MEC-enabled Edge Network Deployment with Converged Fiber and Millimeter-Wave Communications

Mobile edge computing (MEC) and millimeter-wave (mmWave) communication are promising techniques for future cellular networks. MEC enables latency-critical tasks offloading at the network edge, while mmWave provides an abundant spectrum for gigabit-per-second data transmission. Dense deployment of remote radio units (RRUs) is necessary due to high mmWave signal path loss, and hence limiting the deployment cost becomes a prime network design factor. Our work considers that RRUs are deployed to provide mmWave access and to offload computation requests to edge servers (ESs) via fronthaul links. We propose an edge network (EN) deployment problem by jointly optimizing the mmWave access and fronthaul networks. Converged fiber and in-band mmWave techniques are utilized for flexible fronthaul links deployment and cost reduction. The deployed EN is expected to fulfill coverage, reliability and latency requirements of ultra-reliable low-latency (uRLLC) services. We formulate the optimization problem as an integer linear program (ILP) and propose a multi-objective evolutionary algorithm to solve the problem. The numerical results demonstrate that our proposed algorithm can achieve close-to-optimal solutions compared with the ILP formulation. We also comparatively evaluate the deployment costs under different EN settings and show that our algorithm provides up to 20.3% cost savings compared to non-converged solutions.