The Experts below are selected from a list of 87375 Experts worldwide ranked by ideXlab platform
Tho Lengoc - One of the best experts on this subject based on the ideXlab platform.
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distributed subchannel and Power Allocation for ofdma based femtocell networks
Vehicular Technology Conference, 2013Co-Authors: Suman Khakurel, Tho LengocAbstract:This paper proposes a distributed joint subchannel and Power Allocation algorithm for the downlink of an orthogonal frequency-division multiple access (OFDMA) mixed femtocell/macrocell network deployment. Specifically, the total throughput of all femtocell user equipments (FUEs) is maximized while the network capacity of an existing macrocell is always protected. To this end, we employ an iterative process in which subchannels and transmit Powers of base stations (BS) are alternatively assigned and optimized at every step. For a fixed Power Allocation, we prove that the optimal policy is to give each subchannel to the user with the highest data rate, or equivalently the highest signal-to-interference-plus-noise ratio (SINR), on that subchannel. For any given subchannel assignment, we apply the difference-of-concave- functions (d.c.) approach and transform the highly nonconvex program into a sequence of convex Power Allocation subproblems. We show that the developed iterative scheme converges to an optimal point. Importantly, we implement the devised solution by a decentralized algorithm, wherein each BS computes the optimal subchannel and Power Allocation for its own servicing cell. Numerical results confirm the merits of our proposed approach.
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centralized and distributed Power Allocation in multi user wireless relay networks
International Conference on Communications, 2009Co-Authors: Khoa T Phan, Sergiy A Vorobyov, Tho LengocAbstract:Optimal Power Allocation for multi-user amplify-and-forward wireless relay networks in which multiple source-destination pairs are assisted by a set of relays is investigated. Two relay Power Allocation strategies based on maximization of either i) the minimum rate among all users or ii) the weighted sum of rates are developed. A distributed implementation of the maximum weighted-sum-rate Power Allocation strategy is also studied. Numerical results demonstrate the efficiency of the proposed strategies and reveal their interesting throughput-fairness tradeoff in resource Allocation.
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Power Allocation in wireless multi user relay networks
IEEE Transactions on Wireless Communications, 2009Co-Authors: Khoa T Phan, Tho Lengoc, Sergiy A Vorobyov, Chintha TellamburaAbstract:In this paper, we consider an amplify-and-forward wireless relay system where multiple source nodes communicate with their corresponding destination nodes with the help of relay nodes. Conventionally, each relay equally distributes the available resources to its relayed sources. This approach is clearly sub-optimal since each user experiences dissimilar channel conditions, and thus, demands different amount of allocated resources to meet its quality-of-service (QoS) request. Therefore, this paper presents novel Power Allocation schemes to i) maximize the minimum signal-to-noise ratio among all users; ii) minimize the maximum transmit Power over all sources; iii) maximize the network throughput. Moreover, due to limited Power, it may be impossible to satisfy the QoS requirement for every user. Consequently, an admission control algorithm should first be carried out to maximize the number of users possibly served. Then, optimal Power Allocation is performed. Although the joint optimal admission control and Power Allocation problem is combinatorially hard, we develop an effective heuristic algorithm with significantly reduced complexity. Even though theoretically sub-optimal, it performs remarkably well. The proposed Power Allocation problems are formulated using geometric programming (GP), a well-studied class of nonlinear and nonconvex optimization. Since a GP problem is readily transformed into an equivalent convex optimization problem, optimal solution can be obtained efficiently. Numerical results demonstrate the effectiveness of our proposed approach.
H. Vicky Zhao - One of the best experts on this subject based on the ideXlab platform.
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Power Allocation in Multi-User Wireless Relay Networks through Bargaining
IEEE Transactions on Wireless Communications, 2013Co-Authors: Qian Cao, Yindi Jing, H. Vicky ZhaoAbstract:In this paper, we consider a multi-user single-relay wireless network, where the relay facilitates transmissions of the users' signals to the destination. We study the relay Power Allocation among the users, and use bargaining theory to model the negotiation among the users on relay Power Allocation. By assigning a bargaining Power to each user to indicate its transmission priority, we propose an asymmetric Nash bargaining solution (NBS)-based relay Power Allocation scheme. We also propose a distributed implementation for this solution, where each user only requires its local channel state information (CSI). We analytically investigate the impact of the bargaining Powers on the relay Power Allocation and show that via proper selection of the bargaining Powers, the proposed Power Allocation can achieve a balance between the network sum-rate and the user fairness. Then we generalize the NBS-based Power Allocation and its distributed implementation to multi-user multi-relay networks. Simulation results are shown to compare the proposed Power Allocation with sum-rate-optimal Power Allocation and even Power Allocation. The impact of the bargaining Powers on the Power Allocation is also demonstrated via simulations.
