Cloud Assisted Resource Management for Hyper-Dense Small Cell Networks

Hyper-dense deployment of small cells and reuse of available spectrum resources within a wireless cellular network are two promising techniques that can enhance network capacity to satisfy the ever increasing demand for high volumes of mobile data traffic. With the use of these techniques in a network, the network is prone to severe co-channel interference (CCI), due to short distances between the densely deployed small cells. Therefore, to avoid degradation of the network capacity, it is necessary to manage CCI by jointly allocating resources of the small cells. Further, the resource allocation scheme should minimize the computational burden for low-cost small cell base stations (BSs), be able to adapt to time-varying network load conditions, and reduce signaling overhead in the small cell backhauls with limited capacity. To this end, in this paper we present a resource allocation scheme which operates on two time-scales and utilizes cloud computing to determine resource allocation decisions. The resource allocation decisions are made at the cloud in a slow time-scale, and are further optimized at the BSs in a fast time-scale in order to adapt the decisions to fast varying wireless channel conditions. Achievable network capacity enhancements using the proposed scheme are demonstrated through simulation results.

[1]  Reinaldo A. Valenzuela,et al.  Coordinating multiple antenna cellular networks to achieve enormous spectral efficiency , 2006 .

[2]  Ulas C. Kozat,et al.  FAST CLOUD: Pushing the Envelope on Delay Performance of Cloud Storage With Coding , 2013, IEEE/ACM Transactions on Networking.

[3]  Xin Chen,et al.  Toward Optimal Admission Control and Resource Allocation for LTE-A Femtocell Uplink , 2015, IEEE Transactions on Vehicular Technology.

[4]  Xiaohui Liang,et al.  Exploiting Geo-Distributed Clouds for a E-Health Monitoring System With Minimum Service Delay and Privacy Preservation , 2014, IEEE Journal of Biomedical and Health Informatics.

[5]  Supratim Deb,et al.  Algorithms for Enhanced Inter-Cell Interference Coordination (eICIC) in LTE HetNets , 2013, IEEE/ACM Transactions on Networking.

[6]  Wan Choi,et al.  Optimal Rate Adaptation for Hybrid ARQ in Time-Correlated Rayleigh Fading Channels , 2011, IEEE Transactions on Wireless Communications.

[7]  John V. Guttag,et al.  Power-demand routing in massive geo-distributed systems , 2010 .

[8]  F. Richard Yu,et al.  Cloud radio access networks (C-RAN) in mobile cloud computing systems , 2014, 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[9]  Li-Chun Wang,et al.  Cooperative Hierarchical Cellular Systems in LTE-A Networks , 2015, IEEE Systems Journal.

[10]  Krishna Balachandran,et al.  Network-centric cooperation schemes for uplink interference management in cellular networks , 2013, Bell Labs Technical Journal.

[11]  Khairi Ashour Hamdi,et al.  A Unified Framework for the Analysis of Fractional Frequency Reuse Techniques , 2014, IEEE Transactions on Communications.

[12]  Athanasios V. Vasilakos,et al.  Small cell dynamic TDD transmissions in heterogeneous networks , 2014, 2014 IEEE International Conference on Communications (ICC).

[13]  Omer Gurewitz,et al.  Distributed Inter-Cell Interference Mitigation Via Joint Scheduling and Power Control Under Noise Rise Constraints , 2012, IEEE Transactions on Wireless Communications.

[14]  Hao Liang,et al.  Two Time-Scale Cross-Layer Scheduling for Cellular/WLAN Interworking , 2014, IEEE Transactions on Communications.

[15]  Karla L. Hoffman,et al.  A method for globally minimizing concave functions over convex sets , 1981, Math. Program..

[16]  Andrea J. Goldsmith,et al.  Evolution of Base Stations in Cellular Networks: Denser Deployment versus Coordination , 2008, 2008 IEEE International Conference on Communications.

[17]  Ari Hottinen,et al.  Increasing downlink cellular throughput with limited network MIMO coordination , 2009, IEEE Transactions on Wireless Communications.

[18]  Harish Viswanathan,et al.  Self-Organizing Dynamic Fractional Frequency Reuse in OFDMA Systems , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.