[논문]Distributed Carrier Aggregation in Small Cell Networks: A Game-theoretic Approach

Zhang, Yuanhui; Kan, Chunrong; Xu, Kun; Xu, Yuhua

doi:10.3837/tiis.2015.12.004

Distributed Carrier Aggregation in Small Cell Networks: A Game-theoretic Approach 원문보기

KSII Transactions on internet and information systems : TIIS, v.9 no.12, 2015년, pp.4799 - 4818

Zhang, Yuanhui (PLA University of Science and Technology) , Kan, Chunrong (PLA University of Science and Technology) , Xu, Kun (PLA Academy of National Defense Information) , Xu, Yuhua (PLA University of Science and Technology)

Abstract ▼ AI-Helper

In this paper, we investigate the problem of achieving global optimization for distributed carrier aggregation (CA) in small cell networks, using a game theoretic solution. To cope with the local interference and the distinct cost of intra-band and inter-band CA, we propose a non-cooperation game which is proved as an exact potential game. Furthermore, we propose a spatial adaptive play learning algorithm with heterogeneous learning parameters to converge towards NE of the game. In this algorithm, heterogeneous learning parameters are introduced to accelerate the convergence speed. It is shown that with the proposed game-theoretic approach, global optimization is achieved with local information exchange. Simulation results validate the effectivity of the proposed game-theoretic CA approach.

주제어

AI 본문요약
AI-Helper

성능/효과

To cope with the local interference and the distinct cost of intra-band and inter-band CA, we proposed a non-cooperation game which was proved to be an exact potential game. Furthermore, we proposed a spatial adaptive play algorithm with heterogeneous learning parameters (SAP-H) to converge towards NE of the game. In this algorithm, heterogeneous learning parameters were introduced to accelerate the convergence speed.
Furthermore, we proposed a spatial adaptive play algorithm with heterogeneous learning parameters (SAP-H) to converge towards NE of the game. In this algorithm, heterogeneous learning parameters were introduced to accelerate the convergence speed. It is shown that with the proposed game-theoretic approach, global optimization is achieved with local information.
In this algorithm, heterogeneous learning parameters were introduced to accelerate the convergence speed. It is shown that with the proposed game-theoretic approach, global optimization is achieved with local information. Simulation results validated the effectivity of the proposed game-theoretic CA approach.
We obtain the best NE and the worst NE by taking 1000 independent trials and then taking the maximum and minimum throughput after convergence for different network layouts, respectively. Note that the performance of the proposed SAP-H algorithm is close to the best NE and has approximate 10% improvement than the worst NE. The gap among them is nearly uniform.
It is shown that with the proposed game-theoretic approach, global optimization is achieved with local information. Simulation results validated the effectivity of the proposed game-theoretic CA approach. In addition, we studied other factors to affect the network throughput in performing CA and obtained some meaningful conclusions.
To cope with the local interference and the distinct cost of intra-band and inter-band CA, we proposed a non-cooperation game which was proved to be an exact potential game. Furthermore, we proposed a spatial adaptive play algorithm with heterogeneous learning parameters (SAP-H) to converge towards NE of the game.

후속연구

In addition, we studied other factors to affect the network throughput in performing CA and obtained some meaningful conclusions. In future, we plan to study QoS-aware CA in heterogeneous wireless communication system.

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표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

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