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Power Allocation and pricing in multiuser relay networks using stackelberg and bargaining games
IEEE Transactions on Vehicular Technology, 2012Co-Authors: Qian Cao, H. Vicky Zhao, Yindi JingAbstract:This paper considers a multiuser single-relay wireless network, where the relay gets paid for helping users forward signals, and the users pay to receive the relay service. We study the relay Power Allocation and pricing problems and model the interaction between the users and the relay as a two-level Stackelberg game. In this game, the relay, which is modeled as the service provider and the leader of the game, sets the relay price to maximize its revenue, whereas the users are modeled as customers and followers who buy Power from the relay for higher transmission rates. We use a bargaining game to model the negotiation among users to achieve a fair Allocation of relay Power. Based on the proposed fair relay Power Allocation rule, the optimal relay Power price that maximizes the relay revenue is derived analytically. Simulation shows that the proposed Power Allocation scheme achieves higher network sum rate and relay revenue than the even Power Allocation. Furthermore, compared with the sum-rate-optimal solution, simulation shows that the proposed scheme achieves better fairness with comparable network sum rate for a wide range of network scenarios. The proposed pricing and Power Allocation solutions are also shown to be consistent with the laws of supply and demand.
Qian Cao - One of the best experts on this subject based on the ideXlab platform.
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Power Allocation in Multi-User Wireless Relay Networks through Bargaining
IEEE Transactions on Wireless Communications, 2013Co-Authors: Qian Cao, Yindi Jing, H. Vicky ZhaoAbstract:In this paper, we consider a multi-user single-relay wireless network, where the relay facilitates transmissions of the users' signals to the destination. We study the relay Power Allocation among the users, and use bargaining theory to model the negotiation among the users on relay Power Allocation. By assigning a bargaining Power to each user to indicate its transmission priority, we propose an asymmetric Nash bargaining solution (NBS)-based relay Power Allocation scheme. We also propose a distributed implementation for this solution, where each user only requires its local channel state information (CSI). We analytically investigate the impact of the bargaining Powers on the relay Power Allocation and show that via proper selection of the bargaining Powers, the proposed Power Allocation can achieve a balance between the network sum-rate and the user fairness. Then we generalize the NBS-based Power Allocation and its distributed implementation to multi-user multi-relay networks. Simulation results are shown to compare the proposed Power Allocation with sum-rate-optimal Power Allocation and even Power Allocation. The impact of the bargaining Powers on the Power Allocation is also demonstrated via simulations.
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Power Allocation and pricing in multiuser relay networks using stackelberg and bargaining games
IEEE Transactions on Vehicular Technology, 2012Co-Authors: Qian Cao, H. Vicky Zhao, Yindi JingAbstract:This paper considers a multiuser single-relay wireless network, where the relay gets paid for helping users forward signals, and the users pay to receive the relay service. We study the relay Power Allocation and pricing problems and model the interaction between the users and the relay as a two-level Stackelberg game. In this game, the relay, which is modeled as the service provider and the leader of the game, sets the relay price to maximize its revenue, whereas the users are modeled as customers and followers who buy Power from the relay for higher transmission rates. We use a bargaining game to model the negotiation among users to achieve a fair Allocation of relay Power. Based on the proposed fair relay Power Allocation rule, the optimal relay Power price that maximizes the relay revenue is derived analytically. Simulation shows that the proposed Power Allocation scheme achieves higher network sum rate and relay revenue than the even Power Allocation. Furthermore, compared with the sum-rate-optimal solution, simulation shows that the proposed scheme achieves better fairness with comparable network sum rate for a wide range of network scenarios. The proposed pricing and Power Allocation solutions are also shown to be consistent with the laws of supply and demand.
Khoa T Phan - One of the best experts on this subject based on the ideXlab platform.
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centralized and distributed Power Allocation in multi user wireless relay networks
International Conference on Communications, 2009Co-Authors: Khoa T Phan, Sergiy A Vorobyov, Tho LengocAbstract:Optimal Power Allocation for multi-user amplify-and-forward wireless relay networks in which multiple source-destination pairs are assisted by a set of relays is investigated. Two relay Power Allocation strategies based on maximization of either i) the minimum rate among all users or ii) the weighted sum of rates are developed. A distributed implementation of the maximum weighted-sum-rate Power Allocation strategy is also studied. Numerical results demonstrate the efficiency of the proposed strategies and reveal their interesting throughput-fairness tradeoff in resource Allocation.
