# Resource Allocation in C-V2X Mode 3 Based on the Exchanged Preference Profiles
## 1 Introduction
### Related Work  
Most recent research in the design of resource allocation method in C-V2X mainly focuses on the underlay spectrum approach, in which the cellular user equipment (CUE)and the vehicular user equipment (VUE) utilize the same spectrum band at the same time, achieving a higher spectrum efficiency. In [8], the different QoS requirements for vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) links were analyzed, and the ergodic capacity of the V2I was calculated only through the large-scale fading information. Then, Ref. [8] studied the optimal power allocation for each reused CUE-VUE pair and used the Hungarian algorithm to perform the spectrum resource assignment. Ref. [9] improved the vehicle platooning communication model by considering both the V2V communication and controlling factors and designed the corresponding cooperative awareness messages (CAMs) dissemination mechanism based on the bipartite graph matching. Ref. [10] formulated the resource allocation problem in vehicular networks as a latency-minimized problem, the objective of which was to maximize the weighted sum of the latency reductions. The expected latency and packet delivery ratio performances were analyzed in [10]. Ref. [11] utilized the queuing theory and effective capacity to formulate the latency violation probability (LVP) for the V2V link and maximize the V2I links' sum ergodic capacity under the constraint of the LVP of the V2V link. Ref. [12] clustered the vehicles into coalitions to acquire the benefits of spatial reuse and studied the power allocation for vehicular uplink networks. Ref. [13] analyzed the impact of vehicles' transmitting power on the packet delivery ratio performance of mode 4 and proposed an adaptive-transmit power control algorithm to reduce interference among neighboring vehicles. Ref. [4] classified the spectrum sharing model in mode 3 into two types, i.e., overlay and underlay approaches, and formulated the resource allocation problem as the optimization problem of minimizing the number of unallowed vehicular links. To transform the nonconvex optimization problem into a convex problem, Ref. [4] applied the McCormick envelopes method to linearize the corresponding variables. In [14], the closed optimal power allocation for a single pair of a vehicle and a cellular user was derived, and the three-partite hypergraph was utilized to allocate resource blocks (RBs) for multiple CUEs and VUEs. [PERSON]. [15] proposed a location-based maximum reuse distance (MRD) scheduling method based on the allocation scheme in [16], which considered the locations of vehicles applying for RBs reuse. [PERSON]. [17] analyzed the four types of conditions that avoided the resource allocation conflicts in mode 3, which were the differentiated QoS per vehicle, precluding the intracluster subframe conflicts, guaranteeing the minimal time dispersion, and preventing the concurrent signals received by the vehicles lying at the intersection, respectively. The corresponding mathematical framework of the subchannel allocation based on the four conditions was formulated in [17]. Considering the stringent QoS reliability requirements of the vehicular applications, [PERSON]. [18] proposed a priority- and guarantee-based resource allocation method, which first guaranteed the minimum RBs for safety applications and then prioritized the emergency messages to allocate the remaining radio resources properly. [PERSON]. [19] formulated the resource allocation problem as a Stackelberg game and defined the corresponding game equilibrium concept to evaluate the allocation results. Based on the price-penalty mechanism, the selfish behaviors of vehicle pairs could be limited. [PERSON]. [20] studied resource allocation fairness and the various QoS demands among mobile device-to-device (D2D) users and established an interference graph to improve energy efficiency and guarantee the users' requirements, which was based on the graph coloring theory. [PERSON].