The problem of communication among nodes in an is considered, where radio power decay and interference are limiting factors. It has been shown previously that, with simple multi-hopping, the achievable total communication rate in such a network is at most @math . In this work, we study the benefit of node cooperation in conjunction with multi-hopping on the network capacity. We propose a multi-phase communication scheme, combining distributed MIMO transmission with multi-hop forwarding among clusters of nodes. We derive the network throughput of this communication scheme and determine the optimal cluster size. This provides a constructive lower bound on the network capacity. We first show that in a rate of @math can be achieved with transmission power scaling of @math , where @math is the signal path-loss exponent. We further extend this result to , where we show a rate of @math can be achieved with transmission power scaling of @math in a random network with unit node density. In particular, as @math approaches 2, only constant transmission power is required. Finally, we study a random network with density @math and show that a rate of @math is achieved and the required power scales as @math .
Finally, Aeron and Saligrama in @cite_9 have studied the effect of node cooperation on the capacity of wireless networks with a fixed receiver SNR at all nodes and obtained @math network throughput, through spatially separated MIMO relays which collaborate in their transmissions. However, the assumption of constant receiver SNR at all nodes implies that the transmission power needs to scale as @math . In contrast, in this work we show that with much lower power scaling, the same communication rate can be achieved by using multi-hop distributed MIMO transmissions.
@cite_9
2002649876
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-alpha as well as a random phase. We identify the scaling laws of the information-theoretic capacity of the network when nodes can relay information for each other. 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 n2 3 of Aeron and Saligrama. 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 n2-alpha 2 for 2lesalpha 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 multiple-input multiple-output (MIMO) communication. The key ingredient is a hierarchical and digital architecture for nodal exchange of information for realizing the cooperation.