H2H/M2M共存场景下基于图论的干扰协调机制

doi:10.11896/j.issn.1002-137X.2019.05.009

Computer Science ›› 2019, Vol. 46 ›› Issue (5): 62-66.doi: 10.11896/j.issn.1002-137X.2019.05.009

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Graph Theory Based Interference Coordination for H2H/M2M Coexisting Scenarios

SUI Nan-nan¹, XU You-yun², WANG Cong¹, XIE Wei¹, ZHU Yun³

(College of Communications Engineering,PLA Army Engineering University,Nanjing 210007,China)¹
(National Engineering Research Center of Communication and Network Technology,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)²
(School of Physics and Electronic Information,Gannan Normal University,Ganzhou,Jiangxi 341000,China)³

Received:2018-05-21 Revised:2018-09-14 Published:2019-05-15

Abstract

Abstract: For human-to-human (H2H) and machine-to-machine (M2M)communications coexisting scenarios in the co-channel deployed LTE-A heterogeneous networks,a maximum independent set (MIS) based interference coordination and resource block (RB) expansion allocation algorithm (CGMMIS) was proposed to maximize the system sum rate while ensuring RB allocation continuity.Firstly,the interference graph is obtained according to the relative interference between two nodes.Secondly,CGMMIS algorithm divides the nodes with strong interference to each other into different MISs and maximizes the sum channel gain of the nodes in the MIS.However,a node may belongs to multiple MISs under this circumstance.Lastly,in order to guarantee the consecutive allocation of RBs,the RB expansion allocation me-thod is exploited in CGMMIS algorithm,in which the node will only select the MIS that can maximize its achievable rate.Simulation results demonstrate that in the dense deployment scenario of M2M devices,the proposed CGMMIS algorithm is superior to both the non-cooperative algorithm and the random graph coloring based MIS search algorithm in terms of system sum rate.

Key words: LTE-A, Machine to machine (M2M) communications, Maximum independent set, RB expansion allocation

CLC Number:

TN929.5

SUI Nan-nan, XU You-yun, WANG Cong, XIE Wei, ZHU Yun. Graph Theory Based Interference Coordination for H2H/M2M Coexisting Scenarios[J].Computer Science, 2019, 46(5): 62-66.

References

[1]3GPP TS 22.368 V11.0.0.Service Requirements for Machine-Type Communications [S].Istanbul:3GPP,2010.
[2]PALATTELLA M-R,DOHLER M,GRIECO A,et al.Internet of Things in the 5G Era:Enablers,Architecture,and Business Models [J].IEEE Journal on Selected Areas in Communications,2016,34(3):510-527.
[3]OECD.Machine-to-Machine Communications:Connecting Bil-lions of Devices [R].Paris:OECD Digital Economy Papers,2012.
[4]GHAVIMI F,CHEN H H.M2M Communications in 3GPPLTE/LTE-A Networks:Architectures,Service Requirements,Challenges,and Applications [J].IEEE Communications Surveys & Tutorials,2015,17(2):525-549.
[5]WONG I C,OTERI O,MCCOY W.Optimal Resource Allocation in Uplink SC-FDMA Systems [J].IEEE Transactions on Wireless Communications,2009,8(5):2161-2165.
[6]AIJAZ A,TSHANGINI M,NAKHAI M R,et al.Energy-Efficient Uplink Resource Allocation in LTE Networks With M2M/H2H Co-Existence Under Statistical QoS Guarantees [J].IEEE Transactions on Communications,2014,62(7):2353-2365.
[7]LEE S B,PEFKIANAKIS I,MEYERSON A,et al.Proportional Fair Frequency-Domain Packet Scheduling for 3GPP LTE Uplink [C]∥Proceedings of International Confernece on Computer Communications.Riode Janeiro:IEEE Press,2009:2611-2615.
[8]CHEN S,MA R,CHEN H H,et al.Machine-to-Machine Communications in Ultra-Dense Networks－A Survey [J].IEEE Communications Surveys & Tutorials,2017,19(3):1478-1503.
[9]GRASSI A,PIRO G,BACCI G,et al.Uplink Resource Management in 5G:When a Distributed and Energy-Efficient Solution Meets Power and QoS Constraints [J].IEEE Transactions on Vehicular Technology,2017,66(6):5176-5189.
[10]KHAMIDEHI B,SABBAGHIAN M.Resource Allocation forSC-FDMAFemtocell Networks [J].IEEE Transactions on Vehicular Technology,2017,PP(99):1.
[11]AHUJA K,XIAO Y,SCHAAR M.Distributed InterferenceManagement Policies for Heterogeneous Small Cell Networks [J].IEEE Journal on Selected Areas in Communications,2015,33(6):1112-1126.
[12]SAMARAKOON S,BENNIS M,SAAD W,et al.Dynamic Clustering and on/off Strategies for Wireless Small Cell Networks [J].IEEE Transactions on Wireless Communications,2016,15(3):2164-2178.

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