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This paper studies the scalability of a wireless backhaul network modeled asa random extended network with multi-antenna base stations (BSs), where thenumber of antennas per BS is allowed to scale as a function of the networksize. The antenna scaling is justified by the current trend towards the use ofhigher carrier frequencies, which allows to pack large number of antennas insmall form factors. The main goal is to study the per-BS antenna requirementthat ensures scalability of this network, i.e., its ability to delivernon-vanishing rate to each source-destination pair. We first derive aninformation theoretic upper bound on the capacity of this network under ageneral propagation model, which provides a lower bound on the per-BS antennarequirement. Then, we characterize the scalability requirements for twocompeting strategies of interest: (i) long hop: each source-destination pairminimizes the number of hops by sacrificing multiplexing gain while achievingfull beamforming (power) gain over each hop, and (ii) short hop: eachsource-destination pair communicates through a series of short hops, eachachieving full multiplexing gain. While long hop may seem more intuitive in thecontext of massive multiple-input multiple-output (MIMO) transmission, we showthat the short hop strategy is significantly more efficient in terms of per-BSantenna requirement for throughput scalability. As a part of the proof, weconstruct a scalable short hop strategy and show that it does not violate anyfundamental limits on the spatial degrees of freedom (DoFs).

Wireless Backhaul Networks: Capacity Bound, Scalability Analysis and Design Guidelines