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While millimeter wave (mmWave) communications promise high data rates, theirsensitivity to blockage and severe signal attenuation presents challenges intheir deployment in urban settings. To overcome these effects, we consider adistributed cooperative beamforming system, which relies on static relaysdeployed in clusters with similar channel characteristics, and where, at everytime instance, only one relay from each cluster is selected to participate inbeamforming to the destination. To meet the quality-of-service guarantees ofthe network, a key prerequisite for beamforming is relay selection. However, asthe channels change with time, relay selection becomes a resource demandingtask. Indeed, estimation of channel state information for all candidate relays,essential for relay selection, is a process that takes up bandwidth, wastespower and introduces latency and interference in the network. We insteadpropose a unique, predictive scheme for resource efficient relay selection,which exploits the special propagation patterns of the mmWave medium, and canbe executed distributively across clusters, and in parallel to optimalbeamforming-based communication. The proposed predictive scheme efficientlyexploits spatiotemporal channel correlations with current and past networkwideReceived Signal Strength (RSS), the latter being invariant to relay clustersize, measured sequentially during the operation of the system. Our numericalresults confirm that our proposed relay selection strategy outperforms anyrandomized selection policy that does not exploit channel correlations,whereas, at the same time, it performs very close to an ideal scheme that usescomplete, cluster size dependent RSS, and offers significant savings in termsof channel estimation overhead, providing substantially better networkutilization, especially in dense topologies, typical in mmWave networks.

Cooperative Beamforming with Predictive Relay Selection for Urban mmWave Communications