Per User Throughput in Large Wireless Networks

Previous results show that a node's throughput scales poorly as the network size increases when every node has traffic. However, in many cases, only a fraction of nodes in large networks have data to send or receive at any given time, while other nodes can act as relays/routers. Therefore, in this paper, we study the scaling behavior from a user's viewpoint (a user is a node with traffic). We first derive an upper bound on per user throughput. To derive the lower bound, we propose a simple scheduling scheme that enables users to cooperate with relay nodes and fully utilize the networks capacity. We show that per user throughput depends on the network size, the number of users, and the node deployment schemes, and is in general much more optimistic. Our scheme also sheds light on designing efficient cooperation protocols in heterogeneous networks and cognitive radio networks.