n source and destination pairs randomly located in an area want to communicate with each other.Signals transmitted from one user to another at distance r apart are subject to a power loss of r −α as well as a random phase. We identify the scaling laws of the information theoretic capacity of the network. In the case of dense networks, where the area is fixed and the density of nodes increasing, we show that the total capacity of the network scales linearly with n. This improves on the best known achievability result of n 2/3 of [1]. In the case of extended networks, where the density of nodes is fixed and the area increasing linearly with n, we show that this capacity scales as n 2−α/2 for 2 ≤ α < 3 and √ n for α ≥ 3. The best known earlier result [2] identified the scaling law for α > 4. Thus, much better scaling than multihop can be achieved in dense networks, as well as in extended networks with low attenuation. The performance gain is achieved by intelligent node cooperation and distributed MIMO communication. The key ingredient is a hierarchical and digital architecture for nodal exchange of information for realizing the cooperation. I. INTRODUCTIONThe seminal paper by Gupta and Kumar [3] initiated the study of scaling laws in large adhoc wireless networks. Their by-now-familiar model considers n nodes randomly located in the unit disk, each of which wants to communicate to a random destination node at a rate R(n) bits/second. They ask what is the maximally achievable scaling of the total throughput T (n) = n R(n) with the system size n. They showed that classical multihop architectures with conventional single-user decoding and forwarding of packets cannot achieve a scaling better

Abstract-We derive an information-theoretic upper bound on the rate per communication pair in a large ad hoc wireless network. We show that under minimal conditions on the attenuation due to the environment and for networks with a constant density of users, this rate tends to zero as the number of users gets large.

This paper analyzes the capacity of a wireless relay network composed of a large number of nodes that operate in an amplify-and-forward mode and that divide into a fixed number of levels. The capacity computation relies on the study of products of large random matrices, whose limiting eigenvalue distribution is computed via a set of recursive equations.

We establish the high SNR diversity-multiplexing tradeoff of the fading interference channel, for a general interference level and under the assumption that transmitters and receivers are equipped with a single antenna each.

Abstract-This