Browsing by Author "Liou, Yi-Shing"

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A Bargaining Game Based Access Network Selection Scheme for HetNet
(2014-01-01)
Liou, Yi-Shing
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Gau, Rung-Hung
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Chang, Chung-Ju
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電機資訊學士班
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Undergraduate Honors Program of Electrical Engineering and Computer Science
We propose a novel bargaining-game-based access network selection scheme for call requests in heterogeneous networks (HetNet). The bargaining game takes into consideration a number of factors including the mobility pattern of the mobile device, the load of the candidate access network, and the preference of the candidate access network to the call request. The studied bargaining game has a unique solution since the set of feasible payoff vectors is convex. Simulation results show that the proposed scheme could significantly outperform the TOPSIS scheme and the evolutionary game approach in terms of the handoff occurrence ratio and the call dropping probability.
Dynamically Tuning Aggression Levels for Capacity-Region-Aware Medium Access Control in Wireless Networks
(2014-04-01)
Liou, Yi-Shing
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Gau, Rung-Hung
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Chang, Chung-Ju
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
We propose adaptive capacity-region-aware algorithms for medium access control in wireless networks. In particular, the proposed algorithms are aware of the information-theoretic capacity region of a multiple access channel. According to the proposed algorithms, a node dynamically adjusts its channel access strategy based on the previous strategies of other nodes and the channel feedback. A strategy is composed of a transmission threshold and an aggression level. We propose symmetric learning algorithms for maximizing throughput. In addition, we propose asymmetric learning algorithms to strike a good balance between throughput and fairness. Furthermore, we propose novel methods to properly choose a finite number of available data transmission rates. We use both analytical results and simulation results to justify the usage of the proposed algorithms.
Group Partition and Dynamic Rate Adaptation for Scalable Capacity-Region-Aware Device-to-Device Communications
(2015-02-01)
Liou, Yi-Shing
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Gau, Rung-Hung
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Chang, Chung-Ju
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電機工程學系
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Department of Electrical and Computer Engineering
In this paper, we propose using group partition and dynamic rate adaptation for scalable throughput optimization of capacity-region-aware device-to-device communications. We adopt network information theory that allows a receiving device to simultaneously decode multiple packets from multiple transmitting devices, as long as the vector of transmitting rates is inside the capacity region. Based on graph theory, devices are first partitioned into subgroups. To optimize the throughput of a subgroup, instead of directly solving an integer-linear programming problem, we propose using a fast iterative algorithm to select active devices and using aggression levels for rate adaptation based on channel state information. Simulation results show that the proposed algorithm is scalable and could significantly outperform the greedy algorithm by more than 50%.
Group Partition for Capacity-Region-Aware Device-to-Device Communications
(2014)
Liou, Yi-Shing
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Gau, Rung-Hung
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Chang, Chung-Ju
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電機工程學系
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Department of Electrical and Computer Engineering
In this paper, we propose a group partition approach for scalable throughput optimization of capacity-region-aware Device-to-Device communications. Instead of the conventional collision model, we adopt network information theory that allows a receiving device to simultaneously decode multiple packets from multiple transmitting devices, as long as the vector of transmitting rates is inside the capacity region. We propose a novel approach to partition devices into subgroups based on coloring a conflict graph and then solve an optimization problem for each subgroup. In particular, the formation of the conflict graph explicitly takes the capacity region into consideration. Simulation results show that the proposed approach could significantly outperform the greedy algorithm.
Opportunistic Polling for Capacity-Region-Aware MAC in Wireless Networks with Partial CSI
(2015)
Liou, Yi-Shing
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Gau, Rung-Hung
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Chang, Chung-Ju
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電機工程學系
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Department of Electrical and Computer Engineering
In this paper, we propose two opportunistic polling algorithms for capacity-region-aware medium access control (MAC) in wireless networks with partial channel state information. Based on the probability density function of the unknown channel gain, the proposed algorithms opportunistically exploit the capacity region of a multiple access channel in network information theory and benefit from successive interference cancellation techniques. Simulation results show that both algorithms could increase the network throughput. Furthermore, the active opportunistic polling algorithm could increase the network throughput by more than 30%.