On the Throughput Maximization in Dencentralized Wireless Networks

A distributed single-hop wireless network with $K$ links is considered, where the links are partitioned into a fixed number ($M$) of clusters each operating in a subchannel with bandwidth $\frac{W}{M}$. The subchannels are assumed to be orthogonal to each other. A general shadow-fading model, described by parameters $(\alpha,\varpi)$, is considered where $\alpha$ denotes the probability of shadowing and $\varpi$ ($\varpi \leq 1$) represents the average cross-link gains. The main goal of this paper is to find the maximum network throughput in the asymptotic regime of $K \to \infty$, which is achieved by: i) proposing a distributed and non-iterative power allocation strategy, where the objective of each user is to maximize its best estimate (based on its local information, i.e., direct channel gain) of the average network throughput, and ii) choosing the optimum value for $M$. In the first part of the paper, the network hroughput is defined as the \textit{average sum-rate} of the network, which is shown to scale as $\Theta (\log K)$. Moreover, it is proved that in the strong interference scenario, the optimum power allocation strategy for each user is a threshold-based on-off scheme. In the second part, the network throughput is defined as the \textit{guaranteed sum-rate}, when the outage probability approaches zero. In this scenario, it is demonstrated that the on-off power allocation scheme maximizes the throughput, which scales as $\frac{W}{\alpha \varpi} \log K$. Moreover, the optimum spectrum sharing for maximizing the average sum-rate and the guaranteed sum-rate is achieved at M=1.Comment: Submitted to IEEE Transactions on Information Theor

A new decentralized power allocation strategy in single-hop wireless networks

In this paper, a simple decentralized power allocation strategy is proposed, which relies on the local information in a single-hop wireless network with n links. The main goal of the strategy is to improve the average sum-rate. We first define a new utility-based framework, in which each user takes into account the negative impact of its power increment on the other users performance. For large n and by knowing only the direct channel gain hii, the optimum strategy for user i is to transmit with full power or remain silent. The transmission policy is to compare hii with a prespecified threshold τn that is a function of n. Under a Rayleigh fading channel condition, it is demonstrated that among n pairs of nodes, the average number of active links is of order log n. Also, the average sum-rate scales as Θ(log n). The performance of the proposed strategy is compared with that of the centralized power allocation scheme and the non-cooperative power control games through simulation and the analytical arguments. The proposed on-off power allocation scheme has the advantage of not requiring a central controller. The proposed strategy relies on a one shot game with a simple structure, rather than the iterative mechanism used in the pricing algorithm. These properties make our scheme more practical in time-varying networks