User association and the alignment-throughput tradeoff in millimeter wave networks

Millimeter wave (mmWave) communication is a promising candidate for future extremely high data rate, wireless networks. The main challenges of mmWave communications are deafness (misalignment between the beams of the transmitter and receiver) and blockage (severe attenuation due to obstacles). Due to deafness, prior to link establishment between a client and its access point, a time consuming alignment/beam training procedure is necessary, whose complexity depends on the operating beamwidth. Addressing blockage may require a reassociation to non-blocked access points, which in turn imposes additional alignment overhead. This paper introduces a unifying framework to maximize network throughput considering both deafness and blockage. A distributed auction-based solution is proposed, where the clients and access points act asynchronously to achieve optimal association along with the optimal operating beamwidth. It is shown that the proposed algorithm provably converges to a solution that maximizes the aggregate network utility within a desired bound. Convergence time and performance bounds are derived in closed-forms. Numerical results confirm superior throughput performance of the proposed solution compared to existing approaches, and highlight the existence of a tradeoff between alignment overhead and achievable throughput that affects the optimal association.