Virtual Cooperation for Throughput Maximization in Distributed Large-Scale Wireless Networks

A distributed wireless network with K links is considered, where the links are partitioned into M clusters each operating in a subchannel with bandwidth W/M. The subchannels are assumed to be orthogonal to each other. A general shadow-fading model described by the probability of shadowing α and the average cross-link gains ≤ 1 is considered. The main goal is to find the maximum network throughput in the asymptotic regime of K → ∞, which is achieved by: (i) proposing a distributed power allocation strategy, where the objective of each user is to maximize its best estimate (based on its local information) of the average network throughput and (ii) choosing the optimum value forM. In the first part, the network throughput is defined as the average sum-rate of the network, which is shown to scale as Θ(log K). It is proved that the optimum power allocation strategy for each user for large K is a threshold-based on-off scheme. In the second part, the network throughput is defined as the guaranteed sumrate, when the outage probability approaches zero. It is demonstrated that the on-off power scheme maximizes the throughput, which scales as (W/α ) log K . Moreover, the optimum spectrum sharing for maximizing the average sum-rate and the guaranteed sum-rate is achieved atM = 1.