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Power Allocation in wireless multi user relay networks
IEEE Transactions on Wireless Communications, 2009Co-Authors: Khoa T Phan, Tho Lengoc, Sergiy A Vorobyov, Chintha TellamburaAbstract:In this paper, we consider an amplify-and-forward wireless relay system where multiple source nodes communicate with their corresponding destination nodes with the help of relay nodes. Conventionally, each relay equally distributes the available resources to its relayed sources. This approach is clearly sub-optimal since each user experiences dissimilar channel conditions, and thus, demands different amount of allocated resources to meet its quality-of-service (QoS) request. Therefore, this paper presents novel Power Allocation schemes to i) maximize the minimum signal-to-noise ratio among all users; ii) minimize the maximum transmit Power over all sources; iii) maximize the network throughput. Moreover, due to limited Power, it may be impossible to satisfy the QoS requirement for every user. Consequently, an admission control algorithm should first be carried out to maximize the number of users possibly served. Then, optimal Power Allocation is performed. Although the joint optimal admission control and Power Allocation problem is combinatorially hard, we develop an effective heuristic algorithm with significantly reduced complexity. Even though theoretically sub-optimal, it performs remarkably well. The proposed Power Allocation problems are formulated using geometric programming (GP), a well-studied class of nonlinear and nonconvex optimization. Since a GP problem is readily transformed into an equivalent convex optimization problem, optimal solution can be obtained efficiently. Numerical results demonstrate the effectiveness of our proposed approach.
Victor C M Leung - One of the best experts on this subject based on the ideXlab platform.
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joint opportunistic user scheduling and Power Allocation throughput optimisation and fair resource sharing
Iet Communications, 2018Co-Authors: Hu Jin, Victor C M LeungAbstract:Despite extensive studies on optimal Power Allocation, how to design an efficient joint user scheduling and Power Allocation scheme for uplink multiuser networks remains largely unexplored. This study investigates joint opportunistic user scheduling and Power Allocation in uplink multiuser networks to maximise user throughput subject to the Power and resource sharing constraints . By exploiting the cumulative distribution function-based scheduling method, the authors first characterise the optimal Power Allocation subject to both long-term and short-term Power constraints. Instead of calculating the transmit Power in an iterative and central manner, users can independently decide their instantaneous transmit Power in the proposed scheme, which facilitates the algorithm implementation for each user in uplink networks. The closed-form throughput of the proposed scheme is also derived, which can provide an efficient way to estimate and evaluate user performance. Numerical results reveal that compared with several benchmark schemes, the proposed scheme improves throughput performance significantly.
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Secure Communications in NOMA System: Subcarrier Assignment and Power Allocation
IEEE Journal on Selected Areas in Communications, 2018Co-Authors: Ning Yang, Keping Long, George K. Karagiannidis, Miao Pan, Victor C M LeungAbstract:Secure communication is a promising technology for wireless networks because it ensures secure transmission of information. In this paper, we investigate the joint subcarrier (SC) assignment and Power Allocation problem for non-orthogonal multiple access amplify-and-forward two-way relay wireless networks, in the presence of eavesdroppers. By exploiting cooperative jamming (CJ) to enhance the security of the communication link, we aim to maximize the achievable secrecy energy efficiency by jointly designing the SC assignment, user pair scheduling and Power Allocation. Assuming the perfect knowledge of the channel state information at the relay station, we propose a low-complexity subcarrier assignment scheme (SCAS-1), which is equivalent to many-to-many matching games, and then SCAS-2 is formulated as a secrecy energy efficiency maximization problem. The secure Power Allocation problem is modeled as a convex geometric programming problem, and then, solved by interior point methods. Simulation results demonstrate that the effectiveness of the proposed SSPA algorithms under scenarios of using and not using CJ, respectively.
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a distributed Power Allocation scheme for sum rate maximization on cognitive gmacs
IEEE Transactions on Communications, 2013Co-Authors: Sangwook Han, J.m. Cioffi, Hoon Kim, Youngnam Han, Victor C M LeungAbstract:This paper considers a distributed Power Allocation scheme for sum-rate-maximization under cognitive Gaussian multiple access channels (GMACs), where primary users and secondary users may communicate under mutual interference with the Gaussian noise. Formulating the problem as a standard nonconvex quadratically constrained quadratic problem (QCQP) provides a simple distributed method to find a solution using iterative Jacobian method instead of using centralized schemes. A totally asynchronous distributed Power Allocation for sum-rate maximization on cognitive GMACs is suggested. Simulation results show that this distributed algorithm for Power Allocation converges to a fixed point and the solution achieves almost the same performance as the exhaustive search.
