On Power Control and Scheduling to Mitigate Adjacent Channel Interference in Vehicle-to-Vehicle Communication
Safety applications play an essential role in supporting traffic safety and efficiency in next generation vehicular networks. The efficiency of safety applications depends heavily on the establishment of reliable communication since these types of applications have strict requirements on latency and reliability. Recently, vehicle-to-vehicle (V2V) communication have captured great attention due to its potential to improve traffic safety, effective driving assistance, and intelligent transport systems. Typically cellular communication performance is limited by co-channel interference (CCI). However, in the case of V2V broadcast communication with sufficient amounts of dedicated spectrum, we can avoid CCI by allocating non-overlapping frequency resources to vehicular user equipments (VUEs). However, in this scenario, adjacent channel interference (ACI) becomes a deciding factor for the communication performance. This thesis investigates how to mitigate the impact of ACI on V2V broadcast communication by scheduling and power control.
In Paper A, we study the impact of ACI on V2V communications and conclude that the ACI indeed significantly affects the reliability of V2V links. Second, we formulate a power control optimization problem for vehicles to reduce the negative influence of ACI, which is shown to be NP-hard. Furthermore, we propose two power control schemes where the first one solves the formulated problem by a branch and bound method and the second one considers a heuristic algorithm with much reduced complexity. Numerical results show the necessity of power control when ACI exists and also show promising performance of the proposed algorithms.
In Paper B, we formulate the joint scheduling and power control problem, with the objective to maximize the number of connected vehicles, as a mixed integer programming problem with a linear objective and a quadratic constraint. From the joint formulation, we derive (a) the optimal scheduling problem for fixed transmit powers as a Boolean linear programming (BLP) problem and (b) the optimal power control problem for a fixed schedule as a mixed integer linear programming (MILP) problem. Near-optimal schedules and power values for smaller instances of the problem can be computed by solving first (a) and then (b). To handle larger instances of the problem, we propose heuristic scheduling and power control algorithms with reduced computational complexity. We provide exhaustive simulation results in Paper C appended in this thesis for various duplex scenarios and ACI models. As a baseline result, we also show the optimum performance that can be achieved by a block interleaver scheduler (BIS). We observe that significant performance improvement can be achieved using the proposed heuristic algorithms compared to BIS. Moreover, the heuristic algorithms perform close to the near-optimal scheme for small instances of the problem.