Power control and capacity in wireless networks

In cellular wireless communication systems, uplink power control is needed to provide all mobile users with acceptable communications performance while minimizing transmit power levels. We consider a class of distributed asynchronous power control algorithms (parameterized by the performance measure) that is similar to the schemes used in IS-95 inner loop power control. Each user\u27s performance is measured at the base station and compared to a threshold; a single control bit is then sent to the user, indicating whether its power level should be increased or decreased. The performance measurements and power updates do not require synchronization. We show that under certain conditions, this class of algorithms is stable and generates a sequence of power assignments that converges to a region around the optimal power assignment. We characterize this region and show that it can be made as small as desired by choosing algorithm parameters appropriately. For an appropriate choice of algorithm parameters, we show that convergence occurs in a finite number of iterations and derive an upper bound. To illustrate our general results, we apply them to power control algorithms with fixed base station assignment, dynamic base station assignment, and macrodiversity. Finally, we give an example illustrating the algorithm\u27s robustness to power control command errors. We consider a wireless ad hoc network consisting of large number of nodes in a fixed area. Nodes can communicate directly or relay transmissions through other nodes. Each node has a relay buffer for temporarily storing other users\u27 packets before forwarding them to their destination. In the case where users are mobile, we establish a scaling law relationship that characterizes the fundamental tradeoff between throughput capacity and relay buffer size. From this relationship, it is clear that without increased relay buffer sizes, mobility does not increase the capacity of ad hoc networks. Next, we derive a scaling law relationship between delay and throughput for a static ad hoc network. Finally, we derive a formula that provides a simple way to compute achievable throughput for certain routing and scheduling schemes