414 research outputs found

    Adjacent Channel Interference Aware Joint Scheduling and Power Control for V2V Broadcast Communication

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    IEEE 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

    Radio resource management for V2V multihop communication considering adjacent channel interference

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    This paper investigates schemes for multihop scheduling and power control for vehicle-to-vehicle (V2V) multicast communication, taking into account the effects of both co-channel interference and adjacent channel interference, such that requirements on latency or age of information (AoI) are satisfied. Optimal performance can be achieved by formulating and solving mixed Boolean linear programming (MBLP) optimization problems for various performance metrics, including network throughput and connectivity. Fairness among network nodes (vehicles) is addressed by considering formulations that maximizes the worst-case network node performance. Solving the optimization problem comes at the cost of significant computational complexity for large networks and requires that (slow) channel state information is gathered at a central point. To address these issues, a clustering method is proposed to partition the optimization problem into a set of smaller problems, which reduces the overall computational complexity, and a decentralized algorithm that does not need channel state information is provided

    Evaluation of Interference-Cancellation Based MAC Protocols for Vehicular Communications

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    Vehicular communications form an important part of future intelligent transport systems. Wireless connectivity between vehicles can enhance safety in vehicular networks and enable new services such as adaptive traffic control, collision detection and avoidance. As several new algorithms are being developed for enhancing vehicle to vehicle wireless connectivity, it is important to validate the performance of these algorithms using reasonably accurate wireless channel models. Specifically, some recent developments in the medium access control (MAC) layer algorithms appear to have the potential to improve the performance of vehicle to vehicle communications; however, these algorithms have not been validated with realistic channel models encountered in vehicular communications. The aforementioned issues are addressed in this thesis and correspondingly, there are two main contributions - (i) A complete IEEE 802.11p based transceiver model has been simulated in MATLAB and its performance & reliability are tested using existing empirically-developed wireless channel models. (ii) A new MAC layer algorithm based on slotted ALOHA with successive interference cancellation(SIC) has been evaluated and tested by taking into consideration the performance of underlying physical layer. The performance of slotted ALOHA-SIC and the already existing carrier sense multiple access with collision avoidance (CSMA/CA) scheme with respect to channel access delay and average packet loss ratio is also studied

    Implementation and Performance Evaluation of Distributed Autonomous Multi-Hop Vehicle-to-Vehicle Communications over TV White Space

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    This paper presents design and experimental evaluation of a distributed autonomous multi-hop vehicle-to-vehicle (V2V) communication system over TV white space performed in Japan. We propose the two-layer control channel model, which consists of the Zone Aware Control Channel (ZACC) and the Swarm Aware Control Channel (SACC), to establish the multi-hop network. Several vehicles construct a swarm using location information shared through ZACC, and share route and channel information, and available white space information through SACC. To evaluate the system we carried out field experiments with swarm made of three vehicles in a convoy. The vehicles observe channel occupancy via energy detection and agree on the control and the data channels autonomously. For coarse synchronization of quiet periods for sensing we use GPS driven oscillators, and introduce a time margin to accommodate for remaining drift. When a primary user is detected in any of the borrowed channels, the vehicles switch to a vacant channel without disrupting the ongoing multi-hop communication. We present the experimental results in terms of the time to establish control channel, channel switching time, delivery ratio of control message exchange, and throughput. As a result, we showed that our implementation can provide efficient and stable multi-hop V2V communication by using dynamic spectrum access (DSA) techniques
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