Distributed Sum-Rate Maximization Over Finite Rate Coordination Links Affected by Random Failures

The deployment of small cell networks is expected to yield a significant improvement of coverage and spectral efficiency, provided that radio resource management is properly handled. In particular, in view of a potential massive deployment of femto access points (FAP's), it is advisable to consider decentralized resource allocation mechanisms able to keep interference below a suitable threshold. However, purely decentralized schemes might well be spectrally inefficient. In this paper, we consider a local coordination scheme, where nearby FAP's exploit the availability of a wired backhaul (typically an x-DSL line) to exchange control data to enable a local coordination with the aim of improving spectral efficiency. Since the backhaul is prone to random (unpredictable) delay and packet drop and the exchanged data are necessarily quantized, we propose a distributed resource allocation mechanism that limits the effects of the impairments coming from a realistic backhaul model. In particular, using results from stochastic approximation theory, we propose a distributed Robbins-Monro scheme with provable convergence properties. Numerical results are provided to validate the theoretical findings. Finally, in the case where the packet drop probabilities are known (estimated), we show how to counteract the effect of failures through a proper weighting of the messages exchanged among neighbor FAP's.