CLC number: TN92
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2018-05-10
Cited: 0
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Feng Wei, Wei-xia Zou. Suboptimal network coding subgraph algorithms for 5G minimum-cost multicast networks[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(5): 662-673.
@article{title="Suboptimal network coding subgraph algorithms for 5G minimum-cost multicast networks",
author="Feng Wei, Wei-xia Zou",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="19",
number="5",
pages="662-673",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1700020"
}
%0 Journal Article
%T Suboptimal network coding subgraph algorithms for 5G minimum-cost multicast networks
%A Feng Wei
%A Wei-xia Zou
%J Frontiers of Information Technology & Electronic Engineering
%V 19
%N 5
%P 662-673
%@ 2095-9184
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1700020
TY - JOUR
T1 - Suboptimal network coding subgraph algorithms for 5G minimum-cost multicast networks
A1 - Feng Wei
A1 - Wei-xia Zou
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 19
IS - 5
SP - 662
EP - 673
%@ 2095-9184
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1700020
Abstract: To reduce the transmission cost in 5G multicast networks that have separate control and data planes, we focus on the minimum-power-cost network-coding subgraph problem for the coexistence of two multicasts in wireless networks. We propose two suboptimal algorithms as extensions of the Steiner tree multicast. The critical 1-cut path eliminating (C1CPE) algorithm attempts to find the minimum-cost solution for the coexistence of two multicast trees with the same throughput by reusing the links in the topology, and keeps the solution decodable by a coloring process. For the special case in which the two multicast trees share the same source and destinations, we propose the extended selective closest terminal first (E-SCTF) algorithm out of the C1CPE algorithm. Theoretically the complexity of the E-SCTF algorithm is lower than that of the C1CPE algorithm. Simulation results show that both algorithms have superior performance in terms of power cost and that the advantage is more evident in networks with ultra-densification.
[1]Agyapong PK, Iwamura M, Staehle D, et al., 2014. Design considerations for a 5G network architecture. IEEE Commun Mag, 52(11):65-75.
[2]Akyildiz IF, Nie S, Lin SC, et al., 2016. 5G roadmap: 10 key enabling technologies. Comput Netw, 106:17-48.
[3]Ali E, Ismail M, Nordin R, et al., 2017. Beamforming techniques for massive MIMO systems in 5G: overview, classification, and trends for future research. Front Inform Technol Electron Eng, 18(6):753-772.
[4]Andrews JG, Buzzi S, Choi W, et al., 2014. What will 5G be? IEEE J Sel Areas Commun, 32(6):1065-1082.
[5]Baldemair R, Irnich T, Balachandran K, et al., 2015. Ultra-dense networks in millimeter-wave frequencies. IEEE Commun Mag, 53(1):202-208.
[6]Chen SZ, Kang SL, 2018. A tutorial on 5G and the progress in China. Front Inform Technol Electron Eng, 19(3):309-321.
[7]Chen SZ, Qin F, Hu B, et al., 2016. User-centric ultra-dense networks for 5G: challenges, methodologies, and directions. IEEE Wirel Commun, 23(2):78-85.
[8]Chiang M, Low SH, Calderbank AR, et al., 2007. Layering as optimization decomposition: a mathematical theory of network architectures. Proc IEEE, 95(1):255-312.
[9]Choi J, 2015. Iterative methods for physical-layer multicast beamforming. IEEE Trans Wirel Commun, 14(9):5185-5196.
[10]He SW, Huang YM, Wang HM, et al., 2014. Leakage-aware energy-efficient beamforming for heterogeneous multicell multiuser systems. IEEE J Sel Areas Commun, 32(6): 1268-1281.
[11]Heindlmaier M, Lun DS, Traskov D, et al., 2011. Wireless inter-session network coding—an approach using virtual multicasts. IEEE Int Conf on Communications, p.1-5.
[12]Ho T, Medard M, Koetter R, et al., 2006. A random linear network coding approach to multicast. IEEE Trans Inform Theory, 52(10):4413-4430.
[13]Jiang DD, Xu ZZ, Li WP, et al., 2015. Network coding-based energy-efficient multicast routing algorithm for multi-hop wireless networks. J Syst Softw, 104:152-165.
[14]Kotronis V, Dimitropoulos X, Ager B, 2012. Outsourcing the routing control logic: better Internet routing based on SDN principles. Proc 11th ACM Workshop on Hot Topics in Networks, p.55-60.
[15]Kulkarni MN, Ghosh A, Andrews JG, 2016. A comparison of MIMO techniques in downlink millimeter wave cellular networks with hybrid beamforming. IEEE Trans Commun, 64(5):1952-1967.
[16]Li JZ, Ai B, He RS, et al., 2017. Indoor massive multiple-input multiple-output channel characterization and performance evaluation. Front Inform Technol Electron Eng, 18(6):773-787.
[17]Li SY, Sun W, Hua CC, 2016. Optimal resource allocation for heterogeneous traffic in multipath networks. Int J Commun Syst, 29(1):84-98.
[18]Lun DS, Ratnakar N, Koetter R, et al., 2005. Achieving minimum-cost multicast: a decentralized approach based on network coding. Proc IEEE 24th Annual Joint Conf of IEEE Computer and Communications Societies, p.1607-1617.
[19]Ma Z, Zhang ZQ, Ding ZG, et al., 2015. Key techniques for 5G wireless communications: network architecture, physical layer, and MAC layer perspectives. Sci China Inform Sci, 58(4):1-20.
[20]Rajawat K, Gatsis N, Giannakis GB, 2011. Cross-layer designs in coded wireless fading networks with multicast. IEEE/ACM Trans Netw, 19(5):1276-1289.
[21]Ramanathan S, 1996. Multicast tree generation in networks with asymmetric links. IEEE/ACM Trans Netw, 4(4):558-568.
[22]Rappaport TS, Murdock JN, Gutierrez F, 2011. State of the art in 60-GHz integrated circuits and systems for wireless communications. Proc IEEE, 99(8):1390-1436.
[23]Rappaport TS, Sun S, Mayzus R, et al., 2013. Millimeter wave mobile communications for 5G cellular: it will work! IEEE Access, 1:335-349.
[24]Ribeiro A, Giannakis G B, 2010. Separation principles in wireless networking. IEEE Trans Inform Theory, 56(9): 4488-4505.
[25]Riemensberger M, Utschick W, 2014. A polymatroid flow model for network coded multicast in wireless networks. IEEE Trans Inform Theory, 60(1):443-460.
[26]Rusek F, Persson D, Lau BK, et al., 2013. Scaling up MIMO: opportunities and challenges with very large arrays. IEEE Signal Process Mag, 30(1):40-60.
[27]Shokri-Ghadikolaei H, Fischione C, 2016. The transitional behavior of interference in millimeter wave networks and its impact on medium access control. IEEE Trans Commun, 64(2):723-740.
[28]Stai E, Loulakis M, Papavassiliou S, 2015. Cross-layer design of wireless multihop networks over stochastic channels with time-varying statistics. IEEE Trans Wirel Commun, 14(12):6967-6980.
[29]Su LY, Yang CY, Chih-Lin I, 2016. Energy and spectral efficient frequency reuse of ultra dense networks. IEEE Trans Wirel Commun, 15(8):5384-5398.
[30]Szabó D, Németh F, Sonkoly B, et al., 2015. Towards the 5G revolution: a software defined network architecture exploiting network coding as a service. Proc ACM Conf on Special Interest Group on Data Communication, p.105-106.
[31]Wang C, Guo ST, Yang YY, et al., 2016. An optimization framework for mobile data collection in energy-harvesting wireless sensor networks. IEEE Trans Mobile Comput, 15(12):2969-2986.
[32]Wang CC, Shroff NB, 2010. Pairwise intersession network coding on directed networks. IEEE Trans Inform Theory, 56(8):3879-3900.
[33]Wang J, Li Y, Wang XM, 2007. Network coding based multicast in Internet. Int Conf on Parallel Processing Workshops, p.44.
[34]Wei F, Zou WX, 2017. Steiner-tree-based 2-cut-set network coding subgraph algorithm in wireless multicast network. Proc Int Conf in Communications, Signal Processing, and Systems, p.373-381.
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