  In this paper, a dynamic spectrum management framework is proposed to improve
spectrum resource utilization in a multi-access edge computing (MEC) in
autonomous vehicular network (AVNET). To support the increasing data traffic
and guarantee quality-of-service (QoS), spectrum slicing, spectrum allocating,
and transmit power controlling are jointly considered. Accordingly, three
non-convex network utility maximization problems are formulated to slice
spectrum among BSs, allocate spectrum among autonomous vehicles (AVs)
associated with a BS, and control transmit powers of BSs, respectively. Via
linear programming relaxation and first-order Taylor series approximation,
these problems are transformed into tractable forms and then are jointly solved
through an alternate concave search (ACS) algorithm. As a result, optimal
spectrum slicing ratios among BSs, optimal BS-vehicle association patterns,
optimal fractions of spectrum resources allocated to AVs, and optimal transmit
powers of BSs are obtained. Based on our simulation, a high aggregate network
utility is achieved by the proposed spectrum management scheme compared with
two existing schemes.
