Scheduling and Power Control for V2V Broadcast Communications With Co-Channel and Adjacent Channel Interference

This paper investigates how to mitigate the impact of both the co-channel interference and the adjacent channel interference (ACI) in the vehicle-to-vehicle (V2V) broadcast communication by scheduling and power control. Our objective is to maximize the number of connected vehicles. The optimal joint...

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Bibliographic Details
Published in:IEEE access 2019, Vol.7, p.67041-67058
Main Authors: Hisham, Anver, Strom, Erik G., Brannstrom, Fredrik, Yan, Li
Format: Article
Language:English
Subjects:
ACI
ACIR
Algorithms
Boolean algebra
Cochannel interference
Control algorithms
Control theory
Heuristic
Heuristic scheduling
Integer programming
Interference
Linear programming
Mixed integer
Optimal scheduling
optimization
Power control
Safety
Schedules
Scheduling
Signal to noise ratio
SINR
Transmitters
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Summary:This paper investigates how to mitigate the impact of both the co-channel interference and the adjacent channel interference (ACI) in the vehicle-to-vehicle (V2V) broadcast communication by scheduling and power control. Our objective is to maximize the number of connected vehicles. The optimal joint scheduling and power control problem is formulated 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 problem and (b) the optimal power control problem for a fixed schedule as a mixed integer linear programming problem. The near-optimal schedules and power values are computed by solving first (a) and then (b) for smaller-size instances of the problem. To handle larger-size instances of the problem, we propose heuristic scheduling and power control algorithms with less computational complexity. The simulation results indicate that the heuristic scheduling algorithm yields significant performance improvements compared to the baseline block-interleaver scheduler and that performance is further improved by the heuristic power control algorithm. Moreover, the heuristic algorithms perform close to the optimal scheme for small instances of the problem.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2916954