The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Fredrik Brännström - One of the best experts on this subject based on the ideXlab platform.
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Adjacent Channel Interference Aware Joint Scheduling and Power Control for V2V Broadcast Communication
IEEE Transactions on Intelligent Transportation Systems, 2021Co-Authors: Anver Hisham, Erik G. Ström, Di Yuan, Fredrik BrännströmAbstract:This paper proposes scheduling and power control schemes to mitigate the impact of both co-channel Interference (CCI) and adjacent channel Interference (ACI) on direct vehicle-to-vehicle broadcast communication. The objective is to maximize the number of vehicles that can communicate with the prescribed requirement on latency and reliability. The joint scheduling and power control problem is formulated as a mixed Boolean linear programming (MBLP) problem. A column generation method is proposed to reduce the computational complexity of the joint problem. From the joint problem, we formulate a scheduling-alone problem (given a power allocation) as a Boolean linear programming (BLP) problem and a power control-alone problem (given a schedule) as an MBLP problem. The scheduling problem is numerically sensitive due to the high dynamic range of channel values and adjacent channel Interference ratio (ACIR) values. Therefore, a novel sensitivity reduction technique, which can compute a numerically stable optimal solution at the price of increased computational complexity, is proposed. Numerical results show that ACI, just as CCI, is a serious problem in direct vehicle-to-vehicle (V2V) communication due to near-far situations and hence should not be ignored, and its impact can be reduced by proper scheduling and power control.
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Scheduling and Power Control for V2V Broadcast Communications with Adjacent Channel Interference
arXiv: Signal Processing, 2017Co-Authors: Anver Hisham, Erik G. Ström, Fredrik Brännström, Li YanAbstract:This paper investigates how to mitigate the impact of adjacent channel Interference (ACI) in vehicular broadcast communication, using scheduling and power control. Our objective is to maximize the number of connected vehicles. First, we formulate the joint scheduling and power control problem as a mixed Boolean linear programming (MBLP) problem. From this problem formulation, we derive scheduling alone problem as Boolean linear programming (BLP) problem, and power control alone problem as an MBLP problem. Due to the hardness in solving joint scheduling and power control for multiple timeslots, we propose a column generation method to reduce the computational complexity. We also observe that the problem is highly numerically sensitive due to the high dynamic range of channel parameters and adjacent channel Interference ratio (ACIR) values. Therefore, we propose a novel sensitivity reduction technique, which can compute the optimal solution. Finally, we compare the results for optimal scheduling, near-optimal joint scheduling and power control schemes, and conclude that the effective scheduling and power control schemes indeed significantly improve the performance.
Anver Hisham - One of the best experts on this subject based on the ideXlab platform.
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Adjacent Channel Interference Aware Joint Scheduling and Power Control for V2V Broadcast Communication
IEEE Transactions on Intelligent Transportation Systems, 2021Co-Authors: Anver Hisham, Erik G. Ström, Di Yuan, Fredrik BrännströmAbstract:This paper proposes scheduling and power control schemes to mitigate the impact of both co-channel Interference (CCI) and adjacent channel Interference (ACI) on direct vehicle-to-vehicle broadcast communication. The objective is to maximize the number of vehicles that can communicate with the prescribed requirement on latency and reliability. The joint scheduling and power control problem is formulated as a mixed Boolean linear programming (MBLP) problem. A column generation method is proposed to reduce the computational complexity of the joint problem. From the joint problem, we formulate a scheduling-alone problem (given a power allocation) as a Boolean linear programming (BLP) problem and a power control-alone problem (given a schedule) as an MBLP problem. The scheduling problem is numerically sensitive due to the high dynamic range of channel values and adjacent channel Interference ratio (ACIR) values. Therefore, a novel sensitivity reduction technique, which can compute a numerically stable optimal solution at the price of increased computational complexity, is proposed. Numerical results show that ACI, just as CCI, is a serious problem in direct vehicle-to-vehicle (V2V) communication due to near-far situations and hence should not be ignored, and its impact can be reduced by proper scheduling and power control.
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Scheduling and Power Control for V2V Broadcast Communications with Adjacent Channel Interference
arXiv: Signal Processing, 2017Co-Authors: Anver Hisham, Erik G. Ström, Fredrik Brännström, Li YanAbstract:This paper investigates how to mitigate the impact of adjacent channel Interference (ACI) in vehicular broadcast communication, using scheduling and power control. Our objective is to maximize the number of connected vehicles. First, we formulate the joint scheduling and power control problem as a mixed Boolean linear programming (MBLP) problem. From this problem formulation, we derive scheduling alone problem as Boolean linear programming (BLP) problem, and power control alone problem as an MBLP problem. Due to the hardness in solving joint scheduling and power control for multiple timeslots, we propose a column generation method to reduce the computational complexity. We also observe that the problem is highly numerically sensitive due to the high dynamic range of channel parameters and adjacent channel Interference ratio (ACIR) values. Therefore, we propose a novel sensitivity reduction technique, which can compute the optimal solution. Finally, we compare the results for optimal scheduling, near-optimal joint scheduling and power control schemes, and conclude that the effective scheduling and power control schemes indeed significantly improve the performance.
Li Yan - One of the best experts on this subject based on the ideXlab platform.
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Scheduling and Power Control for V2V Broadcast Communications with Adjacent Channel Interference
arXiv: Signal Processing, 2017Co-Authors: Anver Hisham, Erik G. Ström, Fredrik Brännström, Li YanAbstract:This paper investigates how to mitigate the impact of adjacent channel Interference (ACI) in vehicular broadcast communication, using scheduling and power control. Our objective is to maximize the number of connected vehicles. First, we formulate the joint scheduling and power control problem as a mixed Boolean linear programming (MBLP) problem. From this problem formulation, we derive scheduling alone problem as Boolean linear programming (BLP) problem, and power control alone problem as an MBLP problem. Due to the hardness in solving joint scheduling and power control for multiple timeslots, we propose a column generation method to reduce the computational complexity. We also observe that the problem is highly numerically sensitive due to the high dynamic range of channel parameters and adjacent channel Interference ratio (ACIR) values. Therefore, we propose a novel sensitivity reduction technique, which can compute the optimal solution. Finally, we compare the results for optimal scheduling, near-optimal joint scheduling and power control schemes, and conclude that the effective scheduling and power control schemes indeed significantly improve the performance.
Erik G. Ström - One of the best experts on this subject based on the ideXlab platform.
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Adjacent Channel Interference Aware Joint Scheduling and Power Control for V2V Broadcast Communication
IEEE Transactions on Intelligent Transportation Systems, 2021Co-Authors: Anver Hisham, Erik G. Ström, Di Yuan, Fredrik BrännströmAbstract:This paper proposes scheduling and power control schemes to mitigate the impact of both co-channel Interference (CCI) and adjacent channel Interference (ACI) on direct vehicle-to-vehicle broadcast communication. The objective is to maximize the number of vehicles that can communicate with the prescribed requirement on latency and reliability. The joint scheduling and power control problem is formulated as a mixed Boolean linear programming (MBLP) problem. A column generation method is proposed to reduce the computational complexity of the joint problem. From the joint problem, we formulate a scheduling-alone problem (given a power allocation) as a Boolean linear programming (BLP) problem and a power control-alone problem (given a schedule) as an MBLP problem. The scheduling problem is numerically sensitive due to the high dynamic range of channel values and adjacent channel Interference ratio (ACIR) values. Therefore, a novel sensitivity reduction technique, which can compute a numerically stable optimal solution at the price of increased computational complexity, is proposed. Numerical results show that ACI, just as CCI, is a serious problem in direct vehicle-to-vehicle (V2V) communication due to near-far situations and hence should not be ignored, and its impact can be reduced by proper scheduling and power control.
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Scheduling and Power Control for V2V Broadcast Communications with Adjacent Channel Interference
arXiv: Signal Processing, 2017Co-Authors: Anver Hisham, Erik G. Ström, Fredrik Brännström, Li YanAbstract:This paper investigates how to mitigate the impact of adjacent channel Interference (ACI) in vehicular broadcast communication, using scheduling and power control. Our objective is to maximize the number of connected vehicles. First, we formulate the joint scheduling and power control problem as a mixed Boolean linear programming (MBLP) problem. From this problem formulation, we derive scheduling alone problem as Boolean linear programming (BLP) problem, and power control alone problem as an MBLP problem. Due to the hardness in solving joint scheduling and power control for multiple timeslots, we propose a column generation method to reduce the computational complexity. We also observe that the problem is highly numerically sensitive due to the high dynamic range of channel parameters and adjacent channel Interference ratio (ACIR) values. Therefore, we propose a novel sensitivity reduction technique, which can compute the optimal solution. Finally, we compare the results for optimal scheduling, near-optimal joint scheduling and power control schemes, and conclude that the effective scheduling and power control schemes indeed significantly improve the performance.
Jens Zander - One of the best experts on this subject based on the ideXlab platform.
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VTC Spring - A Model for Aggregate Adjacent Channel Interference in TV White Space
2011 IEEE 73rd Vehicular Technology Conference (VTC Spring), 2011Co-Authors: Evanny Obregon, Lei Shi, Javier Ferrer, Jens ZanderAbstract:The presence of white spaces and spectrum holes in the TV bands represents potential opportunities for alleviating the apparent spectrum scarcity. Opportunistic spectrum access (OSA) has been proposed for the secondary user's operation and the main concern is the harmful Interference that secondary systems could cause to the primary receivers. Existing studies have focused on establishing the limits for co-channel and adjacent channel Interference when only one adjacent channel is used by a single secondary user. This paper presents a characterization of the aggregate adjacent channel Interference (AACI) when different adjacent channels are simultaneously accessed by multiple secondary users or white space devices (WSDs). An analytical expression is proposed to approximate the limits of the tolerable AACI. Our model states that not only the Interference received in each adjacent channel should stay below the corresponding threshold for that particular channel, but also the weighted sum of the total adjacent channel Interference power should be kept below a certain threshold. Measurement campaigns show the cumulative effect of the adjacent channel Interference (ACI) when multiple WSDs access multiple adjacent channels at the same time. The proposed analytical expression for AACI closely matches the measurement results.
