On Adjacent Channel Interference-Aware Radio Resource Management for Vehicle-to-Vehicle Communication
Doctoral thesis, 2019

Safety applications play an essential role in supporting traffic safety and efficiency in next generation vehicular networks. Typical safety applications require vehicle-to-vehicle (V2V) communication with high reliability and low latency. The reliability of a communication link is mainly determined by the received interference, and broadly speaking, there are two types of interferences: co-channel interference (CCI) and adjacent channel interference (ACI). The CCI is cross-talk between transmitters scheduled in the same time-frequency slot, whereas ACI is interference due to leakage of transmit power outside the intended frequency slot. The ACI is typically not a problem in cellular communication since interference is dominated by CCI due to spectrum re-usage. However, ACI is a significant problem in near-far situations, i.e., when the channel gain from the interferer to receiver is high compared to the channel gain from the intended transmitter. The near-far situation is more common in V2V broadcast communication scenario due to high dynamic range of the channel gain and penetration loss by intermediate vehicles. This thesis investigates the impact of ACI on V2V communication and methods to mitigate it by proper radio resource management (RRM), i.e., scheduling and power control.

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.


adjacent channel interference (ACI)

vehicle-to- vehicle (V2V)

channel state information (CSI)

convex optimization


vehicle-to-everything (V2X)

combinatorial optimization

traffic efficiency


medium access control (MAC)

power control

radio resource management (RRM)

Room ED, EDIT building
Opponent: Prof. Slawomir Stanczak, Department of Wireless Communications and Networks, Technical University of Berlin, Germany


Anver Hisham Unnichiriyath Siddique

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Traffic-related accidents can be largely reduced with new driverless and connected vehicle technology, since new technologies will remove the human element that is causing most of the traffic accidents. Driverless and connected vehicles can also reduce the traffic congestion since multiple vehicles can move together as a unit, communicate with traffic lights, reduce unnecessary accelerating and braking. This would also help to reduce fuel consumption and emissions significantly.

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


Computational Mathematics

Communication Systems


C3SE (Chalmers Centre for Computational Science and Engineering)



Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4627


Chalmers University of Technology

Room ED, EDIT building

Opponent: Prof. Slawomir Stanczak, Department of Wireless Communications and Networks, Technical University of Berlin, Germany

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