Dynamic Radio Cooperation for User-Centric Cloud-RAN With Computing Resource Sharing

A novel dynamic radio-cooperation strategy is proposed for a Cloud Radio Access Network (Cloud-RAN) consisting of multiple Remote Radio Heads connected to a central Virtual Base Station (VBS) pool. In particular, the key capabilities of Cloud-RAN in computing-resource sharing and real-time communication among the VBSs are leveraged to design a joint dynamic radio clustering and cooperative beamforming scheme that maximizes the downlink Weighted Sum-Rate System Utility (WSRSU). Due to the combinatorial nature of the radio clustering process and to the non-convexity of the cooperative beamforming design, the underlying optimization problem is NP-hard, and is extremely difficult to solve for a large network. The proposed approach aims for a suboptimal solution by transforming the original problem into a Mixed-Integer Second-Order Cone Program (MI-SOCP) and applying Sequential Convex Approximation (SCA) to derive a novel iterative algorithm. Numerical simulation results show that our low-complexity algorithm provides near-optimal performance in terms of WSRSU while significantly outperforming conventional radio clustering and beamforming schemes. Additionally, the results also demonstrate the significant improvement in computing-resource utilization of Cloud-RAN over a traditional RAN with distributed computing resources.

[1]  Tony Q. S. Quek,et al.  Cross-Layer Resource Allocation With Elastic Service Scaling in Cloud Radio Access Network , 2015, IEEE Transactions on Wireless Communications.

[2]  A. Goldsmith,et al.  The effect of time synchronization errors on the performance of cooperative MISO systems , 2004, IEEE Global Telecommunications Conference Workshops, 2004. GlobeCom Workshops 2004..

[3]  Paola Parolari,et al.  Optical fiber solution for mobile fronthaul to achieve cloud radio access network , 2013, 2013 Future Network & Mobile Summit.

[4]  Dario Pompili,et al.  Dynamic provisioning and allocation in Cloud Radio Access Networks (C-RANs) , 2015, Ad Hoc Networks.

[5]  Navid Nikaein,et al.  Critical issues of centralized and cloudified LTE-FDD Radio Access Networks , 2015, 2015 IEEE International Conference on Communications (ICC).

[6]  Vikram Srinivasan,et al.  CloudIQ: a framework for processing base stations in a data center , 2012, Mobicom '12.

[7]  Supeng Leng,et al.  Joint Scheduling and Beamforming Coordination in Cloud Radio Access Networks With QoS Guarantees , 2016, IEEE Transactions on Vehicular Technology.

[8]  Long Bao Le,et al.  Sparse precoding design for cloud-RANs sum-rate maximization , 2015, 2015 IEEE Wireless Communications and Networking Conference (WCNC).

[9]  Yuanming Shi,et al.  Group Sparse Beamforming for Green Cloud-RAN , 2013, IEEE Transactions on Wireless Communications.

[10]  C-ran the Road towards Green Ran , 2022 .

[11]  Dario Pompili,et al.  Dynamic Radio Cooperation for Downlink Cloud-RANs with Computing Resource Sharing , 2015, 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems.

[12]  Stephen P. Boyd,et al.  Branch and bound algorithm for computing the minimum stability degree of parameter-dependent linear systems , 1991, International Journal of Robust and Nonlinear Control.

[13]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[14]  Lei Li,et al.  Recent Progress on C-RAN Centralization and Cloudification , 2014, IEEE Access.

[15]  Karthikeyan Sundaresan,et al.  FluidNet: A Flexible Cloud-Based Radio Access Network for Small Cells , 2013, IEEE/ACM Transactions on Networking.

[16]  Gerhard Fettweis,et al.  Interference Analysis in Time and Frequency Asynchronous Network MIMO OFDM Systems , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[17]  Dario Pompili,et al.  VMAP: Proactive thermal-aware virtual machine allocation in HPC cloud datacenters , 2012, 2012 19th International Conference on High Performance Computing.

[18]  Antti Tölli,et al.  Fast Converging Algorithm for Weighted Sum Rate Maximization in Multicell MISO Downlink , 2012, IEEE Signal Processing Letters.

[19]  Dario Pompili,et al.  Elastic resource utilization framework for high capacity and energy efficiency in cloud RAN , 2016, IEEE Communications Magazine.

[20]  Long Bao Le,et al.  Coordinated Multipoint ( CoMP ) Transmission Design for Cloud-RANs with Limited Fronthaul Capacity Constraints , 2015 .

[21]  Dario Pompili,et al.  QuaRo: A Queue-Aware Robust Coordinated Transmission Strategy for Downlink C-RANs , 2016, 2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON).

[22]  Stephen P. Boyd,et al.  Branch and Bound Methods , 1987 .

[23]  John M. Cioffi,et al.  Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design , 2008, IEEE Trans. Wirel. Commun..

[24]  Chenyang Yang,et al.  Training Resource Allocation for User-Centric Base Station Cooperation Networks , 2016, IEEE Transactions on Vehicular Technology.

[25]  Navid Nikaein,et al.  Processing Radio Access Network Functions in the Cloud: Critical Issues and Modeling , 2015, MCS '15.

[26]  Mugen Peng,et al.  Resource Allocation Optimization for Delay-Sensitive Traffic in Fronthaul Constrained Cloud Radio Access Networks , 2014, IEEE Systems Journal.

[27]  Amir Beck,et al.  A sequential parametric convex approximation method with applications to nonconvex truss topology design problems , 2010, J. Glob. Optim..

[28]  Lingyang Song,et al.  Computing resource constraint in wireless M2M communications , 2016, 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[29]  Tony Q. S. Quek,et al.  Adaptive Compression and Joint Detection for Fronthaul Uplinks in Cloud Radio Access Networks , 2015, IEEE Transactions on Communications.

[30]  Shlomo Shamai,et al.  Robust and Efficient Distributed Compression for Cloud Radio Access Networks , 2012, IEEE Transactions on Vehicular Technology.

[31]  Matti Latva-aho,et al.  Weighted sum-rate maximization for MISO downlink cellular networks via branch and bound , 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

[32]  Vincent K. N. Lau,et al.  Joint Power and Antenna Selection Optimization in Large Cloud Radio Access Networks , 2013, IEEE Transactions on Signal Processing.

[33]  Federico Boccardi,et al.  A dynamic joint clustering scheduling algorithm for downlink CoMP systems with limited CSI , 2012, 2012 International Symposium on Wireless Communication Systems (ISWCS).

[34]  Rui Zhang,et al.  Downlink and Uplink Energy Minimization Through User Association and Beamforming in C-RAN , 2014, IEEE Transactions on Wireless Communications.

[35]  Markku J. Juntti,et al.  Optimal Energy-Efficient Transmit Beamforming for Multi-User MISO Downlink , 2015, IEEE Transactions on Signal Processing.

[36]  Anumula Satheesh,et al.  Joint Cloud and Wireless Networks Operations in Mobile Cloud Computing Environments With Telecom Operator Cloud , 2016 .

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

[38]  Zhisheng Niu,et al.  Joint Scheduling and Dynamic Clustering in Downlink Cellular Networks , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[39]  Stephen P. Boyd,et al.  Applications of second-order cone programming , 1998 .

[40]  Long Bao Le,et al.  Energy-efficient coordinated transmission for Cloud-RANs: Algorithm design and trade-off , 2014, 2014 48th Annual Conference on Information Sciences and Systems (CISS).

[41]  Yvonne Freeh,et al.  Interior Point Algorithms Theory And Analysis , 2016 .

[42]  Wei Yu,et al.  Sparse Beamforming and User-Centric Clustering for Downlink Cloud Radio Access Network , 2014, IEEE Access.

[43]  Lingyang Song,et al.  How Much Computing Capability Is Enough to Run a Cloud Radio Access Network? , 2017, IEEE Communications Letters.

[44]  Donald Goldfarb,et al.  Second-order cone programming , 2003, Math. Program..

[45]  Daniel Pérez Palomar,et al.  A tutorial on decomposition methods for network utility maximization , 2006, IEEE Journal on Selected Areas in Communications.