On Adjacent Channel Interference-Aware Radio Resource Management for Vehicle-to-Vehicle Communication
Doctoral thesis, 2019
In [Paper A], we first study ACI models for various transmission schemes and its impact on V2V communication. We propose a problem formulation for a) optimal scheduling as a Boolean linear programming (BLP) problem and b) optimal power control as a mixed Boolean linear programming (MBLP) problem. The objective of the problem formulation is to maximize the connectivity among VUEs in the network. 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, heuristic scheduling and power control algorithms with less computational complexity are proposed. We also propose a simple distributed block interleaver scheduler (BIS), which can be used as a baseline method.
In [Paper B], we formulate the joint scheduling and power control problem as an MBLP to maximize the connectivity among VUEs. A column generation method is proposed to address the scalability of the network, i.e., to reduce the computational complexity of the joint problem. Moreover, the scheduling problem is observed to be numerically sensitive due to the high dynamic range of channel values and adjacent channel interference ratio (ACIR) values. Therefore, a novel method is proposed to reduce the sensitivity and compute a numerically stable optimal solution at the price of increased computational complexity.
In [Paper C], we extend the RRM problem formulation to include various objectives, such as maximizing connectivity/throughput and minimizing age of information (AoI). In order to account for the fairness, we also formulate the problem to improve the worst-case throughput, connectivity, and AoI of a link in the network. All the problems are formulated as MBLP problems. In order to support a large V2V network, a clustering algorithm is proposed whose computational complexity scale well with the network size. Moreover, a multihop distributed scheduling scheme is proposed to handle zero channel state information (CSI) case.
scheduling
adjacent channel interference (ACI)
vehicle-to- vehicle (V2V)
channel state information (CSI)
convex optimization
LTE
vehicle-to-everything (V2X)
combinatorial optimization
traffic efficiency
3GPP
medium access control (MAC)
power control
radio resource management (RRM)
Author
Anver Hisham Unnichiriyath Siddique
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Reliable wireless communication between vehicles is crucial in sharing information and enabling connected cars. But, unfortunately, wireless communication between vehicles is not perfect. In fact, when information is exchanged between vehicles, the data packets can be lost or delayed due to interference coming from other transmitting vehicles.
This thesis investigates the limitations of vehicle-to-vehicle communication due to interference and discusses a few strategies to overcome those limitations. The goal of the thesis is to establish reliable wireless communication links between vehicles. A technical abstract of this thesis can be found on page i.
Areas of Advance
Information and Communication Technology
Subject Categories
Telecommunications
Computational Mathematics
Communication Systems
Infrastructure
C3SE (Chalmers Centre for Computational Science and Engineering)
ISBN
978-91-7905-160-0
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4627
Publisher
Chalmers
Room ED, EDIT building
Opponent: Prof. Slawomir Stanczak, Department of Wireless Communications and Networks, Technical University of Berlin, Germany