spatial reuse and give known bounds for QoS. Simulations take the network and a set of connections to generate the best possible schedule that guarantees bandwidth to individual connections and maximizes the total number of slots used in the entire system. The total number of slots used is a measure of the bandwidth in use. The set of graphs and connections is generated by a random graph and connection generator and the data set is large enough to average the results. There are two different approaches used for scheduling the connections. The first approach uses graph coloring and provides a simpler implementation in terms of network deployments. Second approach uses on-demand slot allocation. The approaches are compared for their pros and cons. The first approach uses graph coloring to allocate fixed number of slots to each link. This makes an equivalent of a wired network with fixed bandwidth over each link. This network is simpler to operate and analyze at the cost of one time expense of graph coloring. The assumption here is that the network is static or has low mobility. The on demand approach is more flexible in terms of slot assignment and is adaptable to the changing traffic patterns. The cons are that connection establishment is more expensive in terms of bandwidth required and is more complicated and difficult to analyze. The advantages include low initial network establishment cost and accommodation of mobility.

We consider optimal power allocation policies for a single server, multiuser wireless communication system. The transmission channel may experience multipath fading. We obtain very efficient, low computational complexity algorithms which minimize power and ensure stability of the data queues. We also obtain policies when the users may have mean delay constraints. If the power required is a linear function of rate then we exploit linearity and obtain linear programs with low complexity. We also provide closed-form optimal power policies when there is a hard deadline delay constraint. Later on, we also extend single hop results to multihop networks. First we consider the case, when the transmission rate is a linear function of power. We provide low complexity algorithms for joint routing, scheduling and power control which ensure stability of the queues, certain minimum rates, end-to-end hard deadlines, and/or upper bounds on the end-to-end mean delays. Further we extend these results to the multihop networks where the power is a general monotonically increasing function of rate. For our algorithms, we also provide rates of convergence to the stationary distributions for the queue length process and also approximate end-to-end mean delays. Finally, we provide computationally efficient algorithms that minimize the total power when there is a end-to-end hard deadline delay constraint.