Self-organized cooperative 5G RANs with intelligent optical backhauls for mobile cloud computing

In the near future, it is expected that mobile cloud computing (MCC) will benefit enterprises by improving network manageability and maintenance, as well as end users with respect to sharing computing resources. For this purpose, this paper proposes self-organized cooperative 5G Radio Access Networks (RANs) with intelligent elastic optical backhauls. Effective joint optical and radio resource management is implemented in order to satisfy the stringent delay requirements of the emerging MCC applications and increase the overall cell throughput. In addition, spatiotemporal data of the cellular network are observed, analyzed, and stored constantly during the operation of the network. These data provide the capability of dynamic adjustment to channel conditions, as well as effective structuring of the RANs. The proposed techniques increase the Signal-to-Interference Ratio (SINR), and enable future networks to meet the demands of MCC, as they are able to handle a large number of small packets in an efficient manner.

[1]  Sukhwinder Singh,et al.  Mobile Cloud Computing , 2014 .

[2]  Hans D. Schotten,et al.  Access Schemes for Mobile Cloud Computing , 2010, 2010 Eleventh International Conference on Mobile Data Management.

[3]  Satoshi Nagata,et al.  Coordinated multipoint transmission and reception in LTE-advanced: deployment scenarios and operational challenges , 2012, IEEE Communications Magazine.

[4]  Ting Peng,et al.  An improved iterative channel estimation based LTE Downlink , 2012, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery.

[5]  Jin Yang,et al.  UE's role in LTE advanced heterogeneous networks , 2012, IEEE Communications Magazine.

[6]  Luis Miguel Contreras Murillo,et al.  Toward cloud-ready transport networks , 2012, IEEE Communications Magazine.

[7]  Qing Wang,et al.  Wireless network cloud: Architecture and system requirements , 2010, IBM J. Res. Dev..

[8]  Daiyuan Peng,et al.  An SMDP-Based Service Model for Interdomain Resource Allocation in Mobile Cloud Networks , 2012, IEEE Transactions on Vehicular Technology.

[9]  Zhong Liu,et al.  A cooperative target location algorithm based on time difference of arrival in wireless senor networks , 2009, 2009 International Conference on Mechatronics and Automation.

[10]  Albert Kai-Sun Wong,et al.  An Enhanced Toa-Based Wireless Location Estimation Algorithm for Dense NLOS Environments , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[11]  Mehdi Amirijoo,et al.  Use Cases, Requirements and Assessment Criteria for Future Self-Organising Radio Access Networks , 2008, IWSOS.

[12]  Yung-Hsiang Lu,et al.  Cloud Computing for Mobile Users: Can Offloading Computation Save Energy? , 2010, Computer.

[13]  Yuanqiu Luo,et al.  Time- and Wavelength-Division Multiplexed Passive Optical Network (TWDM-PON) for Next-Generation PON Stage 2 (NG-PON2) , 2013, Journal of Lightwave Technology.

[14]  Robert Baldemair,et al.  Improved Data-Aided Channel Estimation in LTE PUCCH Using a Tensor Modeling Approach , 2010, 2010 IEEE International Conference on Communications.