  Designing optimal strategies to deploy small cell stations is crucial to meet
the quality-of-service requirements in next-generation cellular networks with
constrained deployment costs. In this paper, a general deployment framework is
proposed to jointly optimize the locations of backhaul aggregate nodes, small
base stations, machine aggregators, and multi-hop wireless backhaul links to
accommodate both human-type and machine-type communications. The goal is to
provide deployment solutions with best coverage performance under cost
constraints. The formulated problem is shown to be a multi-objective integer
programming for which it is challenging to obtain the optimal solutions. To
solve the problem, a heuristic algorithm is proposed by combining Lagrangian
relaxation, the weighted sum method, the $\epsilon$-constraint method and tabu
search to obtain both the solutions and bounds, for the objective function.
Simulation results show that the proposed framework can provide solutions with
better performance compared with conventional deployment models in scenarios
where available fiber connections are scarce. Furthermore, the gap between
obtained solutions and the lower bounds is quite tight.
