The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Konstantinos Psounis - One of the best experts on this subject based on the ideXlab platform.
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equal interference power allocation for efficient shared Spectrum Resource scheduling
IEEE Transactions on Wireless Communications, 2017Co-Authors: Matthew Clark, Konstantinos PsounisAbstract:Effective radio frequency Spectrum sharing methods are crucial for sustaining growth and development in mobile wireless services. In this paper, we consider a real-world scenario involving Spectrum sharing between mobile wireless and meteorological satellite services as motivation for examining the general problem of efficient Resource scheduling in a shared Spectrum environment. We formulate an optimization framework for maximizing network utility subject to stochastic interference protection constraints. We design and propose a novel solution inspired by analysis of the optimization problem, where the primary contribution is an efficient power allocation algorithm to manage interference between systems. Using theory and simulations, we show that our algorithm significantly outperforms alternative approaches by well approximating the optimal solution with low enough complexity for practical, real-time application to large networks.
Matthew Clark - One of the best experts on this subject based on the ideXlab platform.
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equal interference power allocation for efficient shared Spectrum Resource scheduling
IEEE Transactions on Wireless Communications, 2017Co-Authors: Matthew Clark, Konstantinos PsounisAbstract:Effective radio frequency Spectrum sharing methods are crucial for sustaining growth and development in mobile wireless services. In this paper, we consider a real-world scenario involving Spectrum sharing between mobile wireless and meteorological satellite services as motivation for examining the general problem of efficient Resource scheduling in a shared Spectrum environment. We formulate an optimization framework for maximizing network utility subject to stochastic interference protection constraints. We design and propose a novel solution inspired by analysis of the optimization problem, where the primary contribution is an efficient power allocation algorithm to manage interference between systems. Using theory and simulations, we show that our algorithm significantly outperforms alternative approaches by well approximating the optimal solution with low enough complexity for practical, real-time application to large networks.
Keqin Li - One of the best experts on this subject based on the ideXlab platform.
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Spectrum Resource sharing in heterogeneous vehicular networks a noncooperative game theoretic approach with correlated equilibrium
IEEE Transactions on Vehicular Technology, 2018Co-Authors: Zhu Xiao, Xiangyu Shen, Fanzi Zeng, Vincent Havyarimana, Dong Wang, Weiwei Chen, Keqin LiAbstract:In this paper, with the aims of alleviating the pressure from the shortage of Spectrum Resource and addressing the inefficient Spectrum utilization, we investigate the Spectrum sharing for moving vehicles in Heterogeneous Vehicular Networks (HVNs) consisting of the macrocells and the Road Side Units (RSUs) with Cognitive Radio (CR) technology. We first propose an incentive mechanism for encouraging macrocells to share Spectrum Resource with vehicle users, in which the CR-enabled RSUs perform sensing the Spectrum availability in the surrounding urban environments. Furthermore, the downlink Resource allocation for vehicle users associated with different RSUs is modeled as an $n$ -person game and solved by designing a noncooperative game theoretic approach. By considering transmission power constraint of RSU and inter-RSU interference, the Resource allocation and interference mitigation among RSUs are formulated via maximizing the overall utility in the HVNs. We design a game theoretical strategy optimization algorithm based on regret-matching and then derive the correlated equilibrium solution. Moreover, we propose a heuristic power control algorithm for further mitigating the inter-RSU interference in the noncooperative game based Resource allocation. Simulation results demonstrate that the proposed approach can achieve the correlated equilibrium with fast convergence and significantly improve the system performance in high mobility HVNs.
Ying-chang Liang - One of the best experts on this subject based on the ideXlab platform.
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Efficient Spectrum Utilization on TV Band for Cognitive Radio Based High Speed Vehicle Network
IEEE Transactions on Wireless Communications, 2014Co-Authors: Tao Jiang, Zhiqiang Wang, Lei Zhang, Daiming Qu, Ying-chang LiangAbstract:It is well known that broadband wireless communications (BWC) are necessary for high speed vehicles since passengers need many broadband wireless multimedia services. However, one design challenge is to identify sufficient Spectrum Resource to support BWC in high speed vehicles. Recently, cognitive radios (CRs) are being considered as a promising technology to solve scarcity problem of Spectrum Resource. Therefore, we investigate the Spectrum Resource allocation problem in the CR based high speed vehicle network (CR-HSVN) in this paper. Specifically, we propose a Spectrum Resource allocation framework, where high speed vehicles could effectively utilize the TV white spaces. Subsequently, we formulate the allocation of Spectrum Resource as an optimization problem to maximize the available Spectrum Resources (i.e., TV white spaces) utilized by the CR-HSVN, and investigate the property of the CR-HSVN to reduce the complexity by separation computing method without loss of optimality. Furthermore, we analyze the optimal solution based on branch and bound method, the suboptimal solutions based on single channel and linear programming, respectively. Simulation results show that the proposed framework could offer excellent performances of the Spectrum utilization and fairness for the CR-HSVN. Meanwhile, the aggregated interference from vehicles to primary users is constrained.
Sabrine Aroua - One of the best experts on this subject based on the ideXlab platform.
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Spectrum Resource assignment in cognitive radio sensor networks for smart grids
2018Co-Authors: Sabrine ArouaAbstract:With the advances in wireless communication technologies, cognitive radio sensor networks (CRSNs) stand as an efficient Spectrum solution in the development of intelligent electrical power networks, the smart grids. The cognitive radio (CR) technology provides the sensors with the ability to use the temporally available licensed Spectrum in order to escape the unlicensed Spectrum Resource scarcity problem. In this context, several challenging communication issues face the CRSN deployment for smart grids such as the coexistence of different electrical applications and the heterogeneous opportunities to access available licensed channels between smart grid sensors. The work conducted in this thesis focuses on Spectrum Resource allocations for CRSNs in smart grids. We concentrate our efforts on the development of new Spectrum Resource sharing paradigms for CRSNs in smart grids. The developed solutions focus on distributed and balanced Spectrum sharing among smart grid sensors and on eventual CRSN deployment scenarios in smart grid areas. All along the thesis, channels are assigned without relying on a predefined common control channel (CCC) to exchange control messages before each Spectrum access trial. All along the thesis, channels are assigned without relying on a predefined common control channel (CCC) to exchange control messages before each Spectrum access trial. Performance evaluation of the different proposed channel assignment solutions shows their ability to achieve a distributed and fair opportunistic Spectrum assignment in a way to consider different smart grid system characteristics.
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ISCC - A distributed Cooperative Spectrum Resource Allocation in smart home cognitive wireless sensor networks
2017 IEEE Symposium on Computers and Communications (ISCC), 2017Co-Authors: Sabrine Aroua, Ines El Korbi, Yacine Ghamri-doudane, Leila Azouz SaidaneAbstract:Wireless sensor networks (WSNs) are considered as a crucial technology that will definitely ensure a permanent growth to emergent applications as smart homes, smart grids, etc. In the particular home area network (HAN) context, sensor nodes will be in charge of the power monitoring between the smart home appliances. But, the communications in WSNs generally relay on the ISM bands, characterized by a narrow bandwidth and a high collision/interference ratio. Hence, the cognitive radio technology can be used to overcome the Spectrum Resource scarcity in WSNs. In cognitive radio networks, the sensor nodes will opportunistically access licensed channels if they are vacant of primary signals, thus ensuring a better exploitation of the available radio Resources. Generally, a common control channel (CCC) is used to exchange control messages in the cognitive network. But, relying on a CCC is not always feasible especially if the number of contenders in the network is important or if the sensors do not share the same Spectrum Resources. Therefore, we propose in this paper a new framework for the by-domestic energy control in smart homes using cognitive radio sensor networks (CRSNs). Our proposed framework, called Cooperative Spectrum Resource Allocation (CSRA), aims to completely avoid the CCC and to achieve a distributed fair Spectrum Resource sharing among the sensors in smart homes. The fairness of CSRA is ensured through partially observable Markov decision process (POMDP) that performs the channel assignment, to each node, based on local Spectrum utilization estimates. Performance evaluation, using the OMNeT++ simulator, reveals that the proposed CSRA approach achieves a fair Spectrum allocation between sensor nodes in smart home systems